Deep Learning
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10 lessons3 levels1 capstone project
Build neural-network intuition and implementation skill across backpropagation, optimization, convolution, sequence models, attention, transformers, regularization and scaling.
BASIC
- Introduction to Deep Learning 2026 — MIT 6.S191 (Long)
Current university-level foundation for deep neural networks and training. - Introduction to Deep Learning 2025 — MIT 6.S191 (Long)
Alternative lecture emphasizing core foundations and modern architectures. - Deep Learning Lecture 1 — MIT OpenCourseWare (Long)
Graduate-level deep- learning overview and building blocks.
INTERMEDIATE
- Introduction to Convolutional Neural Networks for Visual Recognition — Stanford
Apply Deep Learning through the adjacent capability: Computer Vision. - Lecture 1: Introduction — Stanford CS231N 2025
Apply Deep Learning through the adjacent capability: Computer Vision. - Evaluation Metrics for Machine Learning Models
Apply Deep Learning through the adjacent capability: Feature Engineering & Model Evaluation.
ADVANCED
- OpenCV Course with Python — freeCodeCamp
Extend Deep Learning into senior/production practice through Computer Vision. - End-to-End NLP Project in Python
Extend Deep Learning into senior/production practice through Natural Language Processing (NLP). - Step by Step — Machine Learning Project Workflow
Extend Deep Learning into senior/production practice through Machine Learning.