Generative AI Professional Program

This module builds a strong foundation in Artificial Intelligence and introduces how Generative AI is transforming industries. You will understand core AI concepts and how modern AI systems generate content.

• Difference between AI, Machine Learning, and Deep Learning explained clearly
  • Overview of Generative AI and how it works in real-world systems
  • Understanding Generative vs Discriminative models
  • Industry applications including chatbots, automation, content creation, and coding assistance
  • Overview of popular AI tools like ChatGPT and other AI platforms
  • Hands-on: Basic prompt interaction and experimentation with AI models

This module introduces Python programming, the backbone of AI development, along with essential data handling tools used in AI workflows.

• Python fundamentals, including variables, loops, and functions
  • Working with Jupyter Notebook and VS Code environments
  • Introduction to NumPy for numerical operations
  • Data handling using Pandas
  • Reading and processing CSV and JSON files
  • API basics and response handling for AI integration

This module covers the core concepts of Machine Learning and how models learn from data to make predictions.

• Supervised and unsupervised learning concepts
  • Basics of regression and classification models
  • Understanding training vs testing datasets
  • Overfitting and underfitting problems and solutions
  • Evaluation metrics for model performance
  • Hands-on implementation of basic ML models

This module introduces neural networks and how deep learning powers advanced AI systems.

• Structure and working of neural networks and layers
  • Activation functions and their importance
  • Loss functions and optimization techniques
  • Introduction to TensorFlow and PyTorch frameworks
  • Working with pre-trained models
  • Hands-on execution of deep learning models

This module focuses on modern generative architectures that create text, images, and other content.

• Overview of generative model architecture
  • Generative Adversarial Networks (GANs)
  • Variational Autoencoders (VAE)
  • Diffusion models and their applications
  • Use cases in text, image, and audio generation
  • Hands-on exploration with generative AI tools

This module explains the breakthrough technology behind modern AI systems like ChatGPT.

• Understanding attention mechanism in AI models
  • Transformer architecture and its components
  • Tokenization and embedding concepts
  • Overview of GPT and BERT models
  • Practical demonstration of LLM usage

This module teaches how to effectively communicate with AI models for better and accurate outputs.

• Structuring effective prompts
  • Zero-shot and few-shot prompting techniques
  • Chain-of-thought reasoning approach
  • Role-based prompting strategies
  • Prompt optimization techniques
  • Hands-on practice with real scenarios

This module explores the tools and frameworks used to build AI-powered applications.

• Working with LLM APIs
  • Introduction to Hugging Face models and ecosystem
  • Basics of the LangChain framework
  • Vector databases like FAISS and Pinecone
  • Semantic search applications
  • Hands-on implementation of AI workflows

This module focuses on developing real-world AI applications using LLMs and advanced architectures.

• Understanding application architecture design
  • Chatbot development using AI models
  • Retrieval-Augmented Generation (RAG) systems
  • Document-based Question Answering systems
  • Context management and memory handling
  • Hands-on chatbot building project

This module prepares learners to deploy AI systems and understand ethical responsibilities.

• Deployment using FastAPI and Flask frameworks
  • Introduction to cloud computing basics
  • Overview of MLOps practices
  • AI ethics, privacy, and responsible AI usage
  • Capstone project development
  • Final project presentation and evaluation

This module introduces autonomous AI systems that can perform multi-step tasks.

• Introduction to AI agents and their architecture
  • Autonomous workflow automation
  • Multi-step reasoning systems
  • Tools and frameworks for building agents
  • Real-world AI agent use cases

This module enables learners to build AI applications without deep programming knowledge.

• Introduction to no-code AI platforms
• Workflow automation using AI tools
• Building applications without coding
• Business use cases of no-code AI solutions

This module connects learning with real-world industry applications and problem-solving.

• Applications of AI in marketing
  • AI use cases in HR operations
  • AI in business and operational workflows
  • Real-world industry case studies
  • Problem-solving using Generative AI