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Analytics Translator - hybrid programme

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In this 4-day interactive course you will learn key skills to perform as an Analytics Translator. You will play the bridging role between the technical expertise of data scientists and the operational expertise of domains such as marketing, HR, supply chain, finance. This role is crucial to ensure that the data science efforts connect flawlessly to the business needs. This unique course will prepare you for this new and valuable role in every organisation. The next edition will start on Thursday 24 March 2022.

This masterclass will be offered in compliance with government regulations and in line with the social distancing rules of a 1.5 metre society. Since the masterclass is offered as an hybrid event, participants can join the course onsite or online via a video connection from any location.

Why join the course Analytics Translator?

  • What will you learn?
    • A fundamental understanding of machine learning methods.
    • Identifying business opportunities for data science solutions.
    • Essential statistical concepts.
    • Data visualisation, dashboard design and storytelling with data.
    • Implementation of data science projects.
    • How to translate between data science team and business team/management.
    • Data science ethics and regulations, including GDPR.
    • Understand data science roles and what kind of teams are needed.
  • For whom?

    This course is designed for business professionals who want to become the crucial link between business and data science and analytics teams. The profile of the participants will be business professionals in finance, auditing, control, risk, marketing, HR, sales, logistics, supply chain, etc. Are you working in the business field and interested in the new role as Analytics Translator? Do you want to help your management or board to identify and prioritise business goals? To help them choose the opportunities that create the most value? In this course you will learn to fulfill the vital role of the translator between business and data science.

  • Dates and fees
    Dates: Spring edition: Thursday 24 & Friday 25 March, Thursday 21 & Friday 22 April and online case presentations on Thursday 19 May 2022
      Autumn edition: 2022 dates tba
     Times: 09:00 - 17:00
    Fee: €4,150* (incl. course materials and light catering)

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

  • Practical information
    Location: Amsterdam Business School and Leonardo Royal hotel, Paul van Vlissingenstraat 24, Amsterdam
    Mode of study: Hybrid and online programme
    Language: English
    Certification: You will receive a Certificate of Attendance from the University of Amsterdam
  • Teaching staff

    This course is organised by The Analytics Academy and will be taught by university lecturers and experienced consultants. The consultants have been conducting and implementing data science projects for multiple years in a wide range of businesses. They will share their best practices with you and warn you about the pitfalls of data science projects. The academic rigor with regards to research methods and statistics, vital for effective data science projects, will be taught by experienced academic lecturers from the University of Amsterdam.

  • 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.'

Contact

Do you have questions about this or our other open programmes? Please contact:

Jannice Daha LLM
Manager Executive Education
E: executive-education@uva.nl
T: +31 (0)20 525 6134

Facts & Figures
Type Contract teaching
Mode Part-time, short-term, module
Language of instruction English
Starts in March, September