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Master In Generative AI Training

A comprehensive program covering Generative AI foundations, LLMs, prompt engineering, RAG, fine-tuning, multimodal AI, deployment, and real-world enterprise use cases.

4.5/5

Level

Advanced

Duration

8 weeks

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About Master In Generative AI Training?

The Master in Generative AI Training program is an advanced, end-to-end curriculum designed to build strong conceptual and practical expertise in modern Generative AI systems. Delivered through Jast Tech, this course takes learners from core AI and deep learning principles to cutting-edge Large Language Models, diffusion models, and multimodal AI applications. Participants gain hands-on experience with prompt engineering, vector databases, retrieval-augmented generation (RAG), fine-tuning LLMs, and deploying scalable AI solutions. The program emphasizes real-world implementation using industry tools such as OpenAI APIs, Hugging Face, LangChain, and cloud platforms. Learners explore responsible AI practices, security considerations, and performance optimization techniques required in enterprise environments. By integrating theory with applied projects, this course prepares professionals for roles such as Generative AI Engineer, AI Solution Architect, and Applied LLM Specialist. The curriculum is structured to match current industry demands, ensuring learners can confidently design, build, and deploy production-ready Generative AI systems across domains like healthcare, finance, education, and content automation.

Job Roles You Can Achieve
After completing this course
  • Solutions Architect
  • Technical Consultant
  • Implementation Specialist
  • System Administrator
  • IT Professional

Master In Generative AI Training Curriculum

1
Module 01

Foundations of AI & Generative Models

Establishes the mathematical and conceptual base needed to understand how generative systems learn data distributions and create new content.

Introduction to AI, ML, and Deep Learning
Evolution of Generative AI
Discriminative vs Generative Models
2
Module 02

Neural Networks & Transformers

Explains why transformers power modern LLMs and how attention enables contextual understanding at scale.

Deep neural networks refresher
Attention mechanisms
Transformer architecture deep dive
3
Module 03

Large Language Models (LLMs)

Focuses on how LLMs are built, optimized, and used in production systems.

GPT, BERT, T5 architectures
Tokenization and embeddings
Training vs inference workflows
4
Module 04

Prompt Engineering & Optimization

Teaches systematic methods to control LLM outputs for accuracy, reasoning, and consistency.

Prompt design patterns
Chain-of-thought prompting
Prompt evaluation and tuning
5
Module 05

Embeddings & Vector Databases

Covers the backbone of semantic search and contextual retrieval in AI applications.

Semantic embeddings
Vector similarity search
FAISS, Pinecone, ChromaDB

Related Courses

Training Roadmap

Seven intentional milestones — from first session to dream job.

Onboarding

01
  • Meet your industry mentor
  • Define your goals
  • Skill gap assessment

Core Learning

02
  • Live interactive classes
  • AI-curated content
  • Recorded sessions

Hands-on Practice

03
  • Weekly assignments
  • MCQ evaluations
  • Module quizzes

Real Projects

04
  • 3 live industry projects
  • Portfolio building
  • Case studies

Mentorship

05
  • 1:1 doubt sessions
  • Peer collaboration
  • Expert feedback

Certification

06
  • Exam preparation
  • Practice dumps
  • Industry-recognised certificate

Career Launch

07
  • Resume crafting
  • Mock interviews
  • Job placement support

Key Projects

01

Enterprise Knowledge Assistant using RAG

This project involves building a Generative AI-powered enterprise assistant that answers user queries using internal documents by combining embeddings, vector databases, and retrieval-augmented generation. Learners desig...
02

Custom Fine-Tuned LLM for Domain-Specific Q&A

In this project, learners fine-tune a pre-trained large language model on domain-specific datasets such as legal, healthcare, or finance content. The focus is on data preparation, parameter-efficient fine-tuning techniqu...
03

Multimodal Content Generation Platform

This project focuses on developing a platform that generates text, images, and summaries using multimodal Generative AI models. Learners integrate text-to-image models with LLMs, design user workflows, and deploy a scala...

Available Course Schedules

Select a schedule that works best for you

Next batch starting soon — Inquire for exact dates
Weekend

Starts

10 Oct 2026

Time

09:30 AM – 12:30 PM

Duration

8 weeks

Weekdays

Starts

12 Oct 2026

Time

07:00 AM – 09:00 AM

Duration

8 weeks

Weekend

Starts

17 Oct 2026

Time

02:00 PM – 05:00 PM

Duration

8 weeks

Weekdays

Starts

19 Oct 2026

Time

08:00 PM – 10:00 PM

Duration

8 weeks

Need a custom schedule?

Our team will craft the perfect batch for you.

What Our Happy Students Say

Real Feedback from our candidates

What We Offer Beyond Courses

24/7 Support

Round-the-clock assistance

LinkedIn Profile

Professional profile building

Resume Writing

Expert resume crafting

Alumni Guidance

Mentorship from graduates

Interview Prep

Mock interviews & tips

Live Projects

Real-world experience

Tejas Kumar

Tejas Kumar

Guidewire Developer • Cognizant

"The practical hands-on scenarios and real-world project assignments made all the difference. I was able to clear the technical interviews on my first attempt."

Verified PlacementJastTech Alumni
Sakshi Singh

Sakshi Singh

PolicyCenter Specialist • Deloitte

"Excellent mentors with deep industry domain knowledge. The LMS access and 24/7 doubt resolution gave me the confidence to transition into a high-paying role."

Verified PlacementJastTech Alumni
Sanjay Patel

Sanjay Patel

ClaimCenter Consultant • PwC India

"This course completely transformed my career trajectory! From resume review to mock interviews, the placement team supported me every step of the way."

Verified PlacementJastTech Alumni

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See how we stand out from the competition

Comprehensive Curriculum
JastTech Advantage

Well-structured, up-to-date curriculum designed by industry experts to build strong fundamentals and advanced knowledge.

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Outdated or incomplete curriculum that may not cover current industry needs.

Practical Hands-on Learning
JastTech Advantage

Extensive practical sessions, live demos, and hands-on exercises to ensure real learning.

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Limited practical exposure with theory-heavy teaching approach.

Expert Instructors
JastTech Advantage

Learn from certified professionals with years of industry experience and teaching expertise.

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Instructors with limited industry experience or practical knowledge.

Real-world Projects
JastTech Advantage

Work on real-world projects that enhance problem-solving skills and build a strong portfolio.

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Lack of real-world projects or unrealistic practice examples.

Assignments & Assessments
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Regular assignments, quizzes, and assessments to track progress and strengthen concepts.

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Irregular assessments or no proper evaluation of learning.

Career Support
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Resume building, interview preparation, and placement assistance to boost your career.

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Limited or no career support and placement assistance.

Doubt Support
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24/7 doubt resolution and personalized guidance from instructors whenever you need it.

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Certification
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Industry-recognized certificate that validates your skills and enhances your career opportunities.

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Lifetime Access
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Lifetime access to course content, recordings, and resources even after completing the course.

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Limited access duration with extra charges for resources.

Affordable Fees
JastTech Advantage

High-quality training at affordable prices with no hidden costs and flexible payment options.

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High course fees with hidden charges and no flexibility.

Certification Details

Master In Generative AI Training – Associate

  • Exam Name

    Master In Generative AI Training – Associate

  • Duration

    130 minutes

  • Format

    Multiple Choice & Multi-Response

  • Passing Score

    720 (Scale: 100–1000)

  • Level

    Associate

Certificate of Completion

Prepare

Top Interview Questions

Curated questions with expert answers to help you ace your next interview.

Q1: What is Generative AI?

Generative AI refers to models that learn data distributions and generate new content such as text, images, audio, or code.

Q2: What problem does RAG solve?

RAG reduces hallucinations by grounding model responses in external, retrievable knowledge sources.

Q3: Difference between fine-tuning and prompt engineering?

Prompt engineering modifies inputs to guide outputs, while fine-tuning updates model weights for deeper adaptation.

Q4: Why are transformers important in LLMs?

Transformers handle long-range dependencies efficiently using attention mechanisms, enabling contextual understanding.

Q5: What are embeddings used for?

Embeddings convert data into vector representations that capture semantic meaning for search and retrieval tasks.

Support

Frequently Asked FAQs

Can't find what you're looking for? Reach out to our support team anytime.

Q1: Who should take this course?

This course is ideal for software engineers, data scientists, ML engineers, and tech professionals aiming to specialize in Generative AI.

Q2: Are coding skills required?

Yes, basic Python knowledge is required. Advanced AI concepts are taught from the ground up.

Q3: Does the course cover real-world tools?

Yes, it includes OpenAI APIs, Hugging Face, LangChain, vector databases, and cloud deployment practices.

Q4: Is this course suitable for enterprise roles?

Absolutely. The curriculum is aligned with enterprise AI architecture and deployment standards.

Q5: Will I build hands-on projects?

Yes, multiple production-style projects are included to reinforce practical skills.

The support team was very cooperative and responsive. They made sure all doubts were cleared without delay. Great experience overall.

Vedant Shinde
Vedant Shinde

I had a great experience with the RF Circuit Design course. Thanks to the teaching staff for such a well planned and structured curriculum it really helped me clear my technical certification for my job.

Irfan Shah
Irfan Shah

I enrolled in the Post-Silicon Validation Certification Training at JastTech and found it quite different from typical courses. They focus on debugging techniques and real chip-level scenarios, which gave me a better idea of how things work.

Gayatri Sonawane
Gayatri Sonawane

One thing I really liked about the Data Analyst course at JastTech is their focus on consistency. Regular sessions and tasks help you stay on track and build a daily learning habit. Also, they provide recordings after live sessions, which help in revision.

Sanmitra Kamble
Sanmitra Kamble

I joined JastTech for the DFT course a few months back. At first, I wasn’t sure what to expect, but the classes turned out to be really helpful. The teaching is simple and not too complicated, which helped me keep up.

sachin kumar
sachin kumar

Take the Next Step in Your Career

Join thousands of learners who have upgraded their skills with our industry-focused training programs. Our experts are here to guide you every step of the way.

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