5.00
(1 Rating)

ML Engineering for the Generative AI Era

Categories: Machine Learning
Wishlist Share
Share Course
Page Link
Share On Social Media

About Course

Purpose:
Prepare students and early-career engineers for the booming AI/ML job market by teaching real-world, production-ready generative AI skills.

Why It Matters:

  • Traditional software engineering roles are declining, while AI roles are growing 21% per year.

  • Huge talent gap: 4.2M AI jobs open vs. only 320K qualified engineers.

  • Universities can’t keep pace with rapid AI innovation, leaving students unprepared.

Who It’s For:

  • Aspiring AI/ML engineers looking for hands-on experience.

  • Students wanting mentorship from industry experts.

  • Anyone seeking to build a portfolio aligned with current AI hiring needs.

Key Outcomes:

  • Build production-grade AI/ML projects: voice agents, LLM fine-tuning, RAG systems, summarizers.

  • Gain experience with high-performance GPU infrastructure.

  • Access mentorship from FAANG ML engineers and startup founders.

  • Develop a portfolio and network that directly connect to hiring opportunities.

  • Demo Day presentations to real recruiters and hiring managers.

Show More

What Will You Learn?

  • Foundations & Data Engineering
  • Build and manage AI agents
  • Work with real-world data pipelines and engineering tasks
  • Search & Retrieval Systems
  • Implement efficient search and retrieval mechanisms
  • Integrate AI models with data sources for practical applications
  • LLM Training & Summarization
  • Train and fine-tune large language models (LLMs)
  • Build summarization systems and other generative AI applications
  • Capstone Project
  • Develop a complete Research Assistant System
  • Apply all learned skills in a real-world aligned project
  • Advanced Extensions
  • Explore multi-modal AI models
  • Refine and extend your projects beyond the core curriculum
  • Deployment & Real-world Engineering
  • Use high-performance GPU infrastructure
  • Deploy AI models for production-level tasks
  • Learn best practices for ML systems used in industry
  • Career & Networking Skills
  • Present projects to hiring managers and AI founders
  • Build a portfolio that showcases production-ready AI systems
  • Connect with mentors, alumni, and industry partners

Student Ratings & Reviews

5.0
Total 1 Rating
5
1 Rating
4
0 Rating
3
0 Rating
2
0 Rating
1
0 Rating
6 years ago
Great clarity in explanations and thoroughly enjoyed the course. I had been working out for quite a while, but a few little things we might miss out from a diet perspective are covered well in detail here.
Especially loved how you structured the entire focus area of dieting into most important ones to lesser ones.