Data Science NDK HF – Course of study

Training in Data Science makes you a sought-after but rarely found specialist in the field of big data. Not only insurance companies and banks, but also public authorities and SMEs depend on the collection, linking and structured evaluations of data records. In this IBAW course, you will acquire various tools and data science methods that will help you extract new and valuable knowledge for your company. This in turn enables companies to effectively achieve their business goals, gain economic advantage from data assets and develop new business models.
Price CHF 5'900.00
(including course materials, excluding external certificates and eLearning; see below)
Lessons 300 lessons of 50 minutes
(40% in-person teaching and approx. 60% independent eLearning)
Duration approx. 9 months
Degree Data Science NDK HF

Training on working with Big Data

Are you an IT professional with analytical thinking skills looking to take on new tasks and responsibility as a data scientist? Then the Data Science NDK HF programme is ideal for you. You will learn how to correctly apply the data science methods and how to optimally use the functions, tools and programming languages for big data experts. Further learning objectives include the preparation, cleansing, analysis and visualisation of data as well as the selection, connection and combination of data sources. You should be able to do all this while respecting the Swiss data protection guidelines.

What content does the postgraduate course cover?

  • Introduction (data science basics, data protection)
  • Data analysis and visualisation with Excel (data model and DAX, imports, measures, Power BI)
  • SQL (JOINs, SET, APPLY, functions, data modification, programming, error handling and transactions)
  • Foundation for data analysis (probability and statistics, sampling and confidence intervals, simulation and hypothesis testing, data cleaning and manipulation)
  • Ethical and legal issues in data analysis
  • Programming with R (data types, control structures, functional programming)
  • Introduction to Data Science with R (Explorative Data Analysis and Data Transformations with tidy verse, Visualisation with ggplot2, Statistical Modelling, Machine Learning)
  • The principles of machine learning (classification, regression, improving models, non-linear modelling, clustering)
  • Machine Learning application (time series and forecasts, spatial data analysis, text analysis, image analysis)
  • Transfer work and case study

A data scientist must be capable of thinking logically

The postgraduate course in Data Science can be taken part-time and can be completed without a specialist basic training. However, an understanding of IT and basic knowledge of databases and IT systems are important. Basic knowledge of mathematics (algebra and statistics; we recommend the Mathematics Basics Crash Course as a preliminary course), basic knowledge of Excel and English, programming experience are also required. You should also have logical and analytical thinking skills.

Do you have doubts whether this training is right for you? Attend one of our “Info events higher professional education” at the various IBAW locations in Switzerland to learn more about our postgraduate course in Data Science.

Independence is a prerequisite

This course consists of approx. 40% in-person  teaching and 60% independent learning (eLearnings, repetition, two transfer papers, one case study). The majority of the eLearning units (two eLearning units at $149, 5 at $99 and 3 at $50) are based on the Harvard University Data Science training available on*.

Afterwards, you have the option of completing the Harvard Data Science Programme with the ‘Capstone Project’ by taking only two additional eLearning units*.

The language of the face-to-face classes is German, the e-learning materials are exclusively in English.

*Subject to change without notice

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