TRACK 27•Modern AI Track•ADVANCED

Fine-Tuning & Model Adaptation

Name: Fine-Tuning & Model Adaptation
Price: 3999.00 INR
Availability: InStock

LoRA, QLoRA, instruction tuning, quantization, and distillation — adapt LLMs for your use case.

Transformer ArchitecturesPyTorch & GPU ImplementationsFull Syllabus Access

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Instructor

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11 Modules

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11 Lessons & Labs

Enrollment1-Year Full Access

₹3,999

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1-Year full access to all 11 modules & labs

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Overview & Outcomes

Course Learning Objectives

Adapt pre-trained models for specific tasks. Transfer learning, fine-tuning, instruction tuning, LoRA, QLoRA, PEFT, quantization, distillation, and model selection strategies.

Core Curriculum Competencies

What you'll master

Parameter-Efficient Fine-Tuning (PEFT): LoRA, QLoRA & Prefix Tuning
Instruction fine-tuning: Alpaca, ShareGPT & dataset formatting
Quantization techniques: bitsandbytes (4-bit/8-bit), GPTQ & AWQ

Supervised Fine-Tuning (SFT) training loops with Hugging Face TRL

Alignment techniques: RLHF (PPO) & Direct Preference Optimization (DPO)

Model merging (MergeKit, SLERP, DARE) & custom model weights

Syllabus & Modules

Course Curriculum

A comprehensive breakdown of all modules, theory readings, interactive quizzes, and compiler practice labs.

Module 1: Transfer Learning Fundamentals

1 Lessons

1.1Transfer Learning FundamentalsREADING

Module 2: Fine-Tuning Pre-trained Models

1 Lessons

2.1Fine-Tuning Pre-trained ModelsREADING

Module 3: Instruction Tuning

Locked

3.1Instruction TuningREADING

Module 4: Parameter-Efficient Fine-Tuning (PEFT)

Locked

4.1Parameter-Efficient Fine-Tuning (PEFT)READING

Module 5: LoRA: Low-Rank Adaptation

Locked

5.1LoRA: Low-Rank AdaptationREADING

Module 6: QLoRA: Quantized LoRA

Locked

6.1QLoRA: Quantized LoRAREADING

Full Syllabus Gated (9+ Modules)

Unlock Full Curriculum & Labs

Enroll to unlock all 11 modules, 11 coding labs, automated graded quizzes, solution walk-throughs & verified certificate.

Log in to buy for ₹3,999

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Lead Instructor & Mentor

Instructor

Passionate engineer and educator specializing in core algorithms, production backend systems, and modern AI engineering.