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Advanced Generative AI

DURATION
6 Months

MODE OF TRAINING
Online/Offline

LEVEL
Advanced

Unlock the Power of Generative AI

Embark on a journey into the transformative field of Generative AI with our expertly crafted course. Explore cutting-edge models like Variational Autoencoders (VAEs), Transformers, Large Language Models, and technologies such as Stable Diffusion. This course offers a thorough understanding of the core algorithms behind these models, their design methodologies, and diverse real-world applications. Unlock the power of Generative AI to produce text, images, and other media, redefining the possibilities of digital content creation.

Step into the future of AI-driven innovation with our Generative AI course. From mastering Variational Autoencoders (VAEs) and Transformers to understanding Large Language Models and Stable Diffusion, this course is your gateway to creativity and technology. Learn how these models are reshaping industries and acquire the skills to craft text, visuals, and media that redefine content creation.

Advanced Generative AI

Introduction To Artificial Intelligence +
  • Introduction to AI
    AI vs ML vs DL
    Types of learning (Supervised, Unsupervised & Reinforcement)
    Core Difference between ML and DL
    Life Cycle of ML and DL Project
  • Modular Case Study: 1
  • Formative Assessment: 1
Introduction To Generative AI +
    Introduction to Generative AI
    Overview of generative AI technologies
    Applications and case studies across industries
  • Modular Case Study: 2
  • Formative Assessment: 2
Getting Started With Large Language +
  • Into to large language Models
    History of NLP
    Intro to RNN,LSTM,GRU
    Intro to Encoder Decoder Model
  • Modular Case Study: 3
  • Formative Assessment: 3
Prompt Engineering And Working With LLM +
  • Intro to Prompt Engineering
    LLM with Prompt Engineering
    Introduction to GPT models
    Understanding how GPT-3 and GPT-4 work
    Training on popular LLMs like GPT (Generative Pre-trained Transformer)
    Practical applications of LLMs in generating text, code, and more
    Case Study: Creating a project with LLMS
  • Modular Case Study: 4
  • Formative Assessment: 4
Working with Open AI API +
  • Intro To Open Ai
    Utilizing OpenAI APIs
    Setting up and authenticating API usage
    Practical exercises using GPT-3/GPT-4 for text generation
    Understanding DALL-E and its capabilities in image generation
    📜Hands-on project to generate images from textual descriptions
  • Modular Case Study: 5
  • Formative Assessment: 5
Working with Google Gemini Gen API +
  • Getting Started with Gemini
    How to obtain an API key for Gemini
    Overview of the Gemini API and accessing its features
    Detailed exploration of different Gemini models
    Selecting and initializing the right model for specific tasks
    Step-by-step project to create an AI-powered chatbot using Gemini
  • Modular Case Study: 6
  • Formative Assessment: 6
Working with Meta’s LLaMA API +
  • Introduction of LLaMA
    Comparison with other large language models like GPT-3 and GPT-4
    Key features and capabilities of LLaMA
    Understanding the Model Architecture of LLaMA
    Discussion on model sizes and capabilities
    Environment setup: Installing necessary libraries and tools.7. Intro to the architecture of LLaMA models
    Understanding the differences between LLaMA model variants (8B, 13B, 30B, and 70B parameters)
    Implementing text generation using LLaMA
  • Modular Case Study: 7
  • Formative Assessment: 7
Working With Hugging Face Ecosystem +
  • Introduction to the Hugging Face ecosystem and the Transformers library
    Exploring Hugging Face Models and Tokenizers
    Project
    Introduction to the Trainer API
    Integrating Hugging Face models with web application
  • Modular Case Study: 8
  • Formative Assessment: 8
Building Gen AI Apps Using Lang Chain +
  • Introduction to the LangChain framework
    Understanding the purpose and core components of LangChain Framework
    LangChain Setup and necessary dependencies
    Basic configuration and setup for development
    Step-by-step guide
  • Modular Case Study: 9
  • Formative Assessment: 9
Intro To RAG +
  • Intro To RAG
    Building applications using RAG
    LLMs in Depth
    Fine Tuning LLMs
    Training LLMs by Implementing Fine Tuning
  • Modular Case Study: 10
  • Formative Assessment: 10
Stable Diffusion by Stability AI +
  • Intro to Stable Diffusion
    Fundamentals of Diffusion Models
    Application of Stable Diffusion
    Modifying image attributes and styles using prompt engineering
    Parameters of image generation: seeds, prompts, and steps explained
    Tool For Stable Diffusion
    Fine-tuning and training Stable Diffusion on custom datasets
    Advanced prompt engineering and achieving specific artistic effects
    Introduction to variations and derivatives of Stable Diffusion (e.g.,DreamBooth for personalization)
    Using the Diffusion library for more control over the diffusion process
    Integrating Stable Diffusion models into web applications
    Advance Stable Diffusion Techniques
  • Modular Case Study: 11
  • Formative Assessment: 11

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