Data Analysis in Python

Description

As a programming language, Python is becoming increasingly important for Data Engineering and Data Science. But how do you get off to a good start with Python? This training lays a solid foundation in Python for both Data Engineering and Data Science. All fundamentals are covered: from working with Jupyter Notebooks and using modules (libraries) to editing and analyzing using pandas.

Audience

If you want to use Python to do Data Engineering or Data Science, the Python Fundamentals training is the perfect starting point.

Skills gained

We work over two days with many hands-on assignments, learning:

• Use Jupyter Notebook powerfully
• Load and apply modules (libraries) in Python
• Manage dependencies on external modules
• How to easily load data into Python
• Edit data using pandas
• Data analytics with pandas
• Visualize data with seaborn

After the course you can work independently with Python and Jupyter Notebooks for loading, editing and analyzing data. You can of course also take the examples and detailed assignments from the course to your organization, and offer you valuable reference work to fall back on later.

Prerequisites to follow the "Python Fundamentals" training

Basic knowledge of programming or scripting is required for this training. Experience with Python, R or another programming language ensures that you get the most out of this training.

Course outline

• Introduction Python
• Using Jupyter Notebook
• Using modules (libraries) in Python
• Loading data into Python
• Edit data with pandas
• Clean up and verify data
• Data analysis with pandas
• Aggregates and groupings
• Visualize trends
• Data visualization
• Linking files and datasets

Study material

In the training "Python Fundamentals" we use material that we have developed ourselves at Wortell Smart Learning. We make sure that you receive all the necessary material on time.