LLM Fine-Tuning, Prompt Engineering & Model Evaluation
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Module 1 – Foundations of Large Language Models
Module 1 – Overview
Preview
Transformer Architecture Overview
Preview
Pre-training vs Fine-Tuning vs Instruction Tuning
Preview
Tokenization and Embeddings
Preview
Model Families: GPT, Llama, Claude, etc.
Preview
Compute Requirements and Infrastructure
Preview
Module 1 – Knowledge Check Quizzes
Preview
7 lessons, 1 quiz
Module 2 – Prompt Engineering Mastery
Module 2 – Overview
Prompt Structures and Templates
Zero-Shot, Few-Shot, and Chain-of-Thought Prompting
System Prompts and Role Assignment
Prompt Optimization Techniques
Context Windows and Memory
Safety, Bias and Ethical Prompting (Prompt injection defense)
Hands-on Lab: Design prompts for summarization, extraction, reasoning
Module 2 – Knowledge Check Quizzes
9 lessons, 1 quiz
Module 3 – Preparing Data for Fine-Tuning
Module 3 – Overview
Data Collection and Curation Strategies
Formatting Training Data (JSONL, CSV, etc.)
Data Cleaning and Preprocessing
Handling Low-Resource Languages
Hands-on Lab: Preparing African Language Dataset
Module 3 – Knowledge Check Quizzes
7 lessons, 1 quiz
Module 4 – Supervised Fine-Tuning (SFT)
Module 4 – Overview
When to Fine-Tune vs Not Fine-Tune
Training Pipelines (LoRA, QLoRA)
Hyperparameter Configuration
Training with Open-Source Models (Llama, Mistral, Gemma)
Deployment Considerations
Hands-on Lab: Fine-tune a small LLaMA-based model using LoRA
Module 4 – Knowledge Check Quizzes
8 lessons, 1 quiz
Module 5 – Retrieval-Augmented Generation (RAG)
Module 5 – Overview
What's RAG? RAG vs Fine-Tuning
Vector Databases (FAISS, Milvus, Pinecone, Weaviate)
Chunking Strategies and Embeddings
Agentic RAG Systems: From Retrieval to Reasoning
Hands-on Lab: Build a simple RAG chatbot using open-source tools
Module 5 – Knowledge Check Quizzes
7 lessons, 1 quiz
Module 6 – Model Evaluation Techniques
Module 6 – Overview
Evaluation Metrics: BLEU, ROUGE, BERTScore, G-Eval
Human Evaluation Design and Frameworks
LLM Safety Testing (toxicity, hallucination, bias & fairness assessment)
LLM Benchmarks, Model Comparisons and Leaderboard Design
Hands-on Lab: Evaluating Model Outputs Across Metrics
Module 6 – Knowledge Check Quizzes
7 lessons, 1 quiz
Module 3 – Preparing Data for Fine-Tuning
Module 3 – Overview
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