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Amsterdam Business School Amsterdam Business School
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MBA in AI, Data & Analytics

Programme

During this part-time programme, you take courses in analytics, business and computer science. The curriculum is specifically designed to help you develop into a knowledgeable AI and data expert. Your thesis project and the international study trip will broaden your experience. The Amsterdam Leadership programme will support you in your personal leadership journey.

Core programme

The curriculum of the programme is divided into 2 years. Each year is divided into 6 blocks.

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Coding Lab
    —

    Get familiar with the basics of programming in Python. The concept of classes and methods will be introduced. During the course, you get to practice your skills and apply your acquired knowledge.

  • Statistics
    —

    Identify big data problems that require statistical techniques. Learn how to apply, understand, interpret and implement these techniques correctly using the programming language R.

  • Psychology of Technology
    —

    Get insight into how people behave as consumers. This course focuses specifically on the innovation environment and current developments such as social media and big data.

  • Econometrics
    —

    Learn how to translate economics and business questions into econometric models and hypotheses. Analyse discrete choice data, panel data, time series and interpret conclusions properly.

  • Driving Impact with AI
    —

    After this course, you should be able to: • drive focus on the critical big data opportunities (goal); • assess readiness on opportunity capture, metrics and models, technology, and people (situation); • develop a coherent vision and roadmap to capture (direction); • lead an AI use case scaling initiative to success.

  • Law and Ethics for AI
    —

    Learn more about the international principles and values concerning privacy and data protection. Understand the basics of international privacy laws, including the Privacy Regulation.

  • Machine Learning
    —

    Get familiar with the theoretical foundations of machine learning and learn to apply these methods in practical analytical tasks.

  • Operations and Supply Chain
    —

    Get introduced to the issues, frameworks and tools needed for managing operations and supply chains in a general business context. Learn to identify, analyse and resolve problems that arise.

  • Financial Accounting
    —

    Get an introduction to financial accounting from an international perspective. Acquire the knowledge and skills to understand the key concepts of financial accounting and to derive and interpret important metrics related to financial performance.

  • Optimisation for Business & Society
    —

    Learn to optimise deterministic and stochastic systems. Recognise (Mixed-Integer) Linear Programmes (MILPs) and learn how to use Excel and AIMMS to programme and solve MILPs.

  • Fintech
    —

    Discover topics like digital currencies and blockchains in the FinTech area. You will explore threats that blockchain technology poses to incumbent firms and their resulting attempts to co-opt the technology into existing business models

  • Language Technology
    —

    Discover technologies that allow machines to read, comprehend and generate human language.

  • Amsterdam Leadership Programme
    —

    Develop your personal and professional leadership skills through lectures, workshops and intervision sessions. You focus on exploring your own leadership styles, strengths and development areas.

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Human Resource Management & People Analytics
    —

    Learn to enhance the skills and talents of employees, while motivating them to achieve strategic goals. You will apply the theory to big data related cases from your organisation.

  • Data Science in Online Marketing
    —

    Study and analyse relevant marketing questions in today’s (online) world and learn to apply quantitative techniques to make data-driven marketing decisions.

  • Entrepreneurship Hackathon
    —

    Learn how an ecosystem stimulates innovation and entrepreneurship. Get familiar with key principles, behaviours, tools and frameworks that enable start-up initiatives to capture the opportunity of digital initiatives such as IOT.

  • Data Wrangling
    —

    Get insight into the opportunities and challenges of collecting data in a dynamic and evolving internet-based context. Learn the steps to prepare data for advanced statistical and machine learning techniques.

  • International Study Trip
    —

    Our international study trip is your chance to intensify your outlook on international business. During this 1-week trip in Europe, you take lectures at a top business school and visit local companies and networking events.

  • Big Data Infrastructures & Technology
    —

    Learn how to critically assess big data technologies for the analysis of large datasets. Learn how to employ Big Data technologies in real-world cases.

  • Digital Transformations
    —

    Discover the impact of disruptive forces on your organisation. Learn to analyse and initiate change and develop into an effective leader who can guide others through a process of digital transformation.

  • Deep Learning
    —

    Get a thorough introduction to deep learning. Learn about neural networks and deep learning basics.

  • Corporate Finance
    —

    Focus on the foundations of finance, in particular, capital budgeting and valuation. Get to know the fundamental concepts and most commonly used tools in capital budgeting and valuation.

  • MBA Thesis Project
    —

    With your thesis project, you will conduct your own research, involving the application of big data in business. It is your chance to explore a subject relevant to your own organisation.

Open the brochure

Primers: 2 online preparation courses

A good understanding of statistics and a basis in coding is essential in the MBA in AI, Data & Analytics. If you need to brush up/learn the skills, we recommend you to join our online primers in Statistics and Python. Fully enrolled students will get access to the primers.

The programme guides you to the level of  communicative quant - a professional applying the latest techniques in data analytics and making an effective connection with the business side. Özlem Guven, Financial Risk Model Development, Research & Advise, alumna

Amsterdam Leadership Programme

The Amsterdam Leadership Programme is our personal coaching programme. It helps you to develop your personal and professional leadership skills through lectures, workshops and intervision sessions. The focus is on exploring your own leadership styles, strengths, and development areas. You will:

  • receive feedback on key skills;
  • focus on the skills needed to grow professionally within an organisation;
  • learn specific skills relevant to personal goals;
  • network with an influential employee;
  • share both frustrations and successes.
Kasia Burgchardt
‘I aspire to move up the career ladder and make an impact with data’

Kasia Burgchardt: ‘This MBA stood out because of its unique combination of business, leadership, big data and analytics. I was able to maintain my full-time and demanding job in Amsterdam next to my study because the programme is part-time.’

Read Kasia’s full story

Balanced mix of theory and practice

Many of our instructors have in-depth industry experience in their fields. You get the chance to discuss theories from both management and policy perspectives, and learn to apply your knowledge to contemporary cases and developments. During your thesis project, you can investigate subjects concerning your own organisation and directly apply your findings.

Small and interactive classes

You will learn and work together with motivated fellow students. Our yearly cohort consists of around 25 students. This intimate learning environment allows you to interact with your fellow students and peers. It will offer you the opportunity to broaden your perspective and have a once-in-a-lifetime learning experience.

Sara Pfann
'The MBA has an orientation on the diverse possibilities of data analytics, combining theory with practice.'

Sara Pfann: 'Implementing a successful data-driven strategy and aspects such as GDPR, infrastructures and technology, data stewardship and machine learning are all aspects of my day-to-day work. One of the main strengths of the programme is exactly its orientation on the diverse possibilities of data analytics in a business environment, while at the same time combining theory with practice.'