The academic year is divided into 2 semesters, each with 3 periods. You complete each period with an examination. In the first semester, you follow the course Supply Chain Analytics instead of Econometrics for DSBA, which is compulsory for the Data Science specialisation. In the second semester, you will follow at least one elective that centres around an application area.
Apply mathematical optimisation and machine learning for better decision making. Model relevant societal problems into the framework of optimisation and machine learning and solve them in small teams.
Understand fundamental methods used in data science. We also help you develop the skills to apply these methods to economic and econometric data sets.
Understand the interaction between machine learning and optimisation at an advanced level. Develop the skills to deal with large datasets in order to solve complex global business issues.
Understand EU personal data protection (privacy) legislation. Put your insights into practice through in-class assignments: an assessment of a hypothetical project that deals with issues like a new app or AI-system that involves the processing of personal (sensitive) data.
Apply deep learning techniques for computer vision, information retrieval and multimedia. Use the knowledge from this and previous courses to address a relevant business or societal challenge. The challenges are provided by our governmental and corporate partners in the Amsterdam Data Science network, such as the City of Amsterdam.
Understand the exploration/exploitation trade-off via the study of multi-armed bandits and of Markov Decision Processes. Implement various reinforcement algorithms (Monte Carlo & temporal-difference) for more complex problems.
Understand and improve supply chains. The success of a supply chain depends on decisions made at all levels, from the network design to chosen routes. Get acquainted with analytical tools to optimise a supply chain regarding efficiency, quality, and responsiveness.
You can choose from a selection of electives from both the Amsterdam School of Economics and the Amsterdam Business School to tailor the programme to your interests:
The Master’s thesis is the final requirement before you can graduate. It is often combined with an internship at a company, institution, public sector agency or semi-governmental organisation. This is your chance to dive deep into a new development or idea that you are enthusiastic about. When writing your thesis, you have the chance to explore it fully while simultaneously training your ability to independently conduct relevant research. You will be awarded the title Master of Science (MSc) upon graduation.
If you are a student of the Master Data Science and Business Analytics and you have a record of academic excellence, a critical mind and an enthusiasm for applied research, then our Honours programme is a great opportunity for you.
We’ve designed this new Master's with input from leading companies. These companies increasingly rely on professionals who can apply data science in various business fields to optimise operating results.Prof. Cees Diks
Programme Director Cees Diks and student Hania explain.
Ideally, a supermarket has the perfect assortment available at every moment. Optimising shelf space allocated to each product category entails understanding customer behaviour and accurately predicting customer demands based on available data. You will be using transaction data and customer data to model and understand customer demands at the level of individual stores. This is an example of a timely research topic within current applied business analytics based on the huge amounts of customer level data currently available.