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Python for Data Science Training
From zero Python to analyzing real datasets and building your first machine-learning models — a practical, project-driven introduction to data science.
What you’ll learn
- Write clean Python: data types, control flow, functions, and files
- Wrangle data confidently with NumPy and Pandas
- Visualize insights with Matplotlib and Seaborn
- Run exploratory data analysis with real datasets
- Build and evaluate first ML models with scikit-learn
- Finish a portfolio-ready capstone project on a real dataset
Course content
Python Foundations 3 sessions
Setup, syntax, variables, and data types90 min
Control flow, loops, and functions90 min
Data structures, files, and error handling90 min
Data Handling 3 sessions
NumPy arrays and vectorized thinking90 min
Pandas DataFrames: loading, cleaning, transforming90 min
Grouping, merging, and reshaping data90 min
Visualization 2 sessions
Matplotlib essentials90 min
Statistical plots with Seaborn90 min
Statistics & EDA 2 sessions
Descriptive statistics and distributions90 min
End-to-end exploratory data analysis90 min
Machine Learning Introduction 2 sessions
Regression and classification with scikit-learn90 min
Model evaluation and avoiding common pitfalls90 min
Capstone Project 1 session
Project presentation, feedback, and next-steps roadmap90 min
How the training works
Every session is code-along, with datasets and notebooks shared before class. Assignments between sessions build toward your capstone.
No programming background required — just a laptop and curiosity. The Teams joining link is emailed after your registration is confirmed.
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