Introduction to Data Science

"Everyone talks about it, but no one does it." is a cry we often hear from people in the field when it comes to Data Science. These 'noises’ from the market inspired us to set up a training course where Data Science is covered from a broad perspective. After all, CQM's advisors have over 35 years’ experience in applying Data Science to thousands of customer projects, always starting with a specific question and ending with a workable solution.

 

Content

The following topics are covered during the Introduction to Data Science training course:

  1. Starting with a question: describe, predict, prescribe
  2. Data: little, medium, and big
  3. Methods and Models from:
    • Statistics
    • Machine Learning
    • Simulation
    • Optimization
  4. Tools such as:
    • Excel, R, Stata, MatLab, SAS, MiniTab, Aimms, Icron, Python, Spark and more
  5. How to become a great Data Scientist
  6. How to run a Data Science Department

All the Data Science buzzwords you know are of secondary importance to the final goal: finding the answer to a relevant business question. Most work practice-related questions contain elements of 'Describe', 'Predict' and also 'Prescribe'. Rarely do such practical questions fit in just one of these boxes. There is always the underlying desire to understand the world better (describe); to see what’s going to happen (predict); and to know how a good decision can be made, or how a product or process can best be developed or improved (prescribe).

 

Who’s it for?

Unlike other CQM training courses, this introductory training is available as both an open course and an in-company course. Anyone interested in Data Science 'Beyond the Hype' is welcome. Here an open course has the advantage that as a participant you get to know people from other companies facing the same questions as you. The in-company course obviously has the advantage that it can be more closely geared to the specific needs of your company.

The programme content doesn’t delve deeply into the methods discussed. But we do discuss all the various methods, models and tools in the context of their practical application.

This means the course will certainly appeal to:

  • Managers of Data Science departments;
  • Businesspeople with a serious interest in Data Science;
  • Clients of Data Science departments;
  • Data Scientists with an interest in the practical application of Data Science;
  • Advisors in the field of Data Science.

 

By the end of the course, participants will:

  • have seen and discussed many aspects of Data Science drawn from the trainers’ experience with real cases;
  • know the relevant methods, models and tools, and how they relate to one another;
  • have had the chance to discuss their own Data Science case with both 'peers' and experienced CQM advisers;
  • be able to indicate the importance of Data Science to their company;
  • have had the opportunity to network and share experiences with colleagues at other companies.

 

And after the introduction...

The technical aspects of using the methods, models and tools is outside the scope of this introductory course. They’re discussed in the context of practical examples where we also look at alternative approaches.

But CQM would of course be happy to provide tailor-made courses for your organization, in which we discuss the methods, models and tools relevant to your organization in more detail, and at a level geared to the knowledge and experience of the people attending.

 

Interested in an introductory or customised training course in Data Science?

Please contact Marnix Zoutenbier, who’ll be happy to discuss the various possibilities with you.

Drs. Marnix Zoutenbier

Drs. Marnix Zoutenbier

Principal Consultant