Generative AI Masters Program

About Course

Generative AI Masters Program

Step into the future with the Generative AI Masters Program—gain deep expertise in Generative AI, Large Language Models (LLMs), GPT, Prompt Engineering, Diffusion Models, AI Agents, and Multimodal AI. Designed by industry experts at Mentorbabaa Academy, this program empowers you with hands-on skills, real-world projects, and a path to global career opportunities in the booming AI landscape.

Why Generative AI Masters Program - MentorBaba Academy

Why Generative AI ?

Game-Changer Technology

Generative AI is not just a trend—it’s a revolution. From content creation to code generation, this is the tech reshaping industries.

Creativity Meets Code

Whether you’re writing, designing, or developing—Generative AI is your creative copilot. Learn how to harness it and stand out.

Explosive Job Growth

Demand for GenAI skills is skyrocketing. Get ahead with expertise that global tech companies, startups, and agencies are hiring for.

Global Reach

Work with global clients, on global problems, from anywhere. Generative AI opens doors to remote, freelance, and full-time roles worldwide.

Generative AI Masters Program

Prompt Engineering

Craft precise and powerful prompts for LLMs to generate meaningful, context-aware outputs.

AI Agents

Build autonomous agents that use memory, tools, and planning to accomplish real-world tasks.

LLMs & Transformers

Dive deep into the architecture behind OpenAI, Google Gemini, Claude and open-source LLMs like Mistral, Mixtral, and LLaMA.

Generative Applications

Learn how to create GenAI-powered apps that write, design, chat, and code—powered by the best APIs and frameworks.

RAG Systems

Build Retrieval Augmented Generation systems using vector databases like FAISS, Chroma, and more.

Production Deployment

Deploy GenAI apps to production using APIs, Docker, Streamlit, LangChain, Azure, and AWS.

Lead the Future with Most in Demand AI Program

Live Classes

Attend expert-led live sessions designed to keep you hands-on and future-focused.

Real Projects

Build real-world Generative AI applications like Chatbots, Content Creators, and Code Assistants.

Mentor Support

Get 1-on-1 mentoring and feedback from top AI professionals and practitioners.

Cutting Edge Tools

Work with GPT-4, Claude, Gemini, LangChain, and vector DBs—tools used in industry today.

Program Certificate

Earn a certificate from MentorBaba Academy upon successful completion of the program.

Career Guidance

Get career coaching, portfolio reviews, and interview preparation from hiring mentors.

Certification Included

Generative AI Masters Certificate

Showcase your advanced skills in LLMs, Agents, Prompt Engineering, and GenAI App Development.

Benefits of the course

Master Generative Models: Build and understand models like GPT, GANs, and Diffusion for generating text, images, and audio.
Hands-on with LLMs: Use tools like HuggingFace, LangChain, and OpenAI to fine-tune and prompt large language models effectively.
Build Real-World GenAI Apps: Create and deploy intelligent applications using Gradio, Streamlit, and multimodal APIs.
Ethical AI & Evaluation: Evaluate outputs using industry metrics and apply responsible AI practices to avoid bias and hallucinations.

Course Content

What is Generative AI? Concepts & History
Generative vs Discriminative Models
Overview of Key Generative Models (VAEs, GANs, Autoregressive, Diffusion)
Use-cases across industries (text, image, audio, video, code)
Challenges in generative modeling (mode collapse, overfitting, evaluation)
Tools, frameworks, and datasets for experimentation

Introduction to GANs: Generator and Discriminator roles
Loss functions: Binary Cross-Entropy, Wasserstein Loss
Common GAN variants: DCGAN, WGAN, StyleGAN
Diffusion Models: Forward vs Reverse process
Text-to-image models and Prompt-to-image pipeline
Challenges: Mode collapse, training instability, hallucination

Architecture of Transformers
Self-Attention, Multi-Head Attention & Positional Encoding
Decoding strategies: Greedy, Beam, Sampling, Top-k, Top-p
Fine-tuning LLMs vs Prompt-based learning
Popular LLMs: GPT, BERT, Mistral, LLaMA, Claude, Gemini

Prompt types: Zero-shot, One-shot, Few-shot
Best practices for prompt crafting and prompt chaining
Retrieval-Augmented Generation (RAG) basics
Finetuning LLMs: full model, adapter-based, instruction tuning
Data preparation for fine-tuning (tokenization, formatting)
Prompt evaluation frameworks (e.g., PromptSource, LM Eval Harness)
Build a prompt chain using LangChain; fine-tune a small LLM on a QA dataset

Introduction to multimodality and embeddings
Vision-Language Models (e.g., CLIP, Flamingo, LLaVA)
Text-to-image models: DALL·E, MidJourney, Stable Diffusion
Image-to-text: Captioning with BLIP, LLaVA
Audio generation and transformation: TTS, Voice Cloning
Video generation basics: Gen-1, RunwayML, Pika Labs
Tools & APIs for building multimodal experiences

Overview of GenAI app architectures
LangChain, LlamaIndex, and semantic search
State management: memory, context windows, retrieval
Agent-based workflows: ReAct, Toolformer, BabyAGI
App development with Gradio, Streamlit, or Next.js
Backend deployment: HuggingFace Spaces, AWS, GCP
Integrating APIs (e.g., OpenAI, Brevo, Replicate, Cohere)

Evaluation metrics for generative models (BLEU, ROUGE, FID, Perplexity)
Automated vs Human Evaluation
Prompt/Model robustness testing (adversarial examples)
Bias, fairness, toxicity, and hallucinations
Red-teaming and safety strategies
Responsible AI practices and governance
Optimization for latency, cost, and scalability

Capstone Project 1
Capstone Project 2
Capstone Project 3
Project Submission

Mentor

mentorbabaa

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30-Day Money-Back Guarantee

Skill LevelIntermediate
Course Duration: 45h

Requirements

Basic knowledge of Python and programming logic
Prior understanding of Machine Learning fundamentals (e.g., classification, overfitting, train/test split)
Familiarity with deep learning libraries such as TensorFlow or PyTorch
Comfortable with Jupyter Notebooks, APIs, and basic Linux commands

Target Audience

Developers & ML Engineers looking to expand their skills into generative AI and large language models
Data Scientists aiming to apply generative techniques in real-world projects and workflows
Tech Enthusiasts & Researchers interested in cutting-edge AI tools like GPT, Stable Diffusion, and CLIP
Educators & Content Creators exploring AI for automating content generation and enhancing creativity

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