Use Case
DNCA
Python
Team
training
12 hours
of training
Score
in progress
3
participants
Training content.
Learning objectives
Master the advanced features of Python development
Optimise developments and increase the speed of execution of scripts
Generate alerts when indicators go beyond certain limits
Monitor indicator levels
Manipulate and extract data
Transform data (filtering…)
A fully personalized :
1 | Concepts and Reminders
Discover / review Python libraries to manipulate data (Numpy, Pandas)
Do data visualization (seaborn, Matplotlib) and machine learning (scikit-learn)
Handle strings, lists and dataframes
2 | Manipulation
Build advanced visualizations in Python for data-driven decision making
3 | Workshop
Getting to grips with Jupyter notebooks to manage data projects
Use cases on Jupyter notebooks
4 | Machine Learning
Understanding the basics of Machine Learning: supervised and unsupervised learning
Going further: text mining, image analysis
Results.
Best practices in data manipulation and data visualization in Python
Make data-driven decisions via Python
Understanding the interests and challenges of Machine Learning in Python