Master end-to-end machine learning, deep neural networks, computer vision, transformers, and production MLOps deployment.
A rigorous 12-week deep dive into artificial intelligence and machine learning. Progress from statistical learning foundations and gradient descent to deep neural networks, convolutional vision models, sequence transformers, and production model serving.
12 weeks · 48 guided hours · 4 hours / week · ₹9,999
Syllabus
- Mathematical Foundations & Statistical Learning: Vector calculus, loss surfaces, gradient descent optimization, and regression models from scratch.
- Deep Learning Foundations with PyTorch: Building multi-layer perceptrons, backpropagation, activation functions, and training dynamics.
- Computer Vision & Sequence Modeling: Convolutional architectures (ResNet) and sequence models for temporal and textual datasets.
- Production MLOps & Model Serving Capstone: Packaging trained models into containerized REST APIs with automated inference monitoring.
What you will learn
- Supervised & unsupervised learning mathematics and implementation
- Deep neural network architecture design with PyTorch
- Convolutional Neural Networks (CNNs) for image classification and segmentation
- Attention mechanisms and Transformer foundations
- MLOps pipelines: model versioning, Dockerization, and FastAPI deployment
Register for AI/ML (Artificial Intelligence & Machine Learning)