Artificial Intelligence

Prompt Distillation for Cost Efficiency

Using Pro models for everything is too expensive. Distillation teaches how to use a large model to teach a smaller, cheaper one to perform the same task at a fraction of the cost.

Level: AdvancedArtificial Intelligence

What You'll Learn

Knowledge distillation concepts for LLMs
Using Gemini 1.5 Pro to generate a high-quality training dataset
Fine-tuning Gemini 1.5 Flash on synthetic data
Cost comparison: Pro vs Flash at scale
Prompt-response dataset construction and quality filtering
Evaluating distilled model performance vs teacher
Achieving 1/10th the cost with comparable accuracy

What's Included

🧭AI Tutor🔒

Interactive learning path with AI-generated lessons read aloud by your personal tutor

🧪Practice Lab🔒

Step-by-step lab instructions with AI guidance — run in your own IDE or sandbox.

🎙️Mock Interviews🔒

AI interviewer asks tailored questions, gives real-time feedback and a score report

📝Evaluation🔒

MCQ questions (theory, practical, code) to test your knowledge and earn a badge

⚔️Challenge AI🔒

Compete head-to-head against AI on real production problems — judged on correctness, performance, scalability, code quality, and edge cases

Course Syllabus

Module 1: Distillation Concepts

  • •Knowledge distillation: teacher → student model
  • •Why smaller models can match larger ones on narrow tasks
  • •Gemini 1.5 Pro vs Flash: capability and cost comparison
  • •Dataset quality vs quantity trade-offs
  • •When distillation is the right approach

Module 2: Generating the Training Dataset

  • •Designing prompt-response pairs for a specific task
  • •Using Gemini 1.5 Pro to generate high-quality examples
  • •Diversity and coverage: avoiding dataset collapse
  • •Filtering low-quality outputs with a scoring prompt
  • •Structuring the dataset in JSONL format for fine-tuning

Module 3: Fine-Tuning & Evaluation

  • •Fine-tuning Gemini 1.5 Flash via Vertex AI
  • •Training hyperparameters: epochs, batch size, learning rate
  • •Evaluating Flash vs Pro on held-out test cases
  • •Cost analysis: tokens, API calls, and fine-tuning fees
  • •Capstone: task-specific Flash model at 1/10th Pro cost

You're all set

Everything in this course is unlocked.

Continue Learning →
✓AI Tutor
✓Practice Lab
✓Mock Interviews
✓Evaluation
✓Challenge AI