AI Course for Managers

Introduction to Deep Learning, Tensorflow & Feed Forward Neural Networks

Building Blocks of Artificial Neural Networks
What are Optimisers and Types of Optimisers
Math Behind Feed Forward Neural Network
Math Behind BackPropagation
Why Activation Functions & Importance
Introduction to Tensorflow
FFNN-Regression Script using Tensorflow
FFNN – Classification Script Using Tensorflow

Feed Forward Neural Network Coding

Foundations of Generative AI

Large Language Models (LLMs)

Small Language Models (SLMs)

Generative AI, Prompt Engineering using LangChains

What is Generative AI? Use cases in text, image, code, and conversation
Foundation Models: GPT, Claude, PaLM, Gemini, Mistral, LLaMA
Introduction to Lang Chains
Using LLMs using Lang Chains
What is Prompt Engineering
Prompt Engineering Principles
Zero-shot, Few-shot, Chain-of-Thought (CoT)
Best Way to Improve LLMs Accuracy
Doing Prompt Engineering using Lang Chains
PromptTemplate best practices with LangChain
Using ChatPromptTemplate, SystemMessagePrompt, HumanMessagePrompt
Prompt evaluation: temperature, top_p, stop, max_tokens

LangChain Framework

Amazon Bedrock & GenAI on Cloud

Retrieval-Augmented Generation (RAG) with LangChain

Why RAG? Token limits, context injection
Vector Embeddings: OpenAI, HuggingFace, Cohere
Vector DBs: FAISS, Pinecone, Chroma, Weaviate, Milvus
LangChain’s RetrievalQA Chain
Chunking strategies and TextSplitter
Hybrid search: Dense + Metadata filtering
SequentialChain vs SimpleSequentialChain
RunnablePassthrough, RunnableLambda (LCEL)
Creating Tool abstractions with @tool decorator
Integrating APIs (e.g., SerpAPI, Weather, Calculator)
Output parsers: StrOutputParser, StructuredOutputParser

Agentic AI

LangGraph – Multi-Agent DAG Framework

Multi-Agent Systems

LangFlow – Visual Low-Code Interface

Agentic AI – Build Autonomous Agents with LangChain

Model Context Protocol(MCP)

Model Context Protocol (MCP) and Multi-Agent Architectures

n8n for Agent Workflow Automation

LLMS: Hugging Face

Fine-Tuning and Pretraining Language Models

LLMOps & Production Deployment

Full Stack Application + Deployment(LLMOps)

Generative AI with Business Skills

Master Generative AI with a Focus on Scrum, Cultural Fit, Problem Solving, Analytical Thinking and Business Acumen

No.1 Syllabus on Generative AI

Generative AI Syllabus which covers Python, SQL, Applied Statistics, Machine Learning, NLP, Open AI, LangChain, Amazon BedRock, Prompt Engineering, Prompt Templates, RAG, Agentic AI, MCP, and LLMOps

Live Doubt Clarification Classes

Generative AI Interactive Q & A with AI Engineers: Weekly 2-3 Live Sessions to Resolve Your Doubts and Enhance Learning

Experience Building Course on Gen AI & Agentic AI for Managers

Cohort Start Date

16th Feb, 2025

Live Class Timing(Mon-Fri)

9:30 PM - 11:00 PM(IST)

Time Commitment

12Hrs/Week

Program Duration

3 Months

Learning Format

Live Classes

AI Course for Managers

100% Hands-On Syllabus on AI for Managers with Case Studies and Portfolio

Introduction to Deep Learning, Tensorflow & Feed Forward Neural Networks

Building Blocks of Artificial Neural Networks

What are Optimisers and Types of Optimisers

Math Behind Feed Forward Neural Network

Math Behind BackPropagation

Why Activation Functions & Importance

Introduction to Tensorflow

FFNN-Regression Script using Tensorflow

FFNN – Classification Script Using Tensorflow

Feed Forward Neural Network Coding

Lecture-5

Lecture-6

Back Propagation

Feed Forward Script Explanation

Introduction to Tensorflow & Feed Forward Neural Network

Foundations of Generative AI

What is Generative AI? Applications and Industry Use-Cases

Evolution: GANs → VAEs → Transformers → Diffusion → LLMs → MoEs

Key Architectures: GPT, BERT, Diffusion, UNet, U-ViT

Metrics: FID, BLEU, ROUGE, perplexity, hallucination rate

Large Language Models (LLMs)

Anatomy of an LLM: Tokenizer → Embedding → Attention → Output Head

Latest LLM Models and Using Them

LLM Evaluation Benchmarks: SWE-bench, ARC, TruthfulQA, HELM

Mixture of Experiments, Context Window, Position Embedding, Memory Compression

Small Language Models (SLMs)

What are SLMs? (Efficient alternatives to LLMs)

Open-source SLMs: Phi-3, TinyLLaMA, Gemma Small, Mistral Small

When to use SLMs vs LLMs (cost, privacy, latency)

Fine-tuning & Quantization for Edge Deployment (QLoRA, GGUF)

Generative AI, Prompt Engineering using LangChains

What is Generative AI? Use cases in text, image, code, and conversation

Foundation Models: GPT, Claude, PaLM, Gemini, Mistral, LLaMA

Introduction to Lang Chains

Using LLMs using Lang Chains

What is Prompt Engineering

Prompt Engineering Principles

Zero-shot, Few-shot, Chain-of-Thought (CoT)

Best Way to Improve LLMs Accuracy

Doing Prompt Engineering using Lang Chains

PromptTemplate best practices with LangChain

Using ChatPromptTemplate, SystemMessagePrompt, HumanMessagePrompt

Prompt evaluation: temperature, top_p, stop, max_tokens

LangChain Framework

Overview of LangChain and Ecosystem

Components: Chains, Agents, Tools, Memory, Prompts

Integration with OpenAI, Anthropic, Cohere, HuggingFace

Use Cases: Doc Chatbot, PDF QA, RAG Chatbots, Tools-based Agents

Custom Chains and Agents

Amazon Bedrock & GenAI on Cloud

What is Amazon Bedrock?

Using Claude, Titan, and Meta Models via Bedrock

Prompt Chaining, Guardrails, Evaluators in Bedrock

Comparison with Vertex AI (Google), Azure AI Studio

Custom Fine-Tuning and Hosting on Bedrock

Retrieval-Augmented Generation (RAG) with LangChain

Why RAG? Token limits, context injection

Vector Embeddings: OpenAI, HuggingFace, Cohere

Vector DBs: FAISS, Pinecone, Chroma, Weaviate, Milvus

LangChain’s RetrievalQA Chain

Chunking strategies and TextSplitter

Hybrid search: Dense + Metadata filtering

SequentialChain vs SimpleSequentialChain

RunnablePassthrough, RunnableLambda (LCEL)

Creating Tool abstractions with @tool decorator

Integrating APIs (e.g., SerpAPI, Weather, Calculator)

Output parsers: StrOutputParser, StructuredOutputParser

Experience Building Course on
Gen AI & Agentic AI for Managers

Live Class Timing
(Mon-Fri)