Module 1: Python for AI

• Python Basics I
• Python Basics II
• Introduction to NumPy & Pandas
• Data Preprocessing & Manipulation
• Data Visualization

Module 2: Predictive Analysis

• Statistical Foundations
• Probablity, Inferential Statistics
• Regression

Module 3: Introduction to Machine Learning

• Supervised Learning - Classification
• Supervised Learning - Classification II
• Unsupervised Learning - Clustering
• Recommendation System
• ML Deployment in Cloud

Module 4: ML

• Introduction to Machine Learning
• Supervised Learning - Classification
• Supervised Learning - Classification II
• Unsupervised Learning - Clustering
• Recommendation System
• ML Deployment in Cloud

Module 5: DL

• Introduction to Deep Learning
• Getting started with Tensorflow 2.0 with Tensor Board
• Image Classification using CNN
• TensorFlow Hub for Object Detection using Faster RCNN
• Tensorflow for Deployment
• Real-time object detection using YOLO v4
• Image Segmentation using Facebook Detectron 2.0
• Data Tagging(VOTT) for Computer Vision

Module 6: Natural Language Processing

• Introduction to NLP with Spacy
• Analyzing and Seggregating the News Headlines
• Building a Resume Classifier
• Building a intent based
• RASA Chatbot
• NLP in Production
• Doubt Clearing Session + End Course Test

Module 7: Sequence Learning

• Introduction to Sequence Learning
• RNN vs LSTM with Google Stock Price
• Sentiment Analysis on Zomato Reviews using LSTM
• Introduction to Transformer model
• BERT and GPT2 using Transformer
• Machine Translation with MT5 (Self-paced)
• Building a Question Answer prediction model using BERT (Self-paced)

Module 8: Project Work & Documentation