About Course
A complete 24-week journey from math foundations and statistics to machine learning, deep learning, computer vision, NLP, and real-world model deployment — with 17+ hands-on projects and a final capstone.
This 24-week program takes you from zero to a fully job-ready Machine Learning & Deep Learning practitioner. You’ll start with the math and statistics that power ML — linear algebra, calculus, and probability — then move through data handling (NumPy, Pandas), visualization, and a complete machine learning curriculum covering regression, classification, clustering, and advanced algorithms like XGBoost.
In the second half, you’ll go deep into Deep Learning — building neural networks with TensorFlow & Keras, computer vision with CNNs, NLP with word embeddings and RNNs/LSTMs, and finally, real-world model deployment using Flask, FastAPI, and Streamlit.
Across the course, you’ll complete 17+ mini-projects on real datasets (House Price Prediction, Customer Churn, Sentiment Analysis, Image Classification, and more), and finish with a Final Capstone Project — choosing either a Machine Learning or Deep Learning track — deployed and presented as a portfolio centerpiece.
By the end, you’ll walk away with a GitHub portfolio, a polished resume, an optimized LinkedIn/Kaggle profile, and the confidence to sit for ML/AI interviews.
Course Content
Introduction to AI, ML & Data Science (Week 1)
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Course Introduction
20:00 -
Python Revision for ML
30:00