Intermediate SML-502 ⏱ 8 weeks 📚 11 topics

Fine-Tuning LLMs: LoRA, QLoRA, and PEFT in Practice Certification

Learn to fine-tune large language models efficiently using LoRA, QLoRA, and PEFT. Practical intermediate course covering the full fine-tuning workflow from dataset to deployment.

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Questions

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Pass Score

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Time Limit

What You'll Demonstrate

  • Choose between fine-tuning, RAG, and prompt engineering for any use case
  • Prepare high-quality datasets for instruction fine-tuning
  • Apply LoRA and QLoRA to fine-tune 7B+ models efficiently
  • Evaluate fine-tuned models with rigorous benchmarks
  • Deploy fine-tuned models to production inference APIs

Topics Covered by This Exam

1

Why Fine-Tune? When and When Not To

60 minutes

lesson
2

The Hugging Face Ecosystem

90 minutes

lesson
3

Dataset Preparation for Fine-Tuning

120 minutes

lesson
4

Full Fine-Tuning: The Baseline

90 minutes

lesson
5

LoRA: Low-Rank Adaptation Explained

120 minutes

lesson
6

QLoRA: Fine-Tuning on Consumer Hardware

150 minutes

lesson
7

PEFT: Comparing Adapters, Prefix Tuning, and IA³

90 minutes

lesson
8

Training Loop, Hyperparameters, and Debugging

120 minutes

lesson
9

Evaluation: BLEU, ROUGE, and LLM-as-Judge

90 minutes

lesson
10

Merging and Deploying Fine-Tuned Models

120 minutes

lesson
11

Capstone: Domain-Specific Assistant

360 minutes

project

Adaptive Exam Format

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Progressive Difficulty

Questions advance from Easy → Medium → Hard as you proceed through the exam

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Single & Multi Select

Mix of single-answer and multi-answer questions to assess depth of knowledge

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Randomised Bank

Questions are drawn randomly from a larger question bank — no two exams are the same

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Badge & Certificate

Digital badge and printable certificate issued immediately upon passing