AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents

AI Engineer Core Track: LLM Engineering, RAG, QLoRA, Agents
2026-02-04
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz

Become an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI, RAG, LoRA and AI Agents.

What you’ll learn
Project 1: Make AI-powered brochure generator that scrapes and navigates company websites intelligently.
Project 2: Build Multi-modal customer support agent for an airline with UI and function-calling.
Project 3: Develop Tool that creates meeting minutes and action items from audio using both open- and closed-source models.
Project 4: Make AI that converts Python code to optimized C++, boosting performance by 60,000x!
Project 5: Build AI knowledge-worker using RAG to become an expert on all company-related matters.
Compare and contrast the latest techniques for improving the performance of your LLM solution, such as RAG, fine-tuning and agentic workflows
Weigh up the leading 10 frontier and 10 open-source LLMs, and be able to select the best choice for a given task

Requirements
Familiarity with Python. This course will not cover Python basics and is completed in Python.
A PC with an internet connection is required. Either Mac (Linux) or Windows.
We recommend that you allocate around $5 for API costs to work with frontier models. However, you can complete the course using open-source models if you prefer.

Description
Who this course is for:
Aspiring AI engineers and data scientists eager to break into the field of Generative AI and LLMs., Professionals looking to upskill and stay competitive in the rapidly evolving AI landscape., Developers interested in building advanced AI applications with practical, hands-on experience., Individuals seeking a career transition or aiming to enhance productivity through LLM-built frameworks.

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