Learn the practical data science workflow in Python - from cleaning data with pandas to training your first machine learning models.
What you will learn
- Manipulate and clean data with pandas
- Visualize data with matplotlib and seaborn
- Train and evaluate basic ML models
- Complete an end-to-end data science project
Requirements
- Basic Python knowledge
- A computer capable of running Jupyter notebooks
- Certificate on completion
FAQ
Basic Python knowledge is assumed - see Python Programming Fundamentals if you're new to Python.
Jupyter notebooks with pandas, matplotlib, and scikit-learn.
It covers the core practical workflow used in most junior data analyst and data science roles.
- NumPy and pandas basics
- Cleaning and transforming dataLocked
- Exploratory data analysisLocked
- Charting with matplotlib and seabornLocked
- Descriptive statistics essentialsLocked
- Identifying patterns and outliersLocked
- Regression and classification introLocked
- Training and evaluating a modelLocked
- End-to-end capstone projectLocked
Sophia Martinez
Data Scientist
Sophia Martinez builds machine learning models for healthcare and retail clients, and teaches data science with a focus on real, reproducible projects.
Reviews
5.0
1 Review
Elena Petrova
★★★★★5 days ago
The capstone project is genuinely portfolio-worthy, not a toy exercise.
