Generative AI Course
Program Overview of Generative AI Course
Who Is This Program For?
The Generative AI Specialization Course is designed for a wide range of professionals and enthusiasts who are eager to dive into the world of advanced AI technologies. This program is ideal for:
Course learning objectives
Skills you'll gain with Generative AI Specialization Course
Python Programming
Statistics and Probability
Calculus for AI
Vector Algebra
Transformer Models
Natural Language Processing (NLP)
GPT Architecture
Neural Networks (MLP, CNN, RNN)
Diffusion Models
Large Language Models (LLMs)
Model Fine-Tuning (LoRA, RAG)
Generative Adversarial Networks (GANs)
Multimodal AI (Text, Image, Sound)
Vector Databases (Pinecone, FAISS, ChromaDB)
AI Frameworks and tools
PyTorch is one of the most popular frameworks for developing deep learning models. Its dynamic nature makes it popular for research and production, helping users build neural networks for various applications like image recognition and NLP.

AI Architectures & Fine-Tuning
Master Advanced AI Models & Techniques
In this course, you'll explore the latest AI architectures and their fine-tuning techniques, gaining hands-on experience with state-of-the-art models used in industries such as healthcare, finance, and language generation.
LLaMA3
What it is
LLaMA3 is Meta’s newest large language model designed for long-form text generation, translation, and NLP tasks. It now supports over 30 languages and has been trained on 15 trillion tokens, offering improved efficiency, accuracy, and faster performance compared to earlier versions.
Fine-Tuning
With LoRA (Low-Rank Adaptation) and RAG (Retrieval-Augmented Generation), LLaMA3 can be fine-tuned to deliver highly efficient, relevant, and cost-effective outputs, while using fewer computational resources.
Applications
Used in NLP tasks like chatbots, language translation, and text summarization. Custom conversational AI for enterprises. Large-scale text generation and document summarization.
Mistral
What it is
Mistral is a lightweight and powerful model optimized for domain-specific tasks in industries like finance and healthcare. It offers exceptional precision while being adaptable to smaller, niche applications with minimal resource usage.
Fine-Tuning
Mistral uses LoRA to minimize computational costs while enhancing domain-specific outputs, making it ideal for high-quality results in specialized tasks.
Applications
Used in medical diagnoses and clinical data analysis. Financial risk assessments, fraud detection, and algorithmic predictions. Niche tasks requiring targeted AI solutions for smaller datasets.
Gemini
What it is
Gemini is Google DeepMind’s most advanced multimodal model, combining vision, language, and reasoning into one unified system. It excels in complex tasks like image understanding, text generation, and multimodal reasoning with high accuracy.
Fine-Tuning
Gemini supports advanced fine-tuning methods, enabling optimized performance for multimodal tasks involving text, vision, and audio. This ensures high adaptability across various industries.
Applications
Used in creative content generation integrating images and text. Development of autonomous agents and decision-making systems. Visual understanding tasks like object detection and multimodal reasoning.
Techniques Explained for Generative AI
LoRA (Low-Rank Adaptation)
What it is
LoRA fine-tunes large models by focusing on specific layers, reducing the number of trainable parameters. This enables faster and more efficient customization of massive models like LLaMA3 and Gemini.
How it works
LoRA adapts the model weights by introducing low-rank matrices, ensuring fine-tuning is lightweight while maintaining high performance.
Why it matters
LoRA is ideal for low-resource environments, enabling businesses to fine-tune models cost-effectively without retraining the full model.
RAG (Retrieval-Augmented Generation)
What it is
RAG improves model outputs by retrieving real-time information from external sources. It combines a retrieval system with a pre-trained language model to produce accurate, context-aware responses.
How it works
RAG searches for relevant documents during inference and integrates the retrieved content into the model’s generation pipeline. This ensures answers are grounded in external knowledge.
Why it matters
RAG is perfect for tasks requiring up-to-date factual information, such as: Customer support systems. Research tools. Dynamic question-answering systems.
Multimodal Techniques
What it is
Multimodal AI integrates text, images, and other data types into a single model. Models like Gemini and LLaMA3 Vision combine modalities to deliver advanced reasoning and generation capabilities.
How it works
Multimodal systems process multiple inputs (e.g., images and text), align them into a shared representation, and generate outputs that combine insights from all modalities.
Why it matters
Multimodal techniques power: Visual Question Answering (VQA) for understanding images and text. Content generation blending visuals and natural language. Autonomous systems that require diverse input analysis for decision-making.
Gen AI Course Roadmap
What Sets Us Apart?
Feature | Our Program | Other Courses |
---|---|---|
Expert-Led Sessions | ✔ 24 weeks of instruction from top-tier professionals with industry experience | ✘ Often lack guidance from seasoned experts, relying on less experienced instructors |
Flexible Learning Options | ✔ Accessible 24/7 with over 150 hours of on-demand content | ✘ Limited accessibility and rigid learning schedules |
Practical Assessments | ✔ 15 practical assessments for hands-on practice | ✘ Minimal practical exposure and hands-on opportunities |
Real-World Assignments | ✔ Engage in 14+ real-world assignments directly linked to industry challenges | ✘ Minimal practical exposure and hands-on opportunities |
Live Doubt-Clearing Sessions | ✔ 11 live sessions with experts for doubt resolution | ✘ Limited opportunities for real-time support and query resolution |
Capstone Projects | ✔ 2-3 capstone projects applying skills to real-world problems | ✘ Few or no chances to work on substantial, real-world projects |
Live Interviews | ✔ 5 mock interviews to prepare you for the real world | ✘ Lack of structured live interview preparation |
Mock Interviews | ✔ 10 mock interviews to prepare for real job scenarios | ✘ Lack of structured mock interview preparation |
Career and Placement Support | ✔ Comprehensive support for job placements, including resume reviews and salary negotiation tips | ✘ Often lack continuous support for career advancement and placement |
Fee Structure
- Refund of up to 70% if you don’t get placed within 10 months (maximum refund ₹49,000).
Additional Benefits:
- Job Assistance: Our program ensures support until you secure a role. 100% Placement Program: We are fully committed to helping you find the right opportunity.
- Real-World Projects: Gain hands-on experience with projects based on real industry scenarios.
- Comprehensive Curriculum: Gain expertise in generative AI across text, image, and audio applications, including multimodal AI.
Testimonials of our Successful Learners
What our learners have to say
Frequently Asked Questions About Generative AI Specialization
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