Advanced AI and Machine Learning Techniques and Capstone
This course explores advanced AI & ML techniques, ending with a comprehensive capstone project. You will learn about cutting-edge ML methods, ethical considerations in GenAI, and strategies for building scalable AI systems. The capstone project allows students to apply all their learned skills to solve a real-world problem.
By the end of this course, you will be able to:
1. Implement advanced ML techniques such as ensemble methods and transfer learning.
2. Analyze ethical implications and develop strategies for responsible AI.
3. Design scalable AI & ML systems for high-performance scenarios.
4. Develop and present a comprehensive AI & ML solution addressing a real-world problem.
To be successful in this course, you should have intermediate programming knowledge of Python, plus experience with AI & ML infrastructure, core AI & ML algorithms and techniques, the design and implementation of intelligent troubleshooting agents, and Microsoft Azure’s AI & ML services. Familiarity with statistics is also recommended.
Watch on Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: LLM Engineering
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
Building the Agentic Banking Workflow on AWS
Medium · AI
I built JARVIS OS: 1000+ autonomous AI agents, on-prem, <300ms voice latency — here's the full architecture
Dev.to · Turbo31150
Claude Skills: Workflow Layer, Not Feature
Dev.to AI
AiFinPay: Autonomous Payments for ruvnet/ruflo
Dev.to AI
🎓
Tutor Explanation
DeepCamp AI