AI & Machine Learning with Python
Python, data, and your first machine-learning models in 3 months
A 3-month program from Python fundamentals through your first real machine-learning models — designed for career switchers and curious engineers.
- Duration
- 3 months (12 weeks)
- Level
- Beginner
- Live coding every session — you build along, not just watch
- Three guest sessions with a senior engineer based in Japan
- WhatsApp group for Q&A
- Extra classes available if you need more time on a topic
A focused, beginner-friendly path into machine learning. You start with Python and the data tools every ML engineer reaches for — NumPy, Pandas, Matplotlib, Seaborn — then move into the foundations of ML and your first real models: linear regression, logistic regression, and decision trees. By the end, you'll have built and evaluated models on real data, not just read about them.
Built for
Career switchers, students, and engineers stepping into machine learning and data science.
What you'll cover
Each phase builds on the last — the goal is to ship something real by the end.
- Weeks 1–2
Python and NumPy
- Python fundamentals
- NumPy arrays and vectorized operations
- Setting up Anaconda and Jupyter
- Weeks 3–5
Pandas and data preprocessing
- DataFrames and Series
- Cleaning, transforming, and joining data
- Handling missing values and outliers
- Weeks 6–7
Data visualization
- Matplotlib basics
- Seaborn for statistical plots
- Building dashboards from real data
- Week 8
Introduction to machine learning
- Supervised vs. unsupervised learning
- The training / test split
- Evaluation metrics that actually matter
- Weeks 9–12
Your first models
- Linear regression
- Logistic regression
- Decision trees
- Model evaluation and improvement
By the end, you'll be able to
- Comfortable in Python, NumPy, and Pandas
- Able to clean, explore, and visualize a real dataset
- Built and evaluated your first ML models with scikit-learn
- Classes per week
- 2
- Class length
- 1 hour
- Total classes
- 24
Built with the same tools we use in production
Everything you'll touch in this course is what teams actually use to ship — no toy stacks, no proprietary detours.
- Python
- Anaconda
- Jupyter Notebooks
- NumPy
- Pandas
- Matplotlib
- Seaborn
- scikit-learn
- GitHub
Simple, flexible payment
Pay in full for a 5% discount, or split into two installments. Talk to us if cost is a blocker — we'll work something out.
- Admission
- Free
- Course fee
- Contact for current fee
- Installments
- 50% on admission, 50% mid-course
- Discount
- 5% off for full upfront payment
Curious whether ML is for you?
Book a free demo and write your first scikit-learn model in under an hour.