Intermediate Artificial Intelligence 40 hours

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

Become an LLM Engineer in 8 weeks: Build and deploy 8 LLM apps, mastering Generative AI, RAG, QLoRA fine-tuning, and AI Agents.

10 Chapters

40 Lessons

1075 min total

Open Access

What you'll learn

Build Your First LLM Product — Exploring Top Models
Multi-Modal Chatbot — LLMs, Gradio UI, and Function Calling
Open-Source Generative AI — Automated Solutions with Hugging Face
The LLM Showdown — Evaluating Models for Code and Business Tasks
Mastering RAG — Build Knowledge Systems with Vector Embeddings
Advanced RAG and Agentic RAG Patterns

+ 4 more chapters below

Engr. Mejba Ahmed

Course Instructor

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

Open Access / Start learning instantly

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Chapters 10

Lessons 40

Duration 40 hours

Level Intermediate

Certificate On Completion

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About This Course

This is the definitive hands-on course for aspiring AI Engineers. Over 10 intensive chapters, you will build 8 real-world LLM applications — from AI brochure generators and multi-modal customer support agents to autonomous deal-finding multi-agent systems. You will master the four pillars of modern AI engineering: LLM Engineering (working with frontier and open-source models), RAG (Retrieval-Augmented Generation with vector databases), QLoRA (efficient fine-tuning on consumer hardware), and Agents (autonomous multi-agent architectures). Every lesson is project-driven with production-grade Python code you can immediately apply to your job or portfolio. By the end, you will have 8 deployed AI projects, deep expertise in LangChain, Hugging Face, vector databases, and fine-tuning — and the skills to command a premium salary as an AI Engineer.

Course Curriculum

10 chapters 40 lessons 1075 min

6 lessons available to preview

1 Setting Up Your AI Engineering Environment

Preview 18min

2 Frontier Models Deep Dive — GPT-4o, Claude, Gemini

Preview 22min

3 Open-Source Models — Llama 3, Mistral, and Ollama

20min

4 Project: Build an AI Brochure Generator

30min

1 Understanding Multi-Modal Models — Text, Image, Audio

Preview 20min

2 Building Interactive AI Apps with Gradio

22min

3 Function Calling — Giving LLMs the Power to Act

25min

4 Project: Build a Multi-Modal Customer Support Agent

35min

1 The Hugging Face Ecosystem — Transformers, Datasets, and Hub

22min

2 Text Generation, Summarization, and Translation Pipelines

24min

3 Code Generation with Open-Source Models

22min

4 Project: Build an Automated Meeting Minutes Generator

30min

1 LLM Evaluation Frameworks — MMLU, HumanEval, and Custom Benchmarks

22min

2 Comparing 10 Frontier Models on Real Business Tasks

25min

3 Comparing 10 Open-Source Models — Performance vs. Cost

24min

4 Project: Build an Automated LLM Evaluation Pipeline

30min

1 Vector Embeddings — How Computers Understand Meaning

Preview 22min

2 Vector Databases — Chroma, Pinecone, and FAISS

25min

3 Building Production RAG Pipelines — Chunking and Retrieval

30min

4 Project: Build an AI Knowledge Worker for Company Docs

35min

1 Advanced Chunking — Semantic, Hierarchical, and Contextual

24min

2 Hybrid Search — Combining Dense and Sparse Retrieval

26min

3 Agentic RAG — Self-Correcting Retrieval with LangGraph

28min

4 Project: Build a Multi-Source RAG System with Query Routing

35min

1 From Traditional ML to Transfer Learning — Understanding the Evolution

Preview 24min

2 LoRA and QLoRA Explained — Efficient Fine-Tuning for Everyone

28min

3 Preparing Training Data — Dataset Curation for Fine-Tuning

26min

4 Project: Fine-Tune Llama 3 on Custom Data with QLoRA

35min

1 Advanced Fine-Tuning — DPO, RLHF, and Preference Alignment

28min

2 Training Infrastructure — GPUs, Cloud, and Cost Optimization

24min

3 Evaluation and Iteration — Measuring Fine-Tuning Success

24min

4 Project: Build a Domain-Specific Model That Rivals GPT-4

35min

1 Agent Architecture — ReAct, Tool Use, and Reasoning Loops

Preview 28min

2 Building Agents with LangGraph — Stateful Multi-Step Workflows

30min

3 Multi-Agent Orchestration — CrewAI and Agent Teams

26min

4 Project: Build an Autonomous Deal-Finding Agent System

35min

1 Deploying LLM Applications — Docker, APIs, and Scaling

28min

2 Monitoring, Cost Optimization, and Guardrails

26min

3 Capstone Project: Full-Stack AI Application

40min

4 Career Guide — Building Your AI Engineering Portfolio

22min

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

What you'll learn

About This Course

Course Curriculum

Build Your First LLM Product — Exploring Top Models

Multi-Modal Chatbot — LLMs, Gradio UI, and Function Calling

Open-Source Generative AI — Automated Solutions with Hugging Face

The LLM Showdown — Evaluating Models for Code and Business Tasks

Mastering RAG — Build Knowledge Systems with Vector Embeddings

Advanced RAG and Agentic RAG Patterns

From Traditional ML to Fine-Tuning with QLoRA

Production Fine-Tuning — Compete with Frontier Models

Build Autonomous Multi-Agent Systems

Production Deployment, Capstone, and Career Mastery

Enjoying the free courses?

Get AI School Daily on LinkedIn

Ratings & Reviews

No reviews yet

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Continue Learning

Building AI Agents with Claude: From Prompts to Production

How to Build Million-Dollar SaaS Applications Using Claude Code (Opus 4.6 & Sonnet 4.6)

AI Automation with Python: Build 10 Production-Ready Intelligent Systems

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Engr Mejba Ahmed

Hey there!

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

What you'll learn

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About This Course

Course Curriculum

Build Your First LLM Product — Exploring Top Models

Multi-Modal Chatbot — LLMs, Gradio UI, and Function Calling

Open-Source Generative AI — Automated Solutions with Hugging Face

The LLM Showdown — Evaluating Models for Code and Business Tasks

Mastering RAG — Build Knowledge Systems with Vector Embeddings

Advanced RAG and Agentic RAG Patterns

From Traditional ML to Fine-Tuning with QLoRA

Production Fine-Tuning — Compete with Frontier Models

Build Autonomous Multi-Agent Systems

Production Deployment, Capstone, and Career Mastery

Enjoying the free courses?

Get AI School Daily on LinkedIn

Ratings & Reviews

No reviews yet

Share Your Experience

Continue Learning

Building AI Agents with Claude: From Prompts to Production

How to Build Million-Dollar SaaS Applications Using Claude Code (Opus 4.6 & Sonnet 4.6)

AI Automation with Python: Build 10 Production-Ready Intelligent Systems

Engr Mejba Ahmed

Hey there!