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Applied Generative AI Specialization

Learn to Develop and Deploy GenAI-Enabled Applications in Applied AI Course

Course Instructor: Vaibhav

FREE

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Why Join this Program
Earn an Elite Certificate
Earn a program completion certificate from Simplilearn, in partnership with Purdue University
Purdue University Edge
Become eligible for Purdue University Alumni Association membership on program completion
Hands-on Learning Experience
Build generative AI and agentic AI apps through hands-on, industry-relevant projects
Learn Popular GenAI Tools
Gain exposure to Copilot, Langchain, Hugging Face, Azure AI Studio, OpenAI, and other tools
Applied Gen AI Course Overview
This Applied Generative AI course equips you to develop AI-powered applications using industry-relevant tools and frameworks. Build expertise in key concepts like prompt engineering, GANs, VAEs, and LLM architectures while exploring advanced topics, including agentic AI, LLM fine-tuning, RAG, and AI governance for practical, real-world deployments.
Key Features
  • Simplilearn's JobAssist helps you get noticed by top hiring companies
  • Program certificate from Simplilearn, in partnership with Purdue University
  • 70+ hours of live, instructor-led training with industry experts
  • Hands-on learning with 7+ real-world projects and a capstone project
  • Gain in-demand skills like LLM fine-tuning, prompt engineering, and AI governance
  • Gain expertise with cutting-edge tools such as ChatGPT, Azure AI Studio, and LangChain
  • Comprehensive curriculum covering AI Literacy, Agentic Frameworks, and Generative AI
  • Become eligible for Purdue University Alumni Association membership on program completion
  • Course completion certificate hosted on the Microsoft Learn portal for Microsoft courses
  • Learn with a diverse cohort of professionals from industries like IT, banking, and education
Applied AI Course Details
Explore our applied generative AI course and acquire advanced skills for real-world applications. Learn prompt engineering, LLM architecture, transformers, and agentic AI. Build LLM applications, AI Agents and fine-tune models using tools like OpenAI, LangChain, CrewAI, Diffusion Models and MCP.
Partnering with IITM Pravartak
  • Earn a program certificate directly from IITM Pravartak Technologies Foundation within 90 days of program completion
  • Attend masterclasses led by faculty and/or alumni from premier institutes such as IITM and other IITs
  • Become eligible for a 2-Day campus immersion at IIT Madras Research Park
Collaborating with Microsoft
  • Access course completion badges/certificates on the Microsoft Learn portal
  • Learn Copilot fundamentals and Retrieval Augmented Generation (RAG)
Course Curriculum

1 Subject

Applied Generative AI Specialization

1 Exercises • 21 Learning Materials

Introduction

Introduction

Video
00:02:39

Intro 2

Video
00:00:05

Learning Path

ME-AGS: Program Induction

ME-AGS: Python Refresher with AI (Optional)

ME-AGS: AI Literacy

ME-AGS: Advanced Generative AI: Models and Architecture

ME-AGS: Advanced Generative AI: Models and Architecture

ME-AGS: Advanced Generative AI: Agentic AI Frameworks With Model Context and Tooling Protocols

ME-AGS: Advanced Generative AI: Image Generation

ME-AGS: Generative AI Governance

ME-AGS: Capstone Project

Electives

ME-AGS: Microsoft Azure AI Fundamentals: Generative AI

ME-AGS: Build a Foundation to Extend Microsoft 365 Copilot

ME-AGS: Masterclass

Exercise

AI Test

Exercise

Exploring GANs, Transformers, and Creative Applications

Exploring GANs, Transformers, and Creative Applications

PDF

GANs, Diffusion Models, and LLMs

PDF

Generative Adversarial Networks

PDF

A Comprehensive Survey of Architectures & Applications

A Comprehensive Survey of Architectures & Applications

PDF

Socio-technical aspects of Agentic AI

PDF

AI Agents, Clearly Explained

External Link

Agentic Workflows — IBM Think Article

External Link
WORK 16+ Skills Covered
Partnering with IITM Pravartak
  • Python Programming
  • Prompt Engineering
  • AI Literacy
  • Generative AI Fundamentals
  • Large Language Model LLM Architecture
  • Agentic AI and Autonomous AI Agents
  • LangChain for Workflow Design
  • Retrieval Augmented Generation RAG
  • LLM Fine Tuning and Customization
  • Stable Diffusion
  • Explainable AI
  • Variational Autoencoders VAEs
  • Transformers and Attention Mechanism
  • GenAI Application Development
  • LLM Benchmarking and Evaluation
  • Generative AI Governance and Ethics

The Gen AI module was an eye opener for me. The mentor's teaching style in the weekend sessions was spot on. While there's a lot of Gen AI content online, this module stood out for its structured approach and the mentor's interactive guidance. It made learning about AI easy, even for beginners like me.

Ashif Khan

Program Details
Explore our advanced Applied Generative AI course to deploy cutting-edge techniques in real-world scenarios. Master GANs, VAEs, and Agentic frameworks while utilizing tools like ChatGPT, DALL-E 2, and Hugging Face. Develop LLM applications using MCP, Multi-agent systems, and RAG applications.
Learning Path

AGS: Python Basics (Optional)

  • Procedural and OOP understanding
  • Python and IDE installation
  • Jupyter Notebook usage mastery
  • Implementing identifiers, indentations, comments
  • Python data types, operators, string identification
  • Types of Python loops comprehension
  • Variable scope in functions exploration
  • OOP explanation and characteristics

AGS: AI Literacy.

  • Foundations of Machine Learning and Generative AI.
  • Generative AI Algorithms: Neural Networks, GANs, and Transformers.
  • Large Language Models (LLMs) and Their Applications in Chatbots.
  • Image Generation Techniques: GANs, Diffusion Models, and VAEs.
  • Hands-On Practice with AI Tools: Chat GPT, Stable Diffusion, and more.
  • Explore Video Generation using Generative AI.
  • Prompt Engineering for Chatbots and AI-Driven Image Generation.

AGS: Advanced Generative AI - Models and Architecture

  • Introduction to Generative Models
  • Large Language Models Architecture
  • Variational Autoencoders (VAEs)
  • Generative Adversarial Networks (GANs)
  • Attention Mechanisms and Transformers

AGS: Advanced Generative AI - Building LLM Applications

  • Langchain and Workflow Design
  • Advanced Prompt Engineering Techniques
  • LLM Application Development
  • LangChain for LLM Development
  • RAG with LangChain
  • LLM Fine-Tuning and Customization
  • Benchmarking and Evaluation of LLM Capabilities
Course Instructor

tutor image

Vaibhav

19 Courses   •   2 Students

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