# Lesson Plan

course: Academic Information
module: Academic-Information
type: pdf
source_url: https://personal-learn.armco.dev/files/Academic-Information/General/Lesson_Plan.pdf
pages: 3

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[page 1]
Session MODULE TOPICS
Week 1 0 Orientation Introduction to the Course and Team
Week 1 0 Academic Orientation Academic Orientation
Week2 1
Foundations of AI and ML
Introduction to AI & ML
Week 2 2 Data Pre-Processing and Curation – I (Handling missing values)
Week 3 3
Data Pre-Processing and Curation – II (Data Curation, Feature Engineering, 
PCA, EDA)
Week 3 4
Data Pre-Processing and Curation – III (Dimensionality Reduction, Feature 
Selection, Data Compression and Reduction, Similarity Measures)
Week 4 5
Exploratory Data Analysis (EDA)- Different types of plots like Box Plots, Violin 
Plots, Heatmaps, Histograms etc.
Week 4 6
Machine Learning Algorithms
Introduction to Supervised Learning- Decision Trees → Random Forests
Week 5 7 Classification Foundations: Similarity, Metrics & Model Evaluation
Week 5 8 ML Algorithms - Supervised Learning I - Hands On Session
Week 6 9
ML Algorithms - I, Supervised Learning- kNN, Naïve Bayes' Classifier, SSE, MAE, 
MSE, k-fold cross validation
Week 6 10 Classification - Hands On Session
Week 7 11 Regression Fundamentals
Week 7 12 Regression - Hands On Session
Week 8 13 ML Algorithms - II, Unsupervised Learning - Clustering, k-Means Clustering
Week 8 14
Regularization: L1 and L2, Lasso and Ridge Regularization and Cluster 
Validation
Week 9 15 Clustering- K-Means Clustering: Hands On
Week 9 16 Lasso and Ridge Regularization: Hands - On Session
Week 10 17
Deep Learning and NLP
Introduction to Deep Learning
Week 10 18 Introduction to Deep Learning-II
Week 11 19 Deep Learning: Hands On -Session
Week 11 20 Deep Learning: Hands On -Session
Week 12 21 Deep Learning
Week 12 22 Back Propagation Demystified
Week 13 23 CNN Theory
Week 13 24 CNN: Hands On Session
Week 14 25 RNN Theory
Week 14 26 RNN: Hands On Session
Week 15 27 LSTM Theory
Week 15 28 LSTM: Hands On Session

[page 2]
Week 16 29
Deep Learning and NLP
Introduction to Text Data
Week 16 30 Text Data: Hands On Session
Week 17 31 Word2Vec Model
Week 17 32
Generative AI and Large Language Models
Transformers Part 1
Week 18 33 Word2vec: Hands On Session
Week 18 34 Transformers Part 2
Week 19 35 Encoder Decoder: Hands On Session
Week 19 36 Encoder Decoder with Attention: Hands On Session
Week 20 37 Transformer+handson
Week 20 38 Transformer+handson
Week 21 39  
Week 21 40 Bert: Hands On Session
Week 22 41 GPT Theory
Week 22 42 GPT Theory contd. And T5 
Week 23 43 T5 Theory
Week 23 44 T5: Hands On Session
Week 24 45 Introduction to RAG
Week 24 46 Introduction to RAG
Week 25 47 Project and Exam Discussion
Week 26 48 Intro to VAE and GAN
Week 27 49 Applications and Hands-on
Week 28 50
AI Agents
Introduction to AI Agents and different types of Agents - Best Practices with AI 
Agents
Week 29 51 Exploring LLM Agents and AI Agents
Week 30 52 Understanding A2A and MCP in Agents
Week 31 53 Learning Agentic Frameworks
Week 32 54 Building Agents using LangChain
Week 33 55 Building Agents using LangGraph - Part 1
Week 34 56 Building Agents using LangGraph - Part 2
Week 35 57 Building Agents using LangGraph - Part 3
Week 36 58
AI Agents Development
Building Agents using Smolagents 
Week 37 59 Exploring Multi-Agent Systems and Understanding Agentic Evaluation
Week 38 60 Orchestration in Multi-Agent System
Week 39 61 Types of Orchestration and Agentic RAG Systems 
Week 40 62 Monitoring and Governance of Multi-Agent System
Week 41 63 Understanding Microsoft AutoGen - Part 1

[page 3]
Week 42 64
AI Agents Development
Understanding Microsoft AutoGen - Part 2
Week 43 65 Understanding Crew AI
Week 44 66 Debugging and Troubleshooting Agents
Week 45 67
Advanced Agentic AI
Agentic RAG Systems with LangGraph - Mini Project
Week 46 68 Agentic RAG Systems with LangGraph - Mini Project
Week 47 69 Agent Collaboration in LangGraph
Week 48 70 Developing Domain specific Agents Developing Customer Support Agent
Week 49 71 Developing Agents that automate productivity and planning Adoption of AI Agents Across Industries
Week 50 72 Developing Agents that automate productivity and planning Developing meeting planner Agent 
Week 51 73 Data, Research and EDA Agents Multi-Model Analysis Agent
Week 52 74 Lab Logging, Monitoring & Analytics for AI Agents
Week 53 75  Open Source Agent Frameworks (AutoGen vs CrewAI vs LangGraph) Case Study Analysis: Comparing Open Source Agent Frameworks (AutoGen vs 
CrewAI vs LangGraph)
Week 54 76 Exam Preparation
Week 55 77 Written Exam 
Week 56 78
Advanced Topics and Specializations
GenAI Specializations & AI Agents for Engineers
Week 57 79 GenAI Specializations & AI Agents for Engineers
Week 58 78 GenAI Specializations & AI Agents for Engineers
Week 59 79 GenAI Specializations & AI Agents for Engineers
Week 60 Capstone Project