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Fine-tuning & Training

Customize AI Models

Learn to customize models for your specific needs. Master parameter-efficient fine-tuning, preference optimization, and alignment techniques.

5-6 weeks
13 Lessons
3 Projects

🎯 What You'll Learn

  • Fine-tune models with LoRA and PEFT
  • Implement preference optimization (DPO)
  • Understand RLHF pipeline
  • Master distributed training
  • Complete 4 hands-on projects

Prerequisites

  • •Completed Level 7
  • •Strong ML fundamentals
  • •GPU access recommended

Course Modules

When and Why to Fine-tuneComing soon
Full Fine-tuning vs PEFTComing soon
LoRA and QLoRA ExplainedComing soon
Adapter MethodsComing soon
Preparing Training DataComing soon
🛠️

Project: Fine-tune a Domain-Specific Model

Estimated time: 4 hours

RLHF ExplainedComing soon
Direct Preference OptimizationComing soon
Constitutional AI PrinciplesComing soon
Reward ModelingComing soon
🛠️

Project: Implement Preference Optimization

Estimated time: 4 hours

Data ParallelismComing soon
Model ParallelismComing soon
DeepSpeed & FSDPComing soon
Pipeline ParallelismComing soon
🛠️

Project: Train a Model with DeepSpeed

Estimated time: 3 hours

Skills You'll Gain

LoRAPEFTRLHFDPODistributed TrainingDeepSpeedFine-tuning