Postgraduate Studies: Big Data & Analytics in Business and Management
Aim of the Programme
This programme is a unique offering as its general aim is to bridge the gap between technical concepts and business applications of big data and analytics techniques.
On the one hand, the programme will provide participants with a thorough understanding of the key technical aspects of big data and analytics technologies. On the other hand, the programme focuses on business and management applications, substantiating how big data and analytics techniques can create business value and providing insights on how to manage big data and analytics projects and teams. As such, this inherent interdisciplinary focus is the unique selling point of our programme.
The programme is founded on the lecturers' experience of advising and collaborating with industry and governmental organizations in Belgium and abroad. After successful completion of the programme, participants will be up-to-date with the latest developments related to big data and analytics. Furthermore, they will understand how to apply these techniques in practice and create value for their organization. The programme is relevant for participants from different sectors: business (marketing, finance, auditing, HR, CRM, consulting), government (fraud, open data, process optimization), healthcare (care flows, data-driven diagnostics), media (sentiment analysis, opinion mining, usability analytics), education (evidence-based performance management, learning analytics), energy & transport (smart data).
→ Download the postgraduate brochure (pdf)
Our programme also offers extensive network opportunities for participants, enabled by the provisioning of full catering (coffee breaks + sandwich dinners) on every session day, plus two networking dinners on the first and final session day.
event_note Programme structure
1. Fundamentals of Data Analytics
-
Predictive analytics: supervised
learning techniques -
Descriptive analytics: unsupervised
learning techniques - The analytics process model: data collection and preprocessing, model construction and evaluation
2. Analytics Business Applications
- Marketing analytics
- Recommender systems
- Insurance analytics
- Text mining
- Web mining
- Social network analytics
- Fraud detection
- Decision mining
3. Big Data Technologies
- Hadoop and its ecosystem
- The MapReduce paradigm
- Big data analytics using Apache Spark
and H2O - NoSQL databases
- Graph databases
4. Process Analytics
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Process discovery
- Event log data
- Conformance checking
- Predictive process mining
- Sequence mining
- Case studies
5. Managing Big Data & Analytics Projects and Teams
- Model deployment
- Valorization of analytics
- Analytics and IT integration
- Data quality and security
- Data privacy and compliance
- Ethics and privacy
Optional hands-on exercises will be provided through a DataCamp classroom.
check_circle Target audience and eligibility
Participants should have obtained an academic or professional bachelor's degree. The programme aims at participants with a minimum of one year of practical experience in the area of business analysis, data analytics, data analysis, statistics, data management, project management, etc. This criterion is strict: if you don't have sufficient work experience, you will not be admitted. Applications are evaluated by the academic coordinator based on the requested information in the registration form. The goal is to build a homogeneous participant group to foster discussions and share experiences.
Example target profiles are: chief data officer, chief analytics officer, compliance and risk officers and managers, data architects, data project managers, junior industry data scientists, data-related programme managers, business analysts, product managers, IT project managers, etc. However, this list is not exhaustive!
access_time Course schedule and location
Sessions are scheduled on Fridays from 13.30 until 21.00 on the following dates:
location_on Location: Faculty of Economics and Business, Naamsestraat 69, 3000 Leuven (view on Google Maps)
If you register for this programme, the information you provide will only be used for the purposes of organising it and to contact you after completion of the programme. The organiser will not share your personal data with third parties within or outside KU Leuven without your explicit consent except to comply with external (e.g. tax) obligations. You have the right to access, correct and if necessary delete personal data held by KU Leuven through this procedure. A certificate is offered for this course. Essential personal data as well as key data relating to the course, including any grades, will therefore be stored indefinitely for certification purposes.
create Registration
Closing date for registrations
13 September 2024
Maximum number of participants
45
Registration fee
€5500
A payment request will be sent after admission approval from the academic coordinator. (Partial) payment through the KMO-portefeuille is possible. Our approval number is DV.O102270. When submitting your application, you choose the theme “Innovation” and the advice “Artificial Intelligence”.
This programme is also eligible for "Betaald Educatief Verlof" by the Flemish Government and the Brussels-Capital Region. FEB Research Chair sponsors enjoy a 20% discount for employees.
question_answer Testimonials
The Postgraduate Studies in Big Data & Analytics in Business and Management at KU Leuven is an exceptional academic journey that exceeded my expectations on every level. This program prepares individuals to navigate in the ever-changing realms of business through the lens of data analytics. The comprehensive curriculum combining theoretical knowledge with practical applications, equipped me with skills essential in today's data-driven industry landscape. Professors and lecturers not only imparted knowledge but also fostered an open environment for discussions. Their industry experiences offered insights into the practical applications of data science in various business domains. I highly recommend this program for those aiming to venture into a career in big data and analytics or seeking to expand their insights and grasp of AI/ML. —Jaroslaw Kwasniewski, Military Information Systems Expert, EUROCONTROL
The objective of the programme has fully accomplishing my expectations. For somebody like me without no real data science background or a PhD in mathematics, the courses were fast, excellent, passionately brought, quite complex and provided a good oversight of all aspects of data mining. The fact that a case had to be prepared forces you to go in depth into the matter, into the real data and applying models. Excellent approach.— Alain Goossens, Managing Partner, SII Belgium & AG-mec Dynamics
Great training to obtain an overall knowledge of what big data is about and to get started on your own!— Lies Peeters, Head of Compliance Risk and Development, BNP Paribas Fortis
This was a fantastic learning experience. Great content, highly relevant, full range overview of the big data and analytics domain, good business cases, great mentoring, comfortable setting. I acquired insights I apply every day in my work environment to position, qualify and steer the initiatives we are taking in the area. I'd recommend this postgraduate to every manager or leader who wants to know more about this key topic in order to be better prepared for future business challenges. Thanks for all!— Bert Vander Elst, Senior Director IT for Global R&D, GSK Vaccines
I highly recommend the postgraduate program in Big Data and Analytics to anyone looking to advance their career in the dynamic field of data science. This comprehensive program offers a broad spectrum of topics, equipping students with a solid foundation in data analysis and machine learning, as well as an introduction to the commonly used tools and technologies. It encourages and empowers students to delve deeper into specific areas of interest and to tackle real-world data challenges effectively and efficiently. — Mattijs D'hoedt, Process & Analytics Manager, Unilin
Whether you are looking to get a broad overview on analytics techniques, want to meet peers and discuss pitfalls of data driven initiatives, or you are looking for open discussions with experts in the field, do not look any further. This postgraduate has it all. One to recommend!— Nico Huybrechts, CEO, dataSHIFT
I am pleased to provide a strong recommendation for the postgraduate program in Big Data and Analytics, based on my firsthand experience with the curriculum and its impact on skill development and knowledge acquisition. One of the standout features of this program is its remarkable efficiency in transferring a comprehensive set of skills and knowledge within a condensed timeframe. In just 10 session days, participants gain a profound understanding of key concepts and practical applications in the field of Big Data and analytics. The program's well-structured modules ensure a focused and efficient learning experience. The curriculum is particularly noteworthy for its ability to provide a clear overview of data analytics techniques. Participants are exposed to a spectrum of methodologies, ranging from foundational concepts like linear regression to advanced techniques such as large language models. What sets this program apart is its emphasis on fostering independent learning and exploration of advanced topics. Beyond the structured sessions, participants are given the tools and resources necessary to delve into more sophisticated areas on their own. This not only instills a sense of autonomy but also prepares individuals to adapt to the ever-changing landscape of Big Data and analytics. In addition to core technical skills, the program takes a holistic approach by incorporating vital aspects such as regulation, ethics, and managerial knowledge. In conclusion, the postgraduate program in Big Data and Analytics stands out as an exemplary educational opportunity. Its efficiency, comprehensive curriculum, emphasis on independent learning, and holistic approach make it an ideal choice for individuals seeking to advance their skills in this dynamic and critical domain. — Arno Bossaert Finance Lead
school Evaluation and diploma
To obtain the postgraduate certificate "Postgraduate Studies in Big Data & Analytics in Business and Management", awarded by the KU Leuven and signed by the Rector, the participant will need to write a dissertation about a case study in the field of big data analytics, along with an oral defence of the case study.
The case study should performed in the participant's organization and deal with the (potential) application of big data and analytics techniques in practice. Participants will be actively guided by one of the lecturers. We will use three possible timelines for the dissertation, with submission deadlines available end of April 2025, end of June 2025, or end of August 2025. The dissertation will be complemented by an oral presentation to be scheduled in the week following the submission deadline.
contact_mail Contact information
Academic coordination:
Programme coordination & information requests:
- Lindsay Vandenameele ✉ (PUC KU Leuven Kulak)
+32 56 24 60 89 or schedule your information meeting here.