Python for data analytics

During this training, we learn how we can analyse data using Python. In the last few years, the fields of data analytics and data science became of great importance throughout the professional world. At the same time, we notice a spectacular growth in the popularity of Python in this field: it is on its way to become the leading language in scientific and business data analysis. Python's general strengths as a multi-purpose programming language, combined with a number of specialised libraries, make it a very valuable tool for exploring, analysing, and visualising all sorts of data.

In this course we look at the possibilities of Python in the field of data analysis and visualisation, including popular libraries such as NumPy, Pandas and Matplotlib.

Schedule

datedur.lang.locationprice 
11 Oct3Woerden 1500 EUR (exempt from VAT)
06 Dec3web based 1500 EUR (excl. VAT)
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Intended for

This training is aimed at whoever wants to start practising data analysis: developers, data scientists, data architects, marketeers, and anyone who needs to manipulate, visualize, or summarize their corporate data.

Background

Basic Python knowledge is a prerequisite for this training, as well as some notions of statistics (see courses Python fundamentals and Statistics fundamentals).

Main topics

  • Reading and writing data
  • Text files, CSV
  • Databases
  • Microsoft Excel
  • XML, HTML, JSON
  • Data Wrangling and exploratory analysis
  • Concatenating, merging and joining data
  • Transforming data
  • Pivoting
  • Handling missing data
  • Data aggregation and Grouping
  • Regular Expressions (optional)
  • Visualisation
  • The Scientific Python ecosystem (SciPy)
  • NumPy
  • Pandas
  • Matplotlib
  • IPython and Jupyter Notebooks
  • Other useful packages

Training method

Classroom training with demos and practical exercises.

Duration

3 days.

Course leader

Arnout Veugelen.

Reviews

4.4/5 (based on 51 evaluations; the most recent ones are shown below)

The course was really in-depth and explained well

 
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It was very well presented, interesting,useful and fun!

 
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good, I feel myself more comfortable with Python after this course

 
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Very satisfied (8.5/10)

 
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Really appreciated the course level, the instructor has been really clear in his explanations

 
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The course was well organised, the explanations clear and the supporting documuments were very helpful. I would recommend it

 
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Excellent. The material was very complete, user friendly and well organised. The teacher was very knowledgeable about the topic and make the training not only interactive and interesting but also entertaining

 
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Very good, good pace and structure of the course.

 
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Very good for our needs. Perhaps slightly too "Theoric" in the initial part for an "Economists" audience.

 
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I would have appreciated something more "genomics oriented" with actual analysis examples - pipeline drafts (for example RNA-seq, WGS or WEX data analysis)

 
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A lot of useful insights provided, included material for self learning & practice. I am satisfied with this course and I can recommend it again in the future. Thank you!

 
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Erg goed, veel geleerd van de fundamenten van data analyse.

 
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Good, maybe a little more exercises could be added.

 
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goede cursus, zeer tevreden

 
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Goed, maar 2 dagen was eigenlijk te kort om het vakgebied Data Analytics goed tot haar recht te laten komen.

 
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Zeer goede intro in dit onderwerp!

 
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Nice!

 
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Very good, just need a bit more exercises with the corrections (during class)

 
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Also interesting

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