AI Learning
Courses on AI β deep learning, LLMs, prompting and agents
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2:00 Doc version 1
Deep Learning Fundamentals and AI Security - From Deep Learning to Security Agents
A two-hour special lecture for students of security. Hour 1 condenses the Introduction to Deep Learning course into one hour to cover how neural networks are built and trained. Hour 2 surveys deep learning for security β malware, intrusion, logs, vulnerabilities and more β then looks at how AI agents that analyze alerts and call tools are changing security work, and how those agents themselves become a target.
2:00 Doc version 1
π Deep Learning Fundamentals and AI Security - From Deep Learning to Security Agents (Details)
Detailed materials for enrolled students of 'Deep Learning Fundamentals and AI Security'.
1:30 Doc version 2
Introduction to Deep Learning - What Is Deep Learning?
An introductory lecture for anyone new to deep learning. Starting from 'functions and algorithms', it explains why machine learning and deep learning emerged through intuitive analogies (shooting baskets, walking blindfolded), then lets you experience the full flow of training, testing and prediction in one go through MNIST digit classification.
1:30 Doc version 2
π Introduction to Deep Learning - What Is Deep Learning? (Details)
Detailed materials for enrolled students of 'Introduction to Deep Learning - What Is Deep Learning?'.
2:00 Doc version 1
Prompt Engineering & AI Agent Design
Learn the principles and core techniques of prompt engineering, along with AI agent architecture and design principles through live coding demos using open-source tools.
Deep Learning: From Basics to Production
A comprehensive course designed for everyone from beginners to those looking to apply deep learning in production. Learn from neural network fundamentals to practical projects with CNN, RNN, and Transformer.
AI Image Processing
Learn computer vision and deep learningβbased image processing from fundamentals to advanced techniques through hands-on projects with tools like OpenCV and PIL.