Courses
Structured lessons and lectures โ from fundamentals to hands-on practice.
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AI Learning
Courses on AI โ deep learning, LLMs, prompting and agents
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 โ malware, intrusion, logs, vulnerabilities and more โ 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
๐ 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
๐ 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 learningโbased image processing from fundamentals to advanced techniques through hands-on projects with tools like OpenCV and PIL.
Dev Workflow
Git/GitHub collaboration, DevOps, MLOps and open-source contribution
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Collaborative Development with Git & GitHub
Walk through Git/GitHub fundamentals, Git Flow-based collaboration, and how AI code generators combine with the workflow. The instructor demonstrates building a simple timer app end-to-end by combining Claude Code with Git Flow, visualized through Sourcetree.
DevOps in Practice: CI/CD and Infrastructure Automation
Learn the core concepts of DevOps through hands-on examples, from building CI/CD pipelines to deploying applications with Docker and Kubernetes.
3:00 Doc version 2
MLOps: Production Machine Learning Pipelines
Automate and manage the full ML lifecycleโdata, training, serving, and monitoringโwith hands-on MLOps pipelines and tooling.
Fundamentals
Courses that build programming and software fundamentals
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Part 3: GitFlow + AI Development Tool-Based Collaboration Practice
Understand Git not as a simple version control tool but as a mental model for team collaboration, and practice efficient collaboration workflows using AI tools.
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Part 2: TDD and Development Thinking in the AI Era
In an era where AI generates code, understand why relying on autocomplete without testing is dangerous, and develop habits that ensure maximum safety with minimum testing effort.
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Part 1: Python for the AI Era: Automation, Data, and Model Integration
Understand why Python is the essential language of the AI era, and build practical foundations for workflow automation, data processing, and AI library integration that you can apply immediately.