Python for Machine Learning & Data Science 2025
Complete ML bootcamp: NumPy, Pandas, Matplotlib, Scikit-Learn, TensorFlow, and real-world projects.
4.8(6 reviews)8 studentsBeginnerEnglish
Created by Marcus Johnson
Data Science & AI
What you'll learn
- Write Python confidently for data analysis
- Clean, transform, and visualize real datasets
- Train, evaluate, and tune ML models with Scikit-Learn
- Build neural networks with TensorFlow and Keras
- Deploy ML models as REST APIs
Requirements
- No prior Python or ML experience needed
- Basic high-school algebra helpful
- A computer with internet access
About this course
The most complete Data Science and Machine Learning course. Start with Python fundamentals, work through NumPy and Pandas for data manipulation, Matplotlib and Seaborn for visualization, then master Scikit-Learn for classical ML and TensorFlow 3 for deep learning. Includes 6 capstone projects: house price prediction, customer churn model, image classifier, NLP sentiment analysis, recommendation engine, and a live ML API deployed to GCP.
Course curriculum
5 lectures · 310 min total
- Python & Data Science Environment SetupPreview20:00
- NumPy & Pandas: Data Wrangling at Scale70:00
- Exploratory Data Analysis & Visualization50:00
- Classical ML with Scikit-Learn80:00
- Deep Learning Foundations with TensorFlow90:00
Your instructor
Marcus holds a PhD in Computer Science from MIT with a focus on deep learning. He spent 4 years at Google Brain and has published 12 peer-reviewed papers. His mission is to demystify AI for working engineers and make cutting-edge ML techniques practical.
Student reviews
4.8- SSophia Bennett
Marcus has a gift for making math intuitive. The linear algebra and statistics refresher chapters are brilliant — I finally understand WHY gradient descent works, not just how to call the function.
- NNoah Harrison
The capstone project at the end ties everything together perfectly. I built a sentiment analysis model from scratch and deployed it on Hugging Face. This course genuinely delivers on its promises.
- JJames Wright
