Student marks analyser
Built end to end, reviewed by a mentor and added to your portfolio.
A friendly start for complete beginners: Python, data handling and your first machine learning model.
Module by module.
Variables, control flow, functions and files.
NumPy arrays, Pandas DataFrames and CSV/Excel data.
Matplotlib and Seaborn charts that tell a story.
Train, test and improve a simple model with scikit-learn.
Built end to end, reviewed by a mentor and added to your portfolio.
Built end to end, reviewed by a mentor and added to your portfolio.
Our flagship path: Python, machine learning, deep learning, LLMs and deployment, finished with a portfolio of real AI products.
Explore course →Go from data to deployed model: classic machine learning, then neural networks for vision and language.
Explore course →Build with LLMs: prompting, retrieval-augmented generation, fine-tuning basics and AI agents that use tools.
Explore course →Ask about the next batch, timings and fees. Our team will guide you.