AI Model Fine-Tuning Online Course

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25 hrs of E-Learning Videos
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AI Model Fine-Tuning Course Overview

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Upcoming AI Model Fine-Tuning Batches

21-09-2026
Mon-FriWeekdays Regular
08:00 AM & 10:00 AM Batches(Class 1Hr - 2Hrs) / Per Session
23-09-2026
Mon - FriWeekdays Regular
06:00 PM & 08:00 PM Batches(Class 1Hr - 2Hrs) / Per Session
25-09-2026
Sat-SunWeekend Batch
09:00 AM & 01:00 PM Batches(Class 2Hr - 4Hrs) / Per Session
Can't find a batch? Pick your own schedule

AI Model Fine-Tuning Course Syllabus

Join our AI Model Fine-Tuning Course! Learn AI model fine-tuning through transfer learning, instruction tuning, LoRA, QLoRA, PEFT, dataset preparation, evaluation, alignment, multimodal models, optimization, deployment, and production-ready customization workflows.

  • Fine-tuning fundamentals
  • Pre-training vs fine-tuning
  • Transfer learning
  • Foundation models
  • When to fine-tune
  • Fine-tuning lifecycle
  • Common use cases
  • Neural network fundamentals
  • Loss functions and optimization
  • Backpropagation
  • Training and validation
  • Overfitting and regularization
  • Learning rates and schedulers
  • Model checkpoints
  • Large Language Models
  • Vision foundation models
  • Multimodal foundation models
  • Model architectures
  • Model checkpoints
  • Hugging Face ecosystem
  • Model selection strategies
  • Data collection
  • Data cleaning
  • Data preprocessing
  • Dataset formatting
  • Instruction-response datasets
  • Train, validation, and test splits
  • Data quality and deduplication
  • Synthetic data generation
  • Full fine-tuning
  • Transfer learning workflows
  • Supervised fine-tuning
  • Domain adaptation
  • Task-specific fine-tuning
  • Training configuration
  • Checkpoint management
  • PEFT fundamentals
  • LoRA
  • QLoRA
  • Adapters
  • Prefix tuning
  • Prompt tuning
  • Parameter and memory efficiency
  • Instruction tuning
  • Chat model fine-tuning
  • Prompt-response datasets
  • Conversational datasets
  • Multi-turn training
  • System and user instructions
  • Instruction-following evaluation
  • Supervised fine-tuning (SFT)
  • Preference optimization
  • DPO
  • ORPO and related approaches
  • Alignment fundamentals
  • Reward modeling concepts
  • Domain-specific LLM customization
  • Image classification
  • Object detection
  • Image segmentation
  • Vision Transformer fine-tuning
  • Transfer learning for computer vision
  • Dataset augmentation
  • Vision model evaluation
  • Vision-language models
  • Image-text datasets
  • Multimodal instruction tuning
  • Visual question answering
  • Document understanding
  • Multimodal evaluation
  • Fine-tuning multimodal foundation models
  • GPU and accelerator fundamentals
  • Mixed-precision training
  • FP16 and BF16
  • Gradient accumulation
  • Gradient checkpointing
  • Distributed training
  • Memory optimization
  • Training performance optimization
  • Model evaluation strategies
  • Accuracy and task-specific metrics
  • LLM evaluation
  • Human evaluation
  • Benchmark datasets
  • Hallucination evaluation
  • Safety and robustness testing
  • Comparing base and fine-tuned models
  • Hugging Face Transformers
  • PEFT
  • TRL
  • Datasets
  • Accelerate
  • PyTorch
  • Unsloth
  • Weights & Biases
  • Experiment tracking
  • Model quantization
  • 4-bit and 8-bit inference
  • Model merging
  • Model compression
  • Inference optimization
  • vLLM and optimized serving
  • API deployment
  • Docker-based deployment
  • Dataset licensing and provenance
  • Privacy considerations
  • Bias and fairness
  • Model safety
  • Fine-tuning security
  • Model versioning
  • Monitoring and drift
  • Continuous evaluation
  • Production model lifecycle
Need customized curriculum?
Build Resume & Get PlacedPlacement Support With Resume Preparation & Interview Guidance

Hands On AI Model Fine-Tuning Projects

Enroll in our AI Model Fine-Tuning Course, gain practical experience customizing foundation models through dataset preparation, supervised fine-tuning, LoRA, QLoRA, model evaluation, opti
mization, and deployment for real-world AI applications.

Domain-Specific LLM Fine-Tuning Project

Fine-tune a pre-trained language model using a domain-specific instruction dataset. Build a specialized AI assistant capable of generating accurate responses for a selected business or industry domain.

Customer Support AI Assistant Fine-Tuning

Develop a conversational AI assistant by fine-tuning an LLM on customer-support conversations, FAQs, and product information. Evaluate response quality and deploy the customized model as an API.

Vision Model Fine-Tuning & Deployment

Fine-tune a pre-trained computer vision model for a specialized image classification or object detection task. Optimize the model for efficient inference and deploy it in a real-world application.

For Corporates

Educate your workforce with new skills to improve their performance and productivity.

Corporate Training
"Leading Companies We've Served"
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Our Instructor
Name
Mr. Rajesh
Experience
8+ Years
Specialized in
AI Model Fine-Tuning, Machine Learning, Deep Learning, LLMs, Generative AI, Transfer Learning, LoRA, QLoRA, PEFT, Model Optimization, and AI Deployment.
More Details
Mr. Rajesh is an AI professional with 8+ years of experience, specializing in model fine-tuning, machine learning, deep learning, LLMs, Generative AI, LoRA, QLoRA, PEFT, and deployment.

AI Model Fine-Tuning Course Objectives

Our AI Model Fine-Tuning Course aims to equip learners with practical skills to customize, optimize, evaluate, and deploy foundation models for specialized AI applications using modern fine-tuning techniques.

Fine-tuning is the process of adapting a pre-trained AI model using task-specific or domain-specific data to improve its performance for specialized applications.

Basic knowledge of Python, machine learning, and deep learning is recommended. Familiarity with neural networks and LLMs will help you understand advanced fine-tuning concepts.

LoRA and QLoRA are parameter-efficient fine-tuning techniques that reduce the computational and memory requirements needed to adapt large AI models.

Job Assistance Program

Our Job Assistance Programme offers you special guidance through the course curriculum and helps in your interview preparation.

Specialised Curriculum
Get on-field knowledge and skills from our expert instructors.
Assessment
Upgrade your on-field skills with our assessments and track your progress in real time.
Hands-on Project
Our hands-on project help you gain experience in real-time working.
Certification Guidance
A global certificate always helps you stand out from the crowd.
Portfolio Building
Experts guide you to maximise your profile with current industry trends that employers expect.
Placment Cell
We promote your abilities and showcase your portfolio to employers.

AI Model Fine-Tuning Career Opportunity

AI Model Fine-Tuning offers careers as LLM Engineer, AI Engineer, Machine Learning Engineer, Generative AI Developer, NLP Engineer, and Model Optimization Engineer, with salaries varying by experience, skills, location, and employer.

Annual Pay Scale
Placement Designation
Employers
Annual Salary
Hiring Companies

Placement Guidance & Interview Preparation

Infibee’s placement guidance navigates you to your desired role in top organisations, ensuring you stand out and excel in every opportunity.

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I completed the Workday HR course at Infibee Technologies and the training was really helpful for my career growth. The trainers support students by providing simple explanations which include real-world examples of every topic. Highly recommended to join now.
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AI Model Fine-Tuning Course FAQ's

Infibee AI Model Fine-Tuning Course offers wide range of services that suits for both fresher and experienced persons via both offline and online at your suitable time slots.

You need not worry about having missed a class. Our dedicated course coordinator will help them with anything and everything related to administration. The coordinator will arrange a session for the student with trainers in place of the missed one.

Yes, of course. You can contact our team at Infibee Technologies, and we will schedule a free demo or a conference call with our mentor for you.

We provide classroom, online, and self-based study material and recorded sessions for students based on their individual preferences.

Yes, all our trainers are industry professionals with extensive experience in their respective domains. They bring hands-on practical and real-world knowledge to the training sessions.

Yes, participants typically receive access to course materials, including recorded sessions, assignments, and additional resources, even after the training concludes.

We provide placement assistance to students, including resume building, interview preparation, and job placement support for a wide range of software courses.

Yes, we offer customisation of the syllabus for both individual candidates and corporate also.

Yes, we offer corporate training solutions. Companies can contact us for customised programmes tailored to their team’s needs.

Participants need a stable internet connection and a device (computer, laptop, or tablet) with the necessary software installed. Detailed technical requirements are provided upon enrollment.

In most cases, such requests can be accommodated. Participants can reach out to our support team to discuss their preferences and explore available options.

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