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Analytics Translator

Big data and AI are transforming what organisations do and how they do it. Analytics Translators play the pivotal role of recognising opportunities where data and analytics could create value, and translating them into a data-analytic assignment for an analytics team. They are the bridge between analytics and other business functions. This 6-day programme prepares you for playing this key role in your organisation. Or take the 2-day first module only for getting a good orientation into this rapidly developing field.

Analytics Translators steer the transition towards the data-driven and digital organisation, and are the bridge between business and analytics teams.

STAP Budget

You can request STAP Budget for this programme.

Why join the course Analytics Translator?

  • What will you learn?

    After finishing the programme, you:

    • will be literate in new technologies in data engineering and analytics. You will understand what these technologies are, how they transform what organisations do and how they do it, and why they have so much impact;
    • will be able to translate a business opportunity into a data analytic question, and to structure the work into a data science project following the CRISP-DM model;
    • will be able to recognise validity issues in predictive algorithms and models;
    • will have a good overview of applications of data and analytics in business, government and healthcare;
    • will be well-prepared for playing a leading role in helping your organisation transform into a data-driven business.

     

  • For whom?

    Senior business professionals and managers who grow into a pivotal role in deploying data-driven working and digitisation in their work and organisations. The programme is suitable for professionals in diverse functions. No specific prior knowledge of IT or analytics is required for this course.

  • Dates and fees
    Dates:
    • Thursday 20 and Friday 21 April 2023 (module 1)
    • Thursday 11 and Friday 12 May 2023 (module 2)
    • Thursday 8 and Friday 9 June 2023 (module 2)
     Times: 09:00 - 17:00
    Fee:
    • €2,380 (Module 1 only, 2 days)
    • €5,750 (Modules 1 and 2, 6 days)

    *UvA alumni get a 10% discount. Fees are VAT-exempt

    STAP Budget

    You can request a STAP Budget for this programme. To be eligible for the subsidy of €1,000 you need a STAP registration certificate. To get this, tick the STAP Budget box in the application form above. Take into account that there are deadlines for registration and receiving the necessary STAP registration certificate.

    More about the STAP Budget
  • Practical information
    Location: Amsterdam Business School
    Mode of study Onsite programme
    Language: English
    Certification: After completing the programme, you will be a Certified Analytics Translator
  • Teaching staff

    Academic director: prof. Jeroen de Mast, professor of data-driven business innovation at the Amsterdam Business School of the University of Amsterdam. Prof. De Mast will teach this course together with professors and experts from the University of Amsterdam and ORTEC.

  • Reviews

    'A clear and basic understanding of a difficult but essential subject, in a pleasant but informative way.'

    'I was enabled to quickly brushed up on my knowledge of statistics and was given enough insight in the relevance for data applications in my own work.'

    'The course forced me to think about my work in a different way.'

    'Data visualisation by Mr. Stephenson. A real eye-opener.'

    'It challenged me to think about my work in a different way.'

2 modules

The Analytics Translator course is divided into 2 modules. You can choose to follow the first module (2 days) or both modules (6 days). Module 1 dives deeper into understanding AI, data science and big data. While module 2 prepares you for the role of Analytics Translator.

  • Module 1 (2 days): Understanding AI, data science and big data
    • Orientation module: Aiming to give you a realistic overview of data science and emerging technologies and their potential value for your organisation. 
    • New forms of data, new analytics, new business opportunities: Big Data, machine learning, AI: what are they, what can you do with them, and why do they have so much impact? 
    • Doing data science: Managing data-science projects as CRISP-DM projects, where a business opportunity is translated into a data-mining question, where data sources are identified and pre-processed, where a model is developed and evaluated, and then deployed. 
    • How machines learn and machine learning in business: Machine learning is the quintessential technique in AI. We will explore many of the popular algorithms, such as decision trees, random forests and neural networks. Our focus is on understanding what it takes to deploy machine learning and AI in a sound, reliable and secure way to create value in a business environment. 
    • Digital safari: Explore the landscape of emerging digital technologies We review the foundational technologies that enable the digital transformation: cloud computing, Big Data, AI, cybersecurity and IoT. We also discuss far-future disruptive technologies, such as AI & robotics, energy, extended reality (AR/VR), quantum computing, 3D printing, and biotech. And finally, we learn about service & technology ecosystems and SaaS. 
  • Module 2 (4 days): Preparing for the role of Analytics Translator
    • Data and analytics use cases: We can learn a lot from other companies that have successfully integrated new technologies and analytics. We review a number of use cases from a variety of industries, including healthcare and government.
    • AI strategy and value chain, and determining the right business question: How do you connect your business strategy to AI and how do you get maximum value out of data science projects, given your high-level company goals?
    • EU Privacy and AI laws: A primer in EU legislation that needs to be considered when using data and algorithms.
    • Leading successful data science teams: Data analytics teams are multidisciplinary and cover many different skill sets. We offer structures that are helpful in getting flow in data analytics projects, and we also discuss what organisational infrastructure such projects need in order to be effective.
    • Data visualisation: You learn the design principles and the applicability of various visualisation techniques.
    • Data governance and data management: We explore the capabilities needed to ensure that high-quality data are available throughout the organisation in a secure and reliable way.
    • Capstone assignment: Participants work on a practical assignment, which they develop and discuss with fellow participants and instructors. In the assignment, participants identify a business opportunity in their own organisation where data and analytics could be of value, and translate it into a data-analytic problem. Part of the assignment is to identify the required data sources and where they could be obtained, and participants will also design a suitable organisational structure for deploying such a project in one’s own organisation.
'The lecturers clearly knew what they were talking about and were willing to adapt the material to the group’s learning needs.'

Tijmen van Diepen: 'I wanted to learn how the power of advanced analytics can be properly applied, so I can offer our clients solutions that they might not have thought of themselves, as well as deeper insights. This programme has most certainly met my expectations.'

Contact

Do you want to know more, or do you want to discuss whether this programme is right for you? Please contact:

Iris Kroese MA
Manager of Executive Education
E: executive-education@uva.nl
T: +31 6 1893 8203

Facts & Figures
Type Contract teaching
Mode Part-time, short-term, module
Language of instruction English
Starts in April
Location Roeterseiland campus