Content

° The internship ties in directly with the student’s present domain of study at the FEB.

° It is solely the student’s responsibility to scout for a viable internship position

° The student follows the procedure for internship applications mentioned on the FEB student portal.

° Only upon approval of the internship coordinator and Education & Students Services Department, the student can validate the internship in the individual study programme.

More information can be found on the FEB student portal.

Course material

Not applicable

Explanation

Evaluation characteristics

The final evaluation of the internship is based on two sources of information:

1. A performance report by the internship mentor in the company

2. An individual reflection report by the student

More information can be found on the FEB student portal.

Determination final result

*The faculty’s internship coordinator is ultimately responsible for the final score but will take into account the score of the internship mentor.

*If a student failed to show up on the performance interview and/or failed to hand in the reflective report in time, the student will obtain a ‘fail’ for the entire course.

*If a student fails to observe the deadline for handing in the evaluation documents the student will obtain a ‘fail’ for the course unless a new deadline was requested and formally acknowledged by the FEB based upon well-founded facts.

Important notice

Students who repeatedly or gravely breach the requirements as laid down in the agreement with the internship provider will be removed from the internship project and will obtain a ‘fail’. These students will not be entitled to do an alternative task and they will not have the opportunity to retake the internship project in any later examination period at this faculty.

Information about retaking exams

Content

° The internship ties in directly with the student’s present domain of study at the FEB.

° It is solely the student’s responsibility to scout for a viable internship position

° The student follows the procedure for internship applications mentioned on the FEB student portal.

° Only upon approval of the internship coordinator and Education & Students Services Department, the student can validate the internship in the individual study programme.

More information can be found on the FEB student portal.

Course material

Not applicable

Explanation

Evaluation characteristics

The final evaluation of the internship is based on two sources of information:

1. A performance report by the internship mentor in the company

2. An individual reflection report by the student

More information can be found on the FEB student portal.

Determination final result

*The faculty’s internship coordinator is ultimately responsible for the final score but will take into account the score of the internship mentor.

*If a student failed to show up on the performance interview and/or failed to hand in the reflective report in time, the student will obtain a ‘fail’ for the entire course.

*If a student fails to observe the deadline for handing in the evaluation documents the student will obtain a ‘fail’ for the course unless a new deadline was requested and formally acknowledged by the FEB based upon well-founded facts.

Important notice

Students who repeatedly or gravely breach the requirements as laid down in the agreement with the internship provider will be removed from the internship project and will obtain a ‘fail’. These students will not be entitled to do an alternative task and they will not have the opportunity to retake the internship project in any later examination period at this faculty.

Information about retaking exams

Content

Part 1: Technology and innovation dynamics/systems: Key concepts and Insights
Part 2: Defining and implementing an innovation strategy (at the level of the firm)
Part 3: Management of New Product Development processes (Project level)

Each part provides the students with a grounded and scientific approach towards important aspects of the innovation process. As a consequence, major scientific as well as application-oriented articles are provided as reading materials for each module.

The first part highlights the disciplinary roots or origins of the innovation process. More specifically, we highlight economic studies of the innovation process. These studies delve deeper into the work and insights of Joseph Schumpeter on the role of entrepreneurs and established companies and market pull and technology push dynamics. In addition we will elaborate insights on the level of innovation systems including the relevancy of (support) policies (e.g. patent systems) as well as the role of research centers and universities within such systems.

The second part develops models of the innovation process and examines the strategic management of technology and innovation on the level of the firm. Both defining an innovation strategy and implementing the innovation strategy by means of concepts and practices such as the development of technology portfolios (including selection criteria for innovation projects and programs) and technology roadmaps will be discussed. Major issues in organising the effective implementation of innovation strategies will be introduced (e.g. Organisational Ambidexterity, Venturing,.. .). We will also look at the nature and relevance of alliances and cooperation for the innovative performance of the firm.

The third part discusses the management of day-to-day operations in innovation environments. We discuss the following themes: (1) organising innovation activities and new product development projects, (2) critical success factors in managing innovation projects, (3) the concept of project performance in innovative settings, (4) techniques and approaches to support project management in innovative environments, and (5) the management of innovative teams and professionals.

Course material

Used Course Material
Handbook: Innovation Management and Strategy, Van Looy. McGraw Hill, 2016. (ISBN: 9781308882987)
Articles and literature
Slides, transparencies, courseware

Toledo
* Toledo is used for this learning activity to share readings, lecture slides, etc.

Format: more information

Students acquire in-depth insights in the management of innovation and technology in a course that combines traditional lectures and a group assignment.

For the group assignment students write a paper and give a poster presentation. Students demonstrate their ability to analyse and understand innovation dynamics. Given the scope of the course, topics can be situated at 3 different levels: innovation systems and policies, innovation strategies of firms and innovative products/projects (including business models).

Explanation

Features of the evaluation

* The written closed book exam assesses the extent to which the student has internalised the insights from the readings and lectures and is able to diagnose innovation dynamics, develop relevant arguments and understands consequences and implications of proposed actions.

* The paper and presentation should reflect that the student is able to analyse and understand the specific nature of their topic, to compare/situate the topic within the relevant (scientific) literature and to arrive at an assessment in terms of appropriateness. This is a group assignment.

* The paper and presentation are group assignments in teams of 4-6 people.

* For the paper the term of deliverance and deadline will be determined by the lecturer and communicated via Toledo. The deadline will be situated before the start of the examination period at the end of the semester.

* The final presentation date will be set by the lecturer and communicated via Toledo. The presentations will take place before the start of the examination period; at the end of the semester.

Determination of final grades

* The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a number on a scale of 20.

* The final grade is a weighted score and consists of the following components: 60% on a written closed book exam; 40% on the written paper and presentation

* The grade for the paper is only taken into account if the student succeeds in the final exam.

* If the student does not participate in the written exam, the final grade of the course will be NA (not taken) for the whole course.

* If the set deadline for the paper was not respected, the grade for that respective part will be a 0-grade, unless agreed otherwise by the lecturer. Changes in deadlines can only be considered in case of unexpected, severe, circumstances.

* If the student did not participate in the elaboration of the paper, the grades for the paper and presentation will be a 0-grade.

Second examination opportunity

* The features of the evaluation and determination of grades are similar to those of the first examination opportunity, as described above.

* The student retakes that part of the evaluation (written closed book exam and/or paper and  presentation) for which he did not pass. The grade obtained at the first exam opportunity for the part the student did pass, will be transferred to the second exam opportunity.

* If students did not pass for the paper and presentation (and did not pass overall), a tailor made trajectory (individual) for the paper can be considered/allowed.

Content

The course consists of two parts:

• Part 1:  Basic concepts of databases, conceptual data modeling, logical database design, relational databases (prof. Baesens)
• Part 2: Transaction management, web-based and other database architectures, data warehousing (prof. Lemahieu)

Course outline:

Part 1:
• Introduction
• Fundamental concepts regarding data management
• Architecture and classification of database management systems
• Data models for database management
• Logical database design
• Database languages in a relational environment
Part 2:
• Universal interfaces to relational database systems
• Transactions, recovery and concurrency control
• Web-database connectivity and database systems in an n-tier environment
• Data warehousing

Course material

Used Course Material
* Handbook: Lemahieu W., vanden Broucke S. and Baesens B., 2018, Principles of Database Management, Cambridge University Press
* Use of Toledo for extra course material  (slides, reader).
* Course material consists primarily of what has been taught during lectures

Toledo

* Toledo is being used for this learning activity.
 

Format: more information

The course is taught on-line, and if the situation allows, classroom exercises will be provided.

The focus of this course is on explaining the learning content. Students are expected to critically and thoroughly study the theory and examples that are presented during the lectures.

During the semester, students have to make one assignment.

Explanation

Features of the evaluation

• The final examination during the examination period involves a multiple choice exam.
• There will be a take home exam (one assignment) whose term and deliverance (individual/group, written/oral, …)  and deadline will be communicated by the lecturer (titularis) via Toledo and during the first lecture.

Determination of final grades

• The grades are determined by the lecturer(s) as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a number on a scale of 20.
• The take home assignment is graded and accounts for 20%, while the final exam accounts for the remaining 80%.
• If the student does not participate in the final examination, the final grade of the course will be NA (not taken). If the student does not participate in the take home exam the grades for this partial evaluation will be a 0-grade within the calculations of the final grade.
• If the set deadline was not respected, the grade for that respective part will be a 0-grade in the final grade, unless the student asked the lecturer to arrange a new deadline. This request needs to be motivated by grave circumstances.

Second examination opportunity

• The features of the evaluation and determination of grades are similar to those of the first examination opportunity, as described above.
• At the second examination opportunity, the take home exam can be handed in again (in case the student made corrections to the original). The grade will be determined and calculated as in the first examination opportunity.

Information about retaking exams

* See ‘Explanation’ for further information regarding the second examination opportunity.

Content

The contents of the course closely match the domain Business Analysis, as indicated in the Business Analysis Body of Knowledge (BABOK ® 2.0). That covers these "knowledge areas": Business analysis planning and monitoring, Requirements elicitation, Requirements management and communication, Enterprise analysis, Requirements analysis, Solution assessment and validation.

Contents:

• Business Analysis: Information strategy, information management, decision management, process management
• BABOK knowledge areas and techniques
• Requirements Engineering and Business modeling
• Business rules management, Business decision management, Decision modeling
• Declarative process modeling
• Project management

Course material

• Slides,exercices and extra papers are made available via Toledo.
• Toledo is being used for this learning activity.

Format: more information

There are no separate seminars: exercises are worked on during the lectures. In addition to the lectures, students must perform assignments independently.

Content

Business Process Management

• Process modeling
• Process verification & validation
• Process automation
• Quantitative process analysis – Process simulation
• Process redesign
• Process mining

Course material

• Course material
* Dumas, M., La Rosa, M., Mendling, J., Reijers, H. (2018) Fundamentals of Business Process Management, Second Edition, Springer
* van der Aalst, W. (2016) Process Mining – Data Science in Action, Second Edition, Springer

• Toledo
Toledo is used in this course Toledo

Format: more information

There are no separate seminars: exercises are worked on during the lectures. In addition to the lectures, students must perform assignments independently.

Explanation

Evaluation caracteristics

• The evaluation consists of a written multiple choice exam and one assignment.
• A correction for guessing is applied to the multiple choice exam.
• Deadlines are communicated via Toledo.    

Determination final result

• The exam is assessed by the titular, as announced on Toledo and the exam regulations.
• The final result is calculated and expressed with a whole number on 20.
• The assignment is assessed on 6 out of 20 marks, the exam on the remaining 14 out of 20 marks.
• The score of the assignment cannot be used to compensate for a severe deficiency on the exam. If the score of the exam does not surpass 5.6/14 (without rounding), the assignment will not count and the score on the exam will be rescaled to a score out of 20.

Information about retaking exams

• The student has got the chance to take the exam twice per academic year: a first time in the first or second examination period, depending on the semester in which the course is programmed, and a second time in the third examination period.
• The evaluation properties of the second examination opportunity are equal to those of the first examination opportunity.
• The score for the assignment is automatically transferred to the second examination opportunity. Only in exceptional circumstances (e.g. long-term illness), the student can request to hand in a new assignment.
• The attributed score in the second examination opportunity is weighed in the same way as in the first examination opportunity.

Content

The topics of this course are:

Part I: IT Service management

* Introduction: IT in a business environment
* A framework for IT management
* IT managment standards and frameworks
* Services delivery management
* Financial managemement
* Operations management
* Services quality management
* Security management
* Supplier management
* Human resources management

Part II: IT governance

* Introduction: what is IT governance?
* The ISO 38500 standard
* The COBIT framework
* IT decision making
* IT spending
* Business-IT alignment

Course material

Mandatory course material: course book: The IT Management Essentials - Delivering business value, ISBN: 9789057187513

Toledo: in depth explanations and comments of parts of the course book, literature, slides.

Language of instruction: more information

De deelnemersgroep is sterk internationaal samengesteld

Format: more information

The course consists of:

1. Lectures where the topics are presented, elaborated and discussed.
2. Exercises where the topics are applied to specific situations. Exercises are prepared by the students and discussed during class.
3. Self-study, in particular the reading of research papers.

Explanation

The exam is oriented towards understanding and applying IT governance and management research, standards, frameworks, principles, processes and techniques.
The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a whole number on a scale of 20.
The features of the evaluation and determination of grades are identical to those of the first examination opportunity, as described above.

Content

Part 1: Data Science Foundations

• Chapter 1: Introduction to Data Science
• Chapter 2: Preprocessing
• Chapter 3: Predictive Analytics - Decision Trees
• Chapter 4: Postprocessing
• Chapter 5: Predictive Analytics - Nearest Neighbors and Ensembles
• Chapter 6: Predictive Analytics - Regression
• Chapter 7: Predictive Analytics - Artificial Neural Networks
• Chapter 8: Descriptive Analytics - Clustering, Association and Sequence analysis, Anomaly Detection
• Chapter 9: Prescriptive Analytics - Uplift Modeling and Causal Machine Learning
• Chapter 10: Prescriptive Analytics - Cost-sensitive Learning, Evaluation and Decision-making
• Chapter 11: Prescriptive Analytics - Multi-armed Bandits and Reinforcement Learning

Part 2: Data Science Applications

• Chapter 1: Credit Risk Modeling
• Chapter 2 Fraud Analytics
• Chapter 3: Customer Lifetime Value
• Chapter 4: Recommender Systems
• Chapter 5: Web Analytics
• Chapter 6: Other applications (HR Analytics, Sentiment analysis, Supply Chain Analytics, Ethics and AI)

Course material

Course material

• Course material will be made available on Toledo: slides, reader, etc.
• Course material consists primarily of what has been taught during lectures

Recommended Reading

• Foster Provost and Tom Fawcett, Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking, 1st edition, O'Reilly Media, ISBN-13: 978-1449361327
• In addition, articles and papers will be provided on Toledo.

Toledo

• Toledo is being used for this learning activity.

Language of instruction: more information

English

Format: more information

The focus of this course is on explaining the learning content. Students are expected to critically and thoroughly study the theory and examples that are presented during the lectures.
Assignments take place during the academic year. Cases, demonstrations, guest lectures are also included.

Explanation

Features of the evaluation

* Assignments take place during the academic year and count for 20% of the final mark. Assignments may have to be carried out in teams of multiple students. The deadline for submitting the assignments will be communicated via Toledo by the lecturer.
* The final exam takes place on-campus, consists of multiple choice questions covering both parts (Part I: Data Science Foundations and Part II: Data Science Applications) of the course equally, and counts for 80% of the final mark.

Determination of final grades

* The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a number on a scale of 20.
* There is a correction for guessing on multiple choice questions, unless indicated otherwise.
* The final grade is a weighted score consisting of one or more assignments (20%) and the final examination (80%). The assignments take place during the academic year.

Second examination opportunity

* The retake exam may consist of open questions or multiple-choice questions, or a combination of both.
* Marks for assignments are counted again in the third exam period. Students can retake assignments upon request by e-mail to the lecturer by July 10 latest.

Content

The goal of this course is to equip students with the knowledge and skills necessary to successfully manage businesses in a global environment. The course provides an overview of key challenges specific to companies and ventures operating in international context and introduces theoretical frameworks and practical tools for decision-making in a global setting. During the course, we will discuss three broad aspects of international management: (1) factors of the international business environment affecting the operation of multinational companies and the set-up of international business ventures; (2) methods of evaluating international business opportunities; and (3) crucial elements of managerial decision-making in an international context. After the course, students should be more prepared to better cope with challenges of working in multinational organizations or to explore entrepreneurial activities outside their national market.

Some of the topics discussed are:

• Opportunities and challenges in international management and entrepreneurship
• The role of social and cultural differences
• Economic, political, and legal aspects of operating in an international environment
• The role of technology
• Building and managing teams in a global context
• Identifying and evaluating international business opportunities
• Managing across borders

Course material

• A set of selected academic and business articles, book chapters
• Slides
• Examples and selected case material
• Toledo / e-platform

Format: more information

Lectures

Students are expected to study and evaluate selected cases, articles, book chapters, or supplementary study materials. Students are expected to participate actively in class by bringing questions and issues for discussion and by offering creative solutions to analysed business problems.

Explanation

Features of the evaluation

* The exam is a written, closed-book exam. The exam covers lectures, articles, and cases indicated at each session as well as guest lectures. The exam may consist of conceptual questions (allowing students to show their understanding of the theory, tools, and concepts) and/or questions of case-study type (to address situations of international management and entrepreneurship in a company context).

Determination of final grades 

* The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a number on a scale of 20.

* The final grade is based upon the written exam. However, students can earn extra points during the course via active class participation and individual or group work (more precise criteria for the allocation of extra points will be communicated via the e-platform).

Second examination opportunity

* The features of the evaluation and determination of grades are similar to those of the first examination opportunity, as described above. The extra points earned for class participation, or other work during the academic year, carry over to the third exam period. 

Information about retaking exams

Second examination opportunity

* The features of the evaluation and determination of grades are similar to those of the first examination opportunity, as described above. The extra points earned for class participation, or other work during the academic year, carry over to the third exam period. 

Content

The master's thesis aims to have students conduct and report (both written and oral) a scientific research project. The student works independently (individually or in group) but under the supervision of a supervisor.

The following general rules apply with regard to the subject of the master's thesis:

• The topic is consistent with the field of study of the programme and the chosen subdomain (major/specialization), if applicable.
• The research assignment should be in line with the research or areas of specialisation of the supervisor (who supervises the approach and completion of the work).
• In developing their research, students have the opportunity to collaborate with the field (but this is not guaranteed for every topic or with every supervisor).

Course material

Toledo is being used for this learning activity

Compulsory study material

The compulsory study material depends on the chosen topic for the master's thesis and can be discussed with the supervisor.

Additional recommended study material

The optional study material depends on the topic chosen for the master's thesis and is to be discussed with the supervisor. Students should make use of relevant scientific articles and literature that they search for themselves via e.g. electronic databases (e.g. LIMO or Google Scholar).

Format: more information

The master's thesis consists of two components:

• Writing a scientific article
• Oral defense of the master’s thesis

With this ECTS file there are supplementary master’s thesis regulations. Students are required to take note of these Regulations and appendices: everything is available online on the FEB master's thesis portal. If there are interim additions, announcements and/or updates during the academic year itself, these will be communicated to students via Toledo.

Points of Attention:

• Possible promoters, topics and information on how to choose them will be made available at the start of the academic year or in the 2^nd semester (depending on the programme). If necessary, students may submit their own topics.
• Students who re-register for the ‘Master's thesis’ never automatically transfer their choice of subject and supervisor at that time. In principle, with the written agreement of the supervisor, the started master's thesis will be continued. These students make this known no later than the start of the academic year. The procedure for making this known will be communicated at the start of the academic year.
• Students moving abroad as part of their master's thesis must give at least 2 weeks' written notice. See FEB master's thesis portal for the procedure. If the planned itinerary and dates change afterwards or during the trip, this must be communicated again.
• Students can work on the master's thesis in groups or individually. More information can be found on the FEB master’s thesis portal.

Explanation

Evaluation Features

In order to successfully complete the course unit Master’s Thesis the student must fulfil the conditions listed below in a timely manner (see deadlines and procedures on the FEB master’s thesis portal):

• be fully in order with the choice and (re)start of the master’s thesis with a supervisor, incl. any project administration
• register for the oral defense (or apply for an early graduation);
• submit the master’s thesis and related documents via KU Loket (in case of group cooperation, specific guidelines apply);
• be available on campus on the scheduled defense dates. The student will receive a call no later than 1 week before the defense date with details about the specific defense time.

Only for weighty reasons (proven force majeure) can the Ombuds Service grant exceptions to the above conditions and corresponding deadlines. 

Determination of final result

The evaluation of the master's thesis is based on various aspects (see Master's thesis regulations on the FEB master's thesis portal):

• Each master's thesis is assessed before the oral defence by an assessment committee using the table of assessment criteria (see FEB master's thesis portal).
• The student defends the master's thesis orally before an assessment committee and is assessed on this defence.
• The final score on the master's thesis is calculated as follows: paper (70%), defence/presentation paper (20%), attitude during the master's thesis process (10%)
• The student must be at least successful on the paper to pass the master's thesis.
• If the student is not successful on the paper, the grade of the paper is the final score for the master's thesis.
• To receive a final score, all evaluation activities must be taken. When the master's thesis is not submitted or submitted late or when the student is not present at the defence, the final score is ‘NA’ (=not taken).
• For sanctions regarding the non-submission or late submission of other compulsory documents, please refer to the FEB Master's thesis portal.

Information about retaking exams

The evaluation at the 2nd examination opportunity takes place in the same way as at the 1st examination opportunity. For master's theses involving group collaboration, the supervision team determines the reworking of the master's thesis.

Content

This component is designed to immerse students in the theory of entrepreneurship and new venture creation and address the trepidations of students who may consider becoming entrepreneurs at some point in their career.

Topics Covered in this Course:

• Entrepreneurship intro, idea generation;
• Feasibility study, business plan guidelines;
• Industry analysis, market analysis;
• Industry segmentation, target market selection;
• Marketing plan, business positioning;
• Team development;
• Operations, product development plan;
• Getting funding, financial statements.

Course material

Used Course Material:

• Barringer, B.R. & Ireland, R.D. (2012). Entrepreneurship: Successfully launching new ventures (4th edition). Harlow: Pearson Education Limited;
• Barringer, B.R. (2008). Preparing effective business plans: An entrepreneurial approach. Upper Saddle River (NJ): Prentice Hall;
• Jones-Evans, D. & Carter, S. (2012). Enterprise and small business: Principles, practice and policy (3rd edition). Harlow: Pearson Education Limited.

Recommended Reading:

• Debrulle, J., & Maes, J. (2014). The act of creating new value: Positioning the independent and corporate entrepreneurship domain. London: McGraw-Hill, available at: https://create.mheducation.com/shop/#/catalog/details/?isbn=9781308118390.

Toledo:

• Toledo is being used to share all necessary readings and lecture slides.

Language of instruction: more information

This course is taught in English. 

Format: more information

Students interactively acquire in-depth and advanced insights into the entrepreneurial process in a course that combines traditional lectures (Models and Ingredients) with a demanding field project (Development of a Business Plan).

Is also included in other courses

D0S18A : Technology Entrepreneurship and New Business Development

Content

For this component, students participate in a group-based business plan writing exercise, accompanied by presentations on their group's progress.

Topics Covered in this Course:

• Idea generation and feasibility study;
• Industry analysis, market analysis;
• Industry segmentation, target market selection;
• Marketing plan, business positioning;
• Team development;
• Operations, product development plan;
• Getting funding, financial statements.

Course material

Used Course Material:

• Barringer, B.R. & Ireland, R.D. (2012). Entrepreneurship: Successfully launching new ventures (4th edition). Harlow: Pearson Education Limited;
• Barringer, B.R. (2008). Preparing effective business plans: An entrepreneurial approach. Upper Saddle River (NJ): Prentice Hall;
• Jones-Evans, D. & Carter, S. (2012). Enterprise and small business: Principles, practice and policy (3rd edition). Harlow: Pearson Education Limited.

Toledo:

• Toledo is being used to share all necessary readings, lecture slides, presentation guidelines, submit work, etc.

Language of instruction: more information

This course is taught in English. All presentations are delivered in English. 

Format: more information

Presentation - Project work

This course provides you with a profound understanding of the role, analytics, and process of business plan writing. Following the lectures ("Models and Ingredients"), students will engage in a group-based business-planning project and accompanying presentations. You will learn how to rigorously prepare for starting up a new business. As part of a small (approximately 6 students) and diverse team, you will develop an operational business plan aimed at either the creation of a new venture (NVC-track) or the development of new business for an established small to medium-sized firm (NBD-track). You will engage in all steps of the entrepreneurial decision-making process (e.g., idea generation, feasibility analysis, industry study, market analysis, marketing plan, production plan, product development, and financial statements). Participants are expected to accumulate entrepreneurial knowledge and behaviors that support creative solutions and new value development.

The business plan is the most demanding course component. It is in the business plan that you can show what you have learned from the course. It requires extensive field research, creativity, and critical thinking.

Explanation

Features of the Evaluation:

• A written exam assesses the extent to which the student has internalized the key insights from the course material that were studied to prepare for the lectures and that will be applied in the business plan. Questions will be in the format of single-answer, multiple-choice, with correction for guessing. Further details about the grading of the multiple-choice questions will be explained during the lectures and can be found on the Toledo page;
• The course involves the full development of an operational business plan as well as multiple intermediate presentations throughout the year;
• The business plan and presentations should reflect that you can adequately apply the different entrepreneurial concepts presented in class;
• Upon completion of the business plan, students have to indicate the extent to which their team members (peers) have contributed to the final result of the manuscript and its presentations (= peer assessment);
• For the business plan exercise, the terms of delivery and deadlines will be determined by the lecturer (titularis) and communicated via the Toledo page;
• The date of the (final) business plan presentation(s) will be determined by the lecturer (titularis) and communicated via the Toledo page. The presentations will take place before the examination period.

Determination of the Final Grades:

• The grades are determined by the lecturer (titularis) as communicated via the Toledo page and stated in the examination schedule. The final grade is calculated and communicated as an integer on a scale of 20;
• The final grade is a weighted score and consists of the following components:
  • 30% on a written closed-book exam in the form of multiple-choice questions, organized in the January examination period (with correction for guessing);
  • 50% on the final business plan;
  • 20% on the business plan presentations.
• Peer evaluation may trigger a correction up to 20% of the grade of the business plan;
• If the set deadlines for the business plan exercise were not respected, the final grade will be “NA” (not taken) for the whole course;
• If the student does not participate in the development of the business plan, the final grade will be “NA” (not taken) for the whole course;
• If the student does not participate in the exam, the final grade will be “NA” (not taken) for the whole course;
• Student attendance and participation in the business plan presentations are required for successful completion of the whole course.

Second Examination Opportunity:

• At the second exam opportunity, the final grade is based on:
  • 30% on a written closed-book exam in the form of multiple-choice questions (with correction for guessing);
  • 50% on an individual assignment (for students who failed the business plan component);
  • 20% on the business plan presentations.
• Students who passed the exam do not have to retake the exam. The grade obtained at the first exam opportunity will therefore be transferred to the second exam opportunity;
• Students who have passed the business plan cannot retake that component. For them, the results already obtained at the first exam opportunity will be transferred to the second exam opportunity;
• Students who failed the business plan, cannot retake the business plan exercise but are required to complete an individual, written assignment;
• Due to the nature of the business plan presentations, this part of the evaluation cannot be retaken. The grade obtained at the first exam opportunity for this part will therefore be transferred to the second exam opportunity.

Information about retaking exams

See ‘Explanation’ for further information regarding the second examination opportunity.

Content

In this course you learn how to develop defensive and offensive intellectual property (IP) strategies that support your business model(s) and competitive strategy. You develop an understanding of the different types of IP (patents, copyright, trademarks, trade secrets), and learn how to formulate closed and open IP strategies. Further, you learn how to build IP portfolios and how to extract value from (unused) IP. Finally, patent landscaping techniques are introduced and you learn how to formulate IP strategies for weak IPR environments.

Course material

Used Course Material
* A reader available through Ekonomika.

Toledo
* Toledo is being used for this learning activity to share readings, lecture slides, etc.

Format: more information

Students interactively acquire insights of strategic IP Management. Throughout the course the case study method is used complemented by plenary discussions. Students should come to class having individually read the cases mentioned under ‘Class preparation’ for each session. Students can use the preparatory questions to guide their individual reading of the case. No case reports are required.

Explanation

Features of the evaluation

The evaluation consists of a final exam and class participation.
* The written exam is a closed book exam and consists of open questions.
* The class participation consists of case and plenary discussions.

Determination of final grades

* The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a whole number on a scale of 20.
* The final grade is a weighted score and consists of : the written exam which is graded and counts for 100%. The evaluation of class participation will lead to an adjustment varying from 0 to +2 points of the final grade.

Second examination opportunity

* The features of the evaluation and determination of grades are similar to those of the first examination opportunity, as described above.
* Due to the nature of the class participation (i.e. the case and plenary discussions), the grade attained at the first examination opportunity will be transferred to the second examination opportunity.

Information about retaking exams

See explanation for further examination regarding the second examination opportunity.

Content

Traditional lectures (hoorcolleges) by means of class recordings.

The traditional lectures consist of 10 modules

The goal of these modules is to transfer knowledge about digital marketing concepts, theories and trends.

Per module, I have 2 to 6 recordings, all together totaling 17 hours.

Module 1: Introduction to digital marketing

Module 2: Digital Mindset, Disruption and Change

Module 3: Back to the Future: Updated CRM for traditional + digital marketing integrated

Module 4: Role of Customers: Customer Experience in the Digital Age

Module 5: Role of Customers: Customer Engagement in the Digital Age

Module 6: The Role of Technology

Module 7: The Role of Employees for Digital Marketing

Module 8: Digital Marketing Analytics

Module 9: Understanding People Reactions towards Technology

Module 10: Value

In addition to these modules, students will need to obtain certificates from a supplementary online course. More information will be provided during the first session and via Toledo.

Practice session (oefensessies) by means of interactive lectures and flipped classroom

The goal of the practice sessions involves a deeper procession of the information acquired in the traditional lectures by means of guided exercises, quizzes and Q&A.

6 sessions (of 2.5 hours each), totaling 15 hours, will be organized, in which we will deep-dive in some of the concepts of the traditional lectures. During these interactive sessions, students (individually or in group) will be assigned to guided exercises. Some of these in-class assignments are voluntary, whereas others are mandatory (such that participation in class on campus will be required for these latter sessions).

In addition, during these sessions there will be room for Q&A (questions from students) and quizzes too (questions from the teacher) with regard to the 10 aforementioned modules.

At the beginning of the course, the lecture will share the timeline of the course, including the dates when in-class participation is required.

Group assignments (groepstaak): there will be 3 types of group assignments:

Assignment 1: Analyze the digital transformation of a company or organization of your choice; and advice recommendations based on the concepts covered in this course. The end product will be a paper and a presentation.

Assignment 2: A digital marketing analytics exercise (website analytics / social media analytics)

Assignment 3: Some of the in-class assignments during the Practice Sessions will be graded too.

For these assignments, feedback sessions per group will be organized, in which there will be room for Q&A. Specifically, 20min (Assignment 1) + 10min (Assignment 2) will be organized, per group = 30min per group.

The students can enroll in a group and will work with the same group on all group assignments.

Course material

Slides

Scientific Papers

Extra-academic material (press releases, cases)

Online course organized by an external organization

Toledo is being used for this learning activity.

Language of instruction: more information

Because of the international focus of the course, it makes more sense to teach it in English. It is also more efficient.

Format: more information

Lectures, practical sessions and guest speaker(s): i

• in which the basics of digital marketing analytics will be lectured and practiced 
• in which the state of the art of digital marketing will discussed, both on the basis of academic sources and other materials.

Explanation

Evaluation characteristics

The evaluation exists of three parts: (1) certificates to be obtained via an online course, (2) group assignments, (3) an a final written exam

• Part 1: Each student is required to obtain certificates from an online course (more information will be provided during the first lecture and via Toledo).
• Part 2: For the group assignment, students will evaluate a digital marketing strategy of an organization; will conduct a digital marketing analysis; and will engage in in-class activities that will be graded too
• Part 3:  The exam is closed book and will exist of open questions about the course material.

More details about the assignments will be communicated via Toledo in the beginning of the academic year.

Determination final result

Students have to obtain the certificates of the online course (Part 1) before the date of the exam. No grades will be assigned to this part of the evaluation, students will be evaluated on a pass/fail basis. If students deliver proof of having obtained the certificates before the indicated deadline, they will receive a pass for this component. If students did not obtain the certificates before the assigned deadline, the student will receive a NA for this component, which results in a NA for the entire course.

The final grade will be based on the assignments and the final exam (part 2 and 3). Specifically, fifty percent of the grade is determined by the written exam and the rest is determined by the assignments. The result is calculated and communicated as a whole number on a scale of 20.

Students have to pass 10/20 or more on the written exam to pass the course unit. For students who pass less, the mark on the written examination counts as the final mark for the course unit.

If the student does not participate in one of the partial assessments, the student receives NA (Not taken) for the entire course.

Information about retaking exams

Second exam opportunity

Identical to the first exam opportunity. When the students passes for one part of the course (written exam or one of the assignments), the grade of that part will be transferred to the second exam opportunity grade. When the student has to redo the group assignment, an alternative individual assignment will be provided.

Content

Part 1 – Overview

• Problem vs Output vs Outcome vs Impact
• Product Development Process

Part 2 – Product Strategy

• What is- and why do you need- product strategy
• Product Roadmapping
• Prioritisation techniques

Part 3 – Discovery

• “User” and “Buyer” focus: type, profile and persona
• Opportunity Framing
• Hypotheses mapping and prioritisation
• Types of experiments, experiment design and hypothesis validation

Part 4 – Development

• Requirements in the form of User Stories (Why? What? How?)

Part 5 – Modelling

• Introduction to MDE & Domain Modelling
• Static modelling with UML Class Diagram & EDG
• Object Interaction
• Object Behaviour Modelling with State Charts
• Constraints and Attributes

Course material

Slides + online course on edge.edx.org

Explanation

Evaluation caracteristics

Features of the evaluation

The evaluation consists of a written exam, a group work consisting of a product + presentation and a process assessment.
* The written exam consists of open and closed questions that assess both theoretical knowledge and the ability to solve exercises.
* The  product and presentation are a group assignment requesting the students to demonstrate mastering the concepts in the domain of requirements engineering and the product development process.
* The process assessment consists of the assessment of meeting deadlines and levels of participation during the semester.
* Deadlines are communicated via Toledo.

Determination final result

Determination of final grades
The exam is assessed by the titular(s), as announced on Toledo and the exam regulations. The exam result is calculated and expressed with a whole number on 20.

* The Process Evaluation is assessed on 1 out of 20 marks, The Project and presentation are assessed on 5 out of 20 marks, the final exam on 14 out of 20 marks.
* Not participating to the group assignment results in a 0 for that part of the examination
* The score of the group assignment (product + presentation) cannot be used to compensate for a severe deficiency on the final exam. If the score of the final exam does not surpass 5.6/14 (without rounding), the scores of the product + presentation are reduced to 0.
* Deadline: the handing-in period and deadline are fixed by the lecturer and announced via Toledo
* If the appointed handing-in period is not respected, the assessment of the group assignment will be 0/5, except if, because of a weighty reason, after demand, a new deadline is appointed.

Information about retaking exams

Second examination opportunity

The student has got the chance to take the exam twice per academic year: a first time in the first or second examination period, depending on the semester in which the course is programmed, and a second time in the third examination period.
* The evaluation properties of the third examination period are equal to those of the first or second examination period.

* Due to the nature of the group work and of the process evaluation, the grades attained at the first examination opportunity for these parts will be transferred to the second examination opportunity (i.e. these parts cannot be retaken).
* The attributed score in the third examination period is weighed in the same way as in the first examination period.

Content

Chapter 1: Introduction: what is simulation

Chapter 2: Fundamental concepts and building blocks in simulation

Chapter 3: Simulation software: Arena

Chapter 4: Constructing simple models: modeling basic operations and inputs

Chapter 5: Modeling detailed operations

Chapter 6: Statistical output analysis, process analysis & optimization

Chapter 7: Constructing more complex models, steady-state statistical analysis of non-terminating simulations

Chapter 8: Modeling transfer of entities: transporters and conveyors

Chapter 9: Generating random variates & variance reduction techniques

Course material

Books:

• D. Kelton, R. Sadowski & N. Swets, Simulation with Arena, 5th edition, McGraw Hill, International edition, 2010, 636 p., ISBN 978-007-126771-7 (Required)
• A.M. Law & D. Kelton, Simulation Modelling and Analysis, 3rd Revised edition, McGraw Hill Higher Education, 2000, ISBN-13 ‏ : ‎ 978-0071165372 (Recommended)

Software

• Rockwell Automation Technologies, Arena Version 12.00.00: Windows compatible software including extended Online Help function which can be downloaded from http://highered.mcgraw-hill.com/sites/0073376280/student_view0/arena_software_download.html

Toledo

• Course material will be made available on Toledo: slides, reader, etc.

Format: more information

Explanation

Features of the evaluation

* Assignments can take place during the academic year. Assignments may have to be carried out in teams of multiple students. The deadline for submitting the assignments will be communicated via Toledo by the lecturer.
* The final exam takes place on-campus and may consist of multiple choice questions and/or open questions.

Determination of final grades

* The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a number on a scale of 20.
* There is a correction for guessing on multiple choice questions, unless indicated otherwise.
* The final grade is a weighted score consisting of one or more assignments (maximum 40%), and the final examination (minimum 60%), as announced on Toledo. The assignments take place during the academic year. Peer review may apply for the assignments.

Second examination opportunity

* The features of the evaluation and/or the determination of grades may differ between the first and the second examination opportunity.
* Marks for assignments are counted again in the third exam period. Students can retake assignments upon request by e-mail to the lecturer by July 10 latest.

Content

The course provides economic analysis for understanding the behavior of firms in a rapidly changing global knowledge-based competitive environment. The focus of the course is on key economic concepts, models and evidence that are essential for understanding global corporate strategies, with a special focus on global innovation strategies. 

A first set of lectures will characterize the changing global environment of firms,  covering recent trends in globalisation:
• Recent trends in globalisation:  changing Trade and FDI patterns,  global value chains, 
• Recent trends in globalisation:  internationalisation of innovation
• Europe innovating and competing in a global environment

A second set of lectures will provide the key economic concepts and models to understand how global integration affects corporate structure & strategy, increases the importance of technology for global market leadership and how firms develop global innovative strategies:
• Impact of global integration on corporate and market structure
• Importance of technology for global market leadership
• Why and how to globalise innovation activities. 
• How to capture value from global innovations 

Special topics include 
• Global open innovation strategies:  International R&D cooperation

A third part of the course involves to empirically assess firms’ global innovation strategies in key sectors:  the GLS exercise (Global Strategies of Leading Firms). Students analyze a key sector and provide a detailed description and comparative analysis of the global strategies applied by the top leading firms in that sector.  The global strategies include their geographic spread of sales, production and R&D activities.  

Guest lectures will complement the scheduled lectures.

Course material

Used Course Material
Slides
Background material
Examples

Toledo
Toledo is being used for this learning activitity

Format: more information

Lectures, guest lectures, paper

The first part of the course involves lectures, the slides and background material are provided in advance to the students. The lectures allow for raising questions and discussion. The second part of the course involves students’ work on internationalization strategies of key leading firms in selected sectors (GLS exercise). Instructions are presented in class, students have to submit interim results and get feedback on interim results. Students present the final results of their analysis in class. These presentations are discussed in class. Finally, students submit the final report of their analysis.
Guest lectures complement the scheduled lectures.

Explanation

Features of the evaluation

Grading will be based on the GLS exercise (presentation and report), as well as on a individual case assignment. 

* The paper and presentation should reflect that you understand the industry and that you tried to apply the insights taught in class to your industry analysis.
* After completing the industry analysis, students have to indicate the extent to which other students (peers) have contributed to the final result of the paper and presentation (= peer assessment).
* For the paper the term of deliverance and deadline will be determined by the lecturer and communicated via Toledo. The deadline is at the end of the semester and before the examination period.
* Students need to submit preliminary work on the paper during the year. These deadlines are spread across the semester.
* The final presentation date will be determined by the lecturer and communicated via Toledo. The presentations will take place before the examination period.

Content

This course explores the overlapping areas of industrial economics and strategic management. It is designed to provide students with an understanding of the economic principles underlying strategy formulation. Based on an analysis of the factors shaping the industry environment, firms assess their positioning relative to their rivals, and formulate strategies in order to achieve a durable competitive advantage. In choosing between strategies, firms have to take into account the possible reactions of rivals to their strategic decisions. The course provides students with the tools to analyse the positioning and performance of firms in different industry environments. These tools mainly rely on economic theories (theories of industrial organization, basic concepts of game theory, transaction cost theory, and the resource based theory of the firm). The course covers various topics in strategy formulation, such as product positioning and differentiation, diversification, vertical integration, pricing, strategic commitments, entry deterrence, and entry into new markets.

Course material

Required reading:

• Besanko, David, David Dranove, Mark Shanley, and Scott Schaefer, 2017, Economics of Strategy, 7th Edition, New York: John Wiley & Sons (ISBN: 978111978761). 
• Case Reader available for purchase at the Case Centre
• Additional course material (such as theory and summary slides) is distributed via Toledo.

Toledo:

Toledo is being used for this learning activitity.

Format: more information

The teaching philosophy for this course is partly based on problem based learning methods. Students are encouraged to read through the theory and consult online mini-lectures in advance, independently or in teams. In preparation for class, students are asked to attempt to find answers to theory and case questions using the textbook and case material. The questions point to the most important concepts in theory, and application of these concepts to the cases aims to foster a better understanding of the importance of economic analysis for strategic decision making. A number of student teams will be asked to prepare a short presentation of their answers and to present their views in class. Since students may come up with diverging answers to these questions, this invites discussion and encourages a more critical attitude towards the usefulness and applicability of theory. Teaching methods based on problem based learning principles have been shown to provide students with a better applicable and durable knowledge base. Implementing this method in this course is facilitated by a comprehensive and accessible textbook and is complemented by a number of online lectures and slides, available on Toledo, in which the more complex parts of theory are explained. Teams of students furthermore conduct a strategy project in which they critically analyse the strategy followed by a chosen firm in a particular industry, using the theoretical tools provided in the course, and culminating in a strategy recommendation. The teams deliver a report on their analysis in the last week of the semester.

Explanation

Features of the evaluation

The evaluation consists of:

• In-class participation (hand-ins and presentations, team work)
• A project paper (team work)
• A written, closed-book exam

The written exam is taken in two parts. Half of the exam will be scheduled in the middle of the semester during a scheduled class and the other half is scheduled in the exam period in June.

Deadlines and terms of deliverance will be determined by the lecturer and communicated via Toledo.

Determination of final grades

The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a whole number on a scale of 20.

The final course grade is a weighted score and consists of:

• ­The in-class participation, counting for 20% of the final grade
• ­The project paper, counting for 20% of the final grade
• ­The written exam, integrating the scores on the two parts, counting  for 60% of the final grade.

If there is a deficit score (<10/20) for the written exam, this exam grade becomes the final grade for the course. Hence, a minimum grade of 10 for the exam is required to pass the course.

Based on peer assessment (team self evaluation), a correction can be made to the grade for the in-class participation and project paper. The correction will correspond to the score a student receives by fellow students in the team for his/her contribution to the team work. The details of the peer evaluation will be communicated via Toledo.

If the student does not participate in the exam scheduled during the exam period, the final grade of the course will be NA (not taken). If the student does not participate at the in-class participation, project paper, or the partial exam during the semester, the grades for this/these partial evaluation(s) will be 0 in the determination of the final course grade.

If one of the set deadlines is not respected, the grade for that respective part will be 0 in the determination of the final course grade, unless the student  is granted a new deadline by the lecturer. Requests for a new deadline need to be well motivated.

Information about retaking exams

Second examination opportunity

The features of the evaluation and determination of grades are similar to those of the first examination opportunity, as described above.

Due to the nature of the in-class participation and the project paper, the grades obtained for these parts at the first exam opportunity will be transferred to the second examination opportunity. In the second exam opportunity, the full written exam (consisting of both parts) has to be retaken.

Content

Starting from a historical overview of the main directions of thought in managerial sciences, the management process of the company is discussed in detail. Apart from strategic and organizational aspects, the decision-making – and planning processes and implementation, motivation, managing and control (financial control included) are also discussed. This is all systematically discussed using a textbook and supplemented with cases, exercises and background material. During class examples and cases are frequently discussed. Furthermore a reading assignment will be given related to strategy and strategy implementation (Grant, Barney, Porter,…).

Course material

Required reading:

• Textbook: Robbins & Coulter, Management, Pearson.
• Additional course material is distributed via Toledo.

Toledo:

Toledo is being used for this learning activitity.

Format: more information

Management: Lectures, discussions and cases with examples.
 

Content

A deepening reading assignment with regard to strategy determination and strategy implementation (Grant, Barney, Porter,…). In addition we will go deeper into the topic control (including financial control) from a strategic perspective (a.o. Grant).

Course material

Used course material:

Reader: articles/literature

Extra course material (articles, exercises and background material, ...) is made available via Toledo

Toledo:

Toledo is used for this course.

Explanation

Features of the evaluation

*The evaluation consist of an closed-book, written exam with open questions.

Determination of the final grade

*The final grade is determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a whole number on a scale of 20.

Second Examination Opportunity

*The features of the evaluation and determination of the final grade are similar to those of the first examination opportunity, as described above.
 

Content

The lectures aim to let students acquire a profound insight in different models and approaches that aim to assess the future development and diffusion of technology and the translation into market/entrepreneurial opportunities. Both quantitative (forecasting) and qualitative approaches (scenario development) will be introduced and assessed. Specific attention will be paid to the role and modelling of contingencies (e.g. development paths of complementary technologies) and the inclusion of uncertainty/unpredictability.

The course also requires students to participate in a series of workshops and testimonials that highlight and discuss a number of technology trends that might unfold in markets/entrepreneurial opportunities in the foreseeable future. These seminars are given by (entrepreneurial) scientists and industry experts. Students are expected to attend and actively participate in these seminars.

Course material

Used Course Material

• Articles and literature
• Syllabus
• Lecture handouts

All material is made available through Toledo.

Format: more information

• Lectures introduce theoretical concepts in the assessment of technologies, and allow for hands-on practice of techniques like technology modelling, growth modelling, scenario planning, ecosystem mapping, etc.
• Testimonial sessions by experts introduce recent technology trends and require the application of the concepts taught in the accompanying lecture.
• The group assignment (2nd semester) requires to apply the lecture concepts to a chosen technology (and demonstrate this through a report and in a final Q&A session), supported by coaching sessions.

Explanation

FEATURES OF THE EVALUATION

• The closed book exam at the end of the 1st semester (in the January exam period) assesses the extent to which the student has internalized the insights from the readings and lectures and is able to diagnose the relevancy of different forward-looking approaches (for technological developments); their consequences/limitations and  the implications for enacting entrepreneurial opportunities. The exam contains both open questions (essay questions) and multiple-choice questions (with penalty correction for guessing).
• The report and the related Q&A session assess the abilities of the students to apply different models and approaches to arrive at an informed ‘prediction’ on the translation of technological opportunities into entrepreneurial opportunities. During the Q&A session each group is invited separately and has to answer questions about their reports. The report and Q&A session are a group assignment, done in teams of +/- 4 students.
  • For the report the requirements and deadline will be determined by the lecturer and communicated via Toledo. The deadline will be situated before the start of the examination period at the end of the second semester.
  • The timing for the final Q&A session will communicated via Toledo and will take place before the start of the examination period at the end of the second semester, typically at the beginning of May.
• Participation in the lectures is assessed (this may also include the obligation to hand in written summary reports).

DETERMINATION OF FINAL GRADES

• The grades are determined by the lecturer as communicated via Toledo and stated in the examination schedule. The result is calculated and communicated as a number on a scale of 20.
• The final grade is a weighted score and consists of the following components: 50% on a written closed book exam, 40% on the report and Q&A-session, and 10% on participation in the lectures.
• If the student does not participate in the written exam, the final grade of the course will be NA (not taken) for the whole course.
• If the deadline for the report was not respected, the grade for that respective part will be a 0-grade, unless agreed otherwise by the lecturer. Changes in deadlines can only be considered in case of unexpected, severe, circumstances.
• If the student did not participate in the elaboration of the report, the grade will be NA (not taken) for the whole course..

Information about retaking exams

SECOND EXAMINATION OPPORTUNITY

The features of the evaluation and determination of grades differ between the first and the second examination opportunity.

The student retakes that part of the evaluation (written closed book exam or report) for which (s)he did not pass. The grade obtained at the first exam opportunity for the part the student did pass, will be transferred to the second exam opportunity.

If students did not pass for the group assignment (and did not pass overall), an individual trajectory for each student in the group will be determined.

Content

R Studio: 

• Introduction and preliminaries
• Data Structures
• Importing and exporting data
• Writing your own function
• Graphics with R
• Basic functions in dplyr package
• More on programming with R
• Some data analysis with R
• GGplot2

SAS programming

Part 1: SAS Programming 1: Essentials

• Essentials
• Accessing Data
• Exploring and validating data
• Preparing data
• Analyzing and reporting on data
• Exporting results
• Using SQL in SAS

Part 2: SAS Programming 2: Data Manipulation Techniques

• Controlling DATA step processing
• Summarizing Data
• Manipulating Data with functions
• Creating custom formats
• Combining tables
• Processing repetitive code
• Restructuring tables

Course material

Online teaching with Q&A sessions, via Toledo and Collaborate

• R Lectures are recorded in advance and are available on Toledo. R notes are available on Toledo
• SAS has to be studied by using the SAS e-learnings provided by SAS 
• Discussion board on Toledo is available. 
• Regularly a Q&A session is organized  

Is also included in other courses

G0A21B : Statistical Software

Explanation

The evaluation consists of two pc exams on the campus.

1. SAS exam counts for 50 % of the final grade. The sas exam is a closed book, pc exam outside of the normal exam period.

2. R exam counts for 50 % of the final grade. This R exam is an open book pc exam in the normal exam period.

The details and consequences for students who do not participate in both exams can be found on Toledo.

Information about retaking exams

The features of the evaluation and determination of grades are similar to those of the first examination opportunity, as described above.

Content

The total survey error paradigm is the basic principle of this course. The different components of the survey process which are relevant for the total survey error and the quality of the survey estimates are discussed. In addition, participants are introducted to the principles of survey experiments. 
 
Topics

• Basic concepts of the survey process and survey data quality, such as observational and non-observational error, among others
• Non response Error
• The respondent related error
• Interviewer related bias and variance
• Questionnaire design and question wording
• Introduction to survey experiments

Format: more information

Lectures
Study of theoretical papers

This course module is taught in block teaching, more specifically, in the second half of the first semester. 

Explanation

Features of evaluation
The evaluation is based on a paper assignment. 

Determination of final result
The paper is evaluated by the teacher, and the result is expressed as a whole number on a scale of 20.

Second examination opportunity
The features of second exam are the same as the first exam.

Content

Introduction to visualisation (what, value, issues)
- Perception and principles: pre-attentive processing, encoding methods, Gestalt principles, colour
- Representation of data and relations
- Presentation issues and techniques to deal with space and time limitations
- Interaction techniques
- Case studies
- Visual analytics
- Volume visualisation
- Information dashboards
 

Course material

Robert Spence. 2007. Information Visualization: Design for Interaction (2nd Edition). Prentice-Hall, Inc., Upper Saddle River, NJ, USA.

Content

Exercise sessions on computers on the topics of the course Data Visualisation.

Course material

Handouts.

Explanation

100% permanent evaluation

Content

The course is complemented with a project that also serves to evaluate students. The assignment for the project is supplied in 2 or 3 successive steps. The project may be worked out individually or in teams of 2 students. The project assignment will involve the development of standalone classes, a hierarchy of classes and possibly a graph abstraction.

Content

The course discusses the object oriented paradigm to develop software systems. It uses Java as a programming language and UML (Unified Modeling Language) as a design notation. In documenting classes, some dialect of first-order logic is used to specify certain aspects in a formal way. 

1. Classes
The first part of the course discusses the definition of a standalone class. The full life cycle including the specification or documentation, the implementation and the verification of a class is covered. Another important topic are the paradigms of defensive programming and of contractual programming as alternative strategies to deal with exceptional cases. Important concepts in the study are preconditions, postcondtions, class invariants, exceptions, and black-box testing. Attention is also paid to representation encapsulation and the dangers of exposing representation objects.


2. Inheritance
The second part of the course focuses on the development of hierarchies of classes. This part studies abstract superclasses as a mechanism for generalizing over a set of concrete classes. It complements that study with polymorphism and dynamic binding, and shows how these concepts contribute to the adaptability and re-usability of software systems. The part also includes an in-depth study of behavioral subtyping, and an introduction to implementation inheritance, interfaces, and the Java Collections Framework.


3. Entity-relationship abstractions
Very often, computer programs need to process data in the form of a graph: a set of entities with relationships and attributes. In an object-oriented program, such a graph is typically represented by means of a group of objects linked using bidirectional associations. The final part of the course studies single-class and multi-class entity-relationship abstractions, as well as encapsulating multi-class abstractions by means of packages.

Course material

• Handbook: new course text by professor Jacobs (in use since 2019-2020)
• Toledo: Solutions of exercises, links to software and additional literature, project assignment, ...

Format: more information

Each lecture covers a chapter from the course book. Students are asked to read the chapter in advance. The lecture consists in interactively solving an exercise that covers all the important aspects of the chapter at stake. At the same time, important concepts are briefly explained. At the end of the session, a possible solution is published on Toledo.
 

Explanation

Students must develop a project, either on their own or in cooperation with another student. The assignment for that project is supplied in two or three successive steps during the semester. Students will receive the next part of the assignment after the deadline for submitting their solution for the previous part.

The result for the project is determined as the weighted average of the results for the three parts, with weights that will be announced via Toledo.

Furthermore, there will be a closed-book written exam (on a PC) during the exam period. During this exam, the student's knowledge of, insight in, and ability to apply the concepts and principles of the course will be examined by means of various types of questions, potentially including (but not limited to):

• fill-in-the-blanks terminology questions
• programming tasks where the student must develop a piece of Java code with accompanying formal documentation and a test suite in Eclipse with the FSC4J plugin on a PC in a PC room

The result for the course (before rounding) is the average of the result for the project and the result for the written exam, except if the student's result for the project is below 8/20 or their result for the written exam is below 10/20, or both; in the latter case, the result for the course (before rounding) is the minimum of the result for the project and the result for the written exam. This means that the result for the course (before rounding) can be >= 10/20 only if the result for the project is >= 8/20 and the result for the written exam is >= 10/20. (Note: rounding is applied to the result for the course only; no rounding is applied to partial results.)

Information about retaking exams

Students who did not pass the course in June can retake the project, the written exam, or both.

For students who retake the project, a new assignment is released after the June exams, with a deadline before the September exam period. The result for the retake project completely replaces the earlier result for the project, even if it is worse.

The result for the retake written exam completely replaces the earlier result for the written exam, unless it is worse.

The result for the course is computed from the result for the project and the result for the written exam exactly like in June.

Note: students must enroll for the retake exams, even if they wish to retake only the project.

Content

The motivation for the course lies in the urgent need for computer programs that assist people in digesting masses of unstructured information composed of text and other media. We need information retrieval technology when, for instance, we find information on the World Wide Web, in repositories of news and blogs, in biomedical document bases, or in governmental and company archives. Moreover, emails, tweets, other messages and advertisements are searched and filtered. Various techniques of content recognition, recommendation and linking play an increasing role and allow generating content models of the documents or messages, that effectively match the personalized information needs of users. We witness a current interest in capturing dynamic changes in the data and in modeling dynamic interactions with users. The proliferation of wireless and mobile devices such as mobile phones has additionally created a demand for effective and robust techniques to index, retrieve and summarize information.

 
The lectures treat the following topics:
 

1. Introduction
 

 2. Advanced representations

 Law of Zipf

Matrix factorization, latent semantic analysis (LSA), training with singular value decomposition

Probabilistic latent semantic analysis (pLSA), latent Dirichlet allocation (LDA), training with Expectation Maximization (EM) algorithms, Markov chain Monte Carlo (MCMC) methods such as Gibbs sampling, and with variational inference

Embeddings obtained with neural networks

3. Retrieval and search models

Algebraic models: vector space models

Probabilistic models: language retrieval models and Bayesian networks

Neural network models

4. Learning to rank

Relevance feedback, personalized and contextualized information needs, user profiling

Pointwise, pairwise and listwise approaches

Structured output support vector machines, loss functions, most violated constraints

End-to-end neural network models

Optimization of retrieval effectiveness and of diversity of search results

5. Dynamic retrieval and recommendation

Static versus dynamic models

Markov decision processes

Multi-armed bandit models

Modelling sessions

Online advertising

6. Multimedia information retrieval

Multimedia data types and features

Concept detection

Cross-modal indexing of content: latent Dirichlet allocation and deep learning methods

Cross-modal and multimodal retrieval and recommendation models

Illustrations with spoken document, image, video and music search

7. Web search

Web search engines, crawler-indexer architecture, query processing

Link analysis retrieval models: PageRank, HITS, personalized PageRank and variants

Behavior and credibility based retrieval models

Social search, mining and searching user generated content

8. Scalability of Web search 

Data structures and search techniques

Inverted files, nextword indices, taxonomy indices, distributed indices

Compression

Learning of hashing functions, cross-modal hashing

Scalability and efficiency challenges

Architectural optimizations

9. Clustering

Distance and similarity functions in Euclidean and hyperbolic spaces, proximity functions

Sequential and hierarchical cluster algorithms, algorithms based on cost-function optimization, number of clusters

Term clustering for query expansion, document clustering, multiview clustering

10. Categorization

Feature selection, naive Bayes model, support vector machines, (approximate) k-nearest neighbor models

Deep learning methods

Multilabel and hierarchical categorization

Convolutional neural network (CNN) based hierarchical categorization

11. Summarization

Document segmentation, maximum marginal relevance

Summarization based on latent Dirichlet allocation models and long short-term memory (LSTM) networks

Abstractive summarization with attention models

Multidocument summarization, search results fusion and visualization 

12. Question answering and conversational agents in search and recommendation

Retrieval based question answering

Deep learning methods including attention models

Cross-modal question answering

E-commerce search and recommendation

13. Evaluation measures and methodology

Recall, precision, F-measure, mean average precision, discounted cumulative gain, mean reciprocal answer rank, accuracy, confusion matrix, ROC curve, normalized mutual information, mean absolute error, root mean square error, pyramid method, inter-annotator agreement, test collections

14. Discussion of interesting research projects

15. Invited lecture by representative of an important company

In 2006-2007: Thomas Hofmann, Director of Engineering, Google Zurich European Engineering Centre, Switzerland; in 2007-2008: Ronny Lempel, director of Yahoo! research, Israel; in 2008-2009: Stephen Robertson, senior researcher at Microsoft Research Cambridge, UK and one of the founders of probabilistic modeling in information retrieval; in 2009-2010: Gregory Grefenstette, Chief Science Officer, Exalead, France; in 2010-2011: Mounia Lalmas, visiting senior researcher at Yahoo! Labs Barcelona, Spain; in 2011-2012: Jakub Zavrel, CEO and founder of TextKernel, The Netherlands; in 2012-2013: Massimiliano Ciaramita, senior research scientist at Google, Zürich, Switzerland; in 2013-2014: Alex Graves, senior research scientist at Google DeepMind, London, UK; in 2014-2015: Fabrizio Silvestri, Senior Scientist at Yahoo Labs, Barcelona; in 2015-2016: Roi Blanco, Senior Scientist at Yahoo Labs, London; in 2016-2017: Holger Schwenk, research scientist at Facebook AI Research, France and Dani Yogatama, research scientist at Google DeepMind, London, UK; in 2017-2018: Enrique Alfonseca, research tech leader at Google AI, Zurich; in 2020-2021: Florian Strub, senior researcher at Google Deepmind, and in 2021-2022: Rylan Conway, applied scientist at Amazon Seattle.

Course material

Course material is available on the Toledo-platform of the K.U.Leuven. The following books offer background to the course material:
Baeza-Yates, R. & Ribeiro-Neto, B. (2011). Modern Information Retrieval: The Concepts and Technology behind Search (2nd edition). Harlow, UK: Pearson.
Büttcher, S., Clarke, C.L.A. & Cormack, G.V. (2010). Information Retrieval: Implementing and Evaluating Search Engines. Cambridge, MA: MIT Press. 
Manning, C.D., Raghaven, P. & Schütze, H. (2009). Introduction to Information Retrieval. Cambridge University Press.
Moens, M.-F. (2006). Information Extraction: Algorithms and Prospects in a Retrieval Context (International Series on Information Retrieval 21). Berlin: Springer.

 

Format: more information

Interactive lectures.

Is also included in other courses

H02C8B : Information Retrieval and Search Engines

Content

• Exercise session on latent semantic models, probabilistic and vector models
• Exercise session on learning to rank
• Exercise session on dynamic retrieval
• Exercise session on compression
• Exercise session on categorization and clustering
• Exercise session on link based and multimodal models

Course material

Exercises and answers are available via the Toledo platform. 

Format: more information

Interactive exercise sessions in small groups.

Is also included in other courses

H02C8B : Information Retrieval and Search Engines

Explanation

Theory exam (grading: 50 %): Written, open book.

Exercise exam (grading: 50 %): Written, open book.

Content

Introduction

• What is project management?
• Situation within the general planning problem
• Characteristics of projects
• Project manager
• Components, concepts and terminology
• Life cycle of a project: strategical and tactical considerations
• Factors responsible for the success of a projectOrganisational structures and task allocation
• Organisational structures
• Staff management
• Concurrent engineering
• Assessment and selection
• Division of a project
• Outsourcing or internal work?
• Conflict evaluation:  within the organisation, environmental effects, othersProject planning
• Introduction
• Duration of project activities
• Learning effects
• Precedence relations
• Gantt-representation
• Arrow network for critical path mathematics
• Block network for critical path mathematics
• LP formulation
• Aggregation of activities
• Dealing with uncertainty
• Analysis of PERT and CPM presuppositions
• Conflicts in planningProject budget
• Introduction
• Project budget and company goals
• Drawing up a budget
• Budget management
• FinancingManagement of resources
• Influence of resource limitations on the project
• Classification of resources
• Planning of resources and project with time as a limiting factor
• Planning of resources and project with resources as a limiting factor
• Priority rules for the allocation of resources
• Subcontracting/assessing suppliers
• Executing projects in parallelProject control
• Introduction
• Control systems
• Following up and controling timewise planning and costs
• Reporting
• Updating cost and planning parameters
• Technological controlComputer support for project management
• Introduction
• Use of computers
• Criteria for software selection
• Software implementation
• Data management and knowledge managementProject termination
• Introduction
• When to finalise a project?
• Final steps in the termination of a projectCase studies

Course material

Handbook, presentations (on Toledo).

Format: more information

Lecture.

Explanation

Assignment per two students with presentation and defense (oral exam) during exam session. Exam timing is coordinated per team of students.

Content

The lectures are structured in following modules spread over 13 lectures:

Introduction (3 lectures)

• What are the various normative mechanisms in society? Cf. Lessig
• What is the nature of ethics and law?
  - Brief introduction to ethics and law
• What are the similarities and the differences between ethics and law?
• Where does ethics enter law?
• In what ways can ethics provide answers where relevant applicable law is not (yet) available
• How do law and ethics, law and technology, ethics and technology interact?
  - Brief introduction to the technological determinism vs constructionism debate
  - Normative consequences of the mutual interactions between technological developments and fundamental ethical and legal concepts and outlooks (e.g. autonomy, personhood, etc.)
• What are the latest developments in Europe (and around the world) in terms of guidelines and standards on ethical (or trustworthy) AI?

Requirements of trustworthy AI: Ethical and legal perspectives, critical discussion and implementation (3 lectures)

• Autonomy and personhood: Human agency and oversight, responsibility, accountability, and liability
• Safety and security: Societal and environmental wellbeing, Technical robustness and safety
• Justice: Diversity, non-discrimination, equality and fairness
• Enforcement and regulatory oversight mechanisms (technical and non-technical methods); whistleblowing regulation.
   

Dual Use: ethical backdrop, policies and implementation (1 lecture)

Case studies (5 lectures) – for instance:

• media & fake news
• automated driving
• banking and insurance
• judiciary
• health/enhancement
   

Comparison EU with non-EU perspectives on ethical / trustworthy AI (1 lecture)

Course material

Electronic reader on Toledo (consisting of legal and policy documents, research articles, etc.)

Explanation

The duration of the written exam is 2 hours. De duur van het schriftelijk examen is twee uur.

Content

1.            Variables, expressions and statements

2.            Conditional statements

3.            Loops

4.            Strings

5.            Functions

6.            Lists and tuples

7.            More about functions and modules

8.            Sets and dictionaries

9.            Text files

10.         Object Oriented Programming

Course material

Video’s with theoretical background via Toledo
Slides via Toledo
Summaries and quizzes via Toledo
Handbook: The Practice of Computing Using Python, Global Edition (Third Edition), Punch and Enbody, Pearson, ISBN-13 978-1-292-16662-9

Language of instruction: more information

The language of the course is English. 

Format: more information

Asynchronous online learning - Blended learning

Introductory lecture about the practical arrangements.

Online module on Toledo with explanations about the theory.

Is also included in other courses

I0D41A : Introduction to Programming

Content

Python exercises are done through the online learning environment Dodona. Students obtain automated feedback.

Course material

Exercises on the Dodona platform. 

Language of instruction: more information

Language is English. 

Format: more information

Students do Python excercises under supervision in the PC classroom. 

Is also included in other courses

I0D41A : Introduction to Programming

Content

Students develop a Python project either in a small group or alone.

There is no evaluation for this take-home assignment. The purpose is that students practice their Python programming skills.

Course material

The assignment will be made available on Toledo

Language of instruction: more information

The language is English. 

Format: more information

Students do a Python assignment at home.

Explanation

There is an open book programming exam on the pc, during which students solve a programming assignment in Python. Student can bring their handbook, but not their own notes or other printed material. There is no use of the internet, neither of AI assistance for coding. Student can use the installed IDE on the student PC’s in the PC classroom, to implement their code. Students are allowed to bring an alternative keyboard, KU Leuven only provides Azerty keyboards. Students are responsible for changing the language settings on the student PC to use alternative keyboards.

Information about retaking exams

Students can retake their exam, the modalities are identical to the first exam.

Content

This course is theoretical in nature. It provides an introduction to the multidisciplinary field of Human-Computer Interaction. It focuses on the interaction between ‘humans’ and ‘computers’ in a context of important ICT evolutions. It brings together insights from a variety of disciplines such as cognitive psychology, social sciences, computer sciences and design.

Table of contents:

• Introduction to the course
• Introduction to Human-Computer Interaction
• User-centred design principles and methods
• Interaction Paradigms
• First wave – classical HCI
• Second wave – modern HCI
• Third wave – contemporary HCI
• Towards a fourth wave - Reflections

Course material

Course material:

• Slides and video lectures distributed via Toledo.
• Course reader.  A printed version of the reader can be bought via the Cursusdienst of Politika, Scientica, and Ekonomika; a digital version is uploaded to the Toledo platform. The reader consists of a selection of influential HCI papers and book chapters. As some of the articles refer to recent ICT-evolutions or recent reflections upon the topics taught, a yearly update of this reader is not exceptional.

Format: more information

This course is built on the principles of ‘blended learning’.
1. Students view prerecorded video lectures that explain the learning materials. Prerecorded lectures are supported by a slide presentation, and deal with the content of the reader. The video lectures, slides and reader are all available on Toledo.

2. During the contact hours, interactive sessions take place. Where possible, we encourage students to work in small groups. These sessions can be organized physically and/or digitally, the exact modality will clearly be communicated via Toledo. Students have to prepare for these interactive sessions in order to make meaningful discussions and reflections possible. These interactive sessions provide ample opportunities to ask for feedback. The interactive sessions help students to prepare for the exam, e.g., by explaining how the topics taught should be studied, by stressing the focal points and by giving examples of exam questions.

3.  Throughout the academic year, each student gradually starts working on an assignment in which the student elaborates and critically reflects on a clear position statement about a specific HCI theme of choice. The assignment is due at the end of the lecture series and before the exam period. The exact deadline is communicated at the beginning of the lecture series. All instructions about the assignment, including its modalities, evaluation criteria and deadline, are available on Toledo. This information will also be explained and communicated during the first week of the course programme.

Although highly recommended, participation in the class activities is not obligatory. Students can follow this course without attending the interactive sessions.

This course unit is taught in block teaching (at the beginning/end of the semester).

Explanation

Written open book exam:

• The written open book exam focuses on open questions, such as application and/or reflection questions. 
• The exam takes place during the regular exam period. The exact modality will be communicated via Toledo. 
• Example exam questions are given in the lectures and during the interactive sessions.
• Language errors that do not obscure the meaning of the student’s answer will not affect the evaluation.
• The written exam is open book; students are allowed to rely on a printed and/or online, digital copy of their (annotated) reader, their personal notes, slides, and a physical, digital or online dictionary and grammar tool. Students can use their own electronic devices.  During the exam, students are not allowed to communicate to others, except for the communication with the invigilator (in Dutch: “surveillant”), the course or administrative staff in the case of questions or (technical) issues.

Assignment:

• The goal of the assignment is twofold: students will learn to apply the knowledge gained from tthe course materials as well as to critically evaluate and reflect upon the topics taught by forming a scientifically informed judgment and viewpoint.
• Students will be guided in the accomplishment of the assignment, e.g., by guidance in the planning and feedback on initial ideas.
• Instructions are communicated during the lectures and via Toledo.
• The assignment must show evidence of scientific rigour and ethical practices and reflections.

The final grade is calculated by taking a weighted sum of the course evaluation components. The assignment accounts for 50% of the final grade; the written exam accounts for 50% of the final grade.

If the student fails to deliver the assignment within the confines of submission conditions, then this results in a reduced score for that particular missing evaluation component. If the student fails to meet the deadline, then this will be evaluated as ‘NA’ (Niet Afgelegd = Not Completed).

If there are exceptional individual circumstances causing a delay or other issues with regard to the evaluation components of this course such as the deadline of the assignment, then the ombuds service must to be consulted.

If the student is not taking part in one of the evaluation moments (e.g., not attending the exam or not submitting the assignment), then this results in a NA-score (= not taken) for the entire course grade.

Be advised: plagiarism is not acceptable and will be sanctioned. Plagiarism (http://www.kuleuven.be/plagiarism/) is a form of examination fraud that consists of the action of copying the work (ideas, texts, structures, images, plans, …) of someone else without adequate acknowledgment, in an identical form or slightly changed. For the application of these regulations the copying of one’s own work without adequate acknowledgment is considered examination fraud. Plagiarism will be sanctioned with the sanctions mentioned in the University’s Regulations on Education and Examinations (http://www.kuleuven.be/education/regulations/).

Second examination opportunity

Students who did not obtain a sufficient grade and/or who did not take part in all evaluation components are able to redeem it by passing a supplementary evaluation.
Students may then redo each part (assignment and/or exam) for which (s)he did not obtain a sufficient grade. 

Students who participated in at least one evaluation component of the first exam opportunity and who obtained a score of at least 10/20 for the specific evaluation component(s), can decide to transfer the corresponding mark to the following examination period within the same academic year, provided that the student explicitly informs the lecturer about this choice at the latest two weeks after the results of the first evaluation period have been announced. In case of doubt, the highest score will be taken into account.