Generative AI Classes In Boston

9 Lesson

40 Hours

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Overview

Prerequisites

Basic computer knowledge and familiarity with using the internet

Skills You Will Gain

Write clear, effective prompts to get accurate AI responses
Apply AI tools for content, research, and daily productivity tasks
Understand AI ethics, limitations, and responsible usage practices

Key Features

100% Money-Back Guarantee
Flexible Schedule
100% Job Assistance
Small Batches Upto 10 Participants

Course Curriculum

Lesson 1 - Introduction of GenAI

1. Introduction to Generative AI

2. Generative AI Applications

3. Understanding Probability and Statistics in Generative AI

4. Introduction to Generative Models

5. Deep Learning for Generative Models

6. Introduction to Generative Adversarial Networks (GANs)

7. Autoencoders

8. Transformers and Attention Mechanisms - "Attention is all you need".

Lesson 2 - Introduction of LLM Model

1. Introduction to Large Language Models (LLMs)

2. Architecture of Large Language Models

3. Text AI LLMs (GPT-3, GPT-4, LaMDA, LLaMA, Stanford Alpaca, Google FLAN, Poe, Falcon LLM)

4. Image AI Models & Services (Midjourney, Stable Diffusion, ControlNet (SD))

5. Video AI Models (Runway - Gen 1 & 2, Kaiber, D-ID)

6. Audio AI Models (ElevenLabs)

Lesson 3 - Learning Prompt Engineering using ChatGPT

1. Introduction to Prompt Engineering

2. Introduction to ChatGPT

3. Designing a prompt - The process and workflow

4. Avoiding prompt injections using delimiters

5. Defining constraints

6. Zero-shot Prompting

7. Few-shot Prompting

8. Persona Prompting

9. Chain of Thought

10. Adversial

Lesson 4 - Customizing LLM for own data

1. Type of Customization(Fine Tunning, Embeddings,RLHF)

2. Knowledge Graphs

3. Search-deep dive

Lesson 5 - GenAi and Enterprise Architecture

1. Enterprise Architecture overview

2. Gen AI postioning within Enterprise Architecture

3. Attention Architecture

4. Transformer Architeture

5. End to End AI Model Architecture with GenAI

6. Day in life of Data Scientist

Lesson 6 - Industrialisation and demos

1. How to industrialize models and enable ModelOps

2. When and how to recalibrate,re-train,re-build models

3. Search Architecture

4. Chatbot Architecture

5. Domain specfic architectures

Lesson 7 - Advanced AI App Development using Langchain

1. What is LangChain and when should you use it?

2. The LangChain Ecosystem

3. Supported LLMs

4. Case Study: Getting started with LangChain and OpenAI

5. Prompt composition and templates

6. Using multiple LLMs (Chains)

7. Working with Data loaders - Ingesting documents

8. Working with text splitters - Chunking Data

9. Working with Chains (Conversational Retrieval QA, Retrieval QA, Summarization, API etc.)

10. Working with Memory

11. Working with Embedding

Lesson 8 - Non-Microsoft Solution

1. OpenSource LLM-Overview

2. Other LLM Models(Cohere,AI21 etc)

3. Text AI LLMs (GPT-3, GPT-4, LaMDA, LLaMA, Stanford Alpaca, Google FLAN, Poe, Falcon LLM)

4. Image AI Models & Services (Midjourney, Stable Diffusion, ControlNet (SD))

5. Video AI Models (Runway - Gen 1 & 2, Kaiber, D-ID)

6. Audio AI Models (ElevenLabs)

Lesson 9 - Responsible AI in GenAI

1. When should retrain our LLM Model

2. Impact on environment

3. Biases and other ethical Issues

4. Copyrights and ownership

5. License types for models and its implications

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+91 7240740740 (India)

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Course Fees

SELF PACED LEARNING

US $ 499.00 US $ 439.00

Refund Policy

Duration : 40 hrs
Lifetime Free Upgrade
Reference Documents
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Online Class Room Program

US $ 899.00

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Duration : 40 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 27 Aug 2026
Weekday Batch 31 Aug 2026
Weekend Batch 29 Aug 2026

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Want to know Today's Offer

Generative AI Cert

Upon completion of igmGuru’s Generative AI Training, you will receive a Course Completion Certificate that authenticates your skills.

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