Job-Ready AI & Machine Learning Bootcamp
Go from Python basics to deploying real ML models — the exact workflow we use on client projects.
What you'll learn
- Write clean, production-quality Python for data and ML work
- Wrangle real messy datasets with Pandas and NumPy
- Build, tune and evaluate every core ML algorithm from scratch and with scikit-learn
- Understand the maths behind gradient descent, regularisation and loss functions without a PhD
- Train neural networks with PyTorch and know when deep learning is the wrong tool
- Deploy models as FastAPI services with proper input validation
- Track experiments, version datasets and avoid silent data leakage
- Ship 4 portfolio projects with real business framing you can defend in interviews
What's included
Course content 8 sections · 41 lessons · 15h 17m total
Requirements
- A laptop with 8GB RAM and a stable internet connection
- No prior machine learning experience needed
- Basic school-level maths — we rebuild everything else from zero
- Willingness to actually type the code along with the lessons
Description
This is a to-the-point, project-first AI and Machine Learning bootcamp built for people who want a job, not just a certificate.
You start with Python and the data stack, move through the core ML algorithms with the maths explained in plain language, and finish by deploying models as real APIs that other software can call. Every module ends with a hands-on build, and the final third of the course is entirely portfolio projects.
No filler, no 40-minute theory monologues. If a topic will not help you ship or get hired, it is not in here.
Your instructor
Pratik Naiya
Pratik Naiya builds production AI systems, automations and data products at HackWithPro. He has shipped AI agents, RAG helpdesks and document-intelligence pipelines for real businesses, and teaches the exact workflow he uses on client projects.
Frequently asked questions
Still deciding?
Tell us what you are trying to build and we will say honestly whether this course is the right fit — or point you at something better.