Python for Data Science
Master Python and the Anaconda ecosystem to analyze, visualize and model your data.
Overview
This course teaches you to use Python for transforming and analyzing scientific data. From installing Anaconda to manipulating datasets with Pandas and building your first machine learning models, you leave with a concrete method you can apply to your research.
Learning objectives
- ✓ Install and get started with the Anaconda environment (Jupyter, Spyder)
- ✓ Write Python scripts to automate data processing
- ✓ Manipulate and clean datasets with Pandas
- ✓ Produce clear visualizations with Matplotlib and Seaborn
- ✓ Build a first machine learning model with scikit-learn
Target audience
Master's students, PhD candidates, teachers, researchers and anyone wanting to analyze data with Python.
Prerequisites
No programming experience required. Comfort with computers is recommended.
Detailed program
- Installing Anaconda, Jupyter Notebook and Spyder
- Variables, types, control flow and functions
- Lists, dictionaries and comprehensions
- Best practices and project organization
- Series and DataFrames: create, load, explore
- Filtering, sorting, grouping (groupby)
- Cleaning: missing values, duplicates, types
- Import / export CSV, Excel, databases
- Charts with Matplotlib
- Statistical visualizations with Seaborn
- Choosing the right chart for the right message
- Exporting publication-ready figures
- Descriptive statistics and correlations
- Principles of supervised learning
- A first classification model with scikit-learn
- Evaluating model performance
- Case study on a real dataset
- From raw data to interpreting the results
- Reproducibility and documentation
- Going further: directions and resources
Teaching methods
A mix of theory and hands-on exercises on real cases. Course materials provided.
Assessment
Continuous assessment through exercises and quizzes. Certificate of completion for each participant.
Funding
Eligible for funding by your employer, training fund or research institution. Quote on request.
Accessibility
Our courses are accessible to people with disabilities. Contact us to adapt the program.
Related courses
R language for statistical analysis
Analyze your data and produce publishable results with R and the tidyverse ecosystem.
Artificial Intelligence & Machine Learning
Build AI models for classification and analysis of scientific data.