Data Processing and Analysis with Python
upyttb
Organized by talent.brussels
3 days
Getting started with Python
This training has no Python prerequisites. So first the basics of Python are covered.
- Introducing the Python programming language
- Python environments
- Interactive development with Azure notebooks
- Variables and objects
- Common data structures: Lists, tuples, sets and dictionaries
- Functions
- Creating and using classes
- LAB: Coding in Python
Data processing with SciPy
In data science its crucial to deal with tables: Loading, manipulating, data quality checks, … Dataframes can help out with that, and in this module the two most important Python packages for data manipulation are inspected: Numpy and Pandas.
- Numerical Python: Numpy
- Numpy data structures
- Pandas DataFrames
- Loading data with pandas
- Data manipulations with Pandas
- LAB: Loading and manipulating datasets in Pandas
Data Inspection
Some pictures express more than a 1000 words. This holds in data science as well, so visualizing data is a crucial data science skill. Matplotlib is the most popular library for this. But there are additional libraries which build further upon this.
- Plotting with pandas
- Introducing the matplotlib package
- Using the seaborn package
- Creating interactive plots with Plotly
- LAB: Plotting data in Python
Data Engineering converts data into insights. This field has received a lot of attention lately, resulting in a lot of possible techniques to tackle this problem. In this training you will gradually dive deeper in the use of Python to apply data engineering techniques on business data.
This course focusses on developers and data engineers.Prior knowledge of Python is not needed to attend this training, but some basic coding skills are handy.
