AI & ML Training in Bangalore

Pre Program preparatory content (1 Week)

• Introduction to Python
• Python for Data Science
• Data Visualization in Python
• Data Analysis Using SQL (Optional)
• Advanced SQL and Best Practices (Optional)
• Data Analysis in Excel
• Analytics Problem Solving
• Math for Machine Learning

Statistics & Exploratory Data Analytics (2 Weeks)

• Exploratory Data Analysis
• Cloud Essentials: Intro to Git & GitHub
• Inferential Statistics
• Hypothesis Testing
• Lending Club Case Study

Machine Learning – I

• Linear Regression
• Assignment
• Logistic Regression
• Naive Bayes
• Model Selection

Machine Learning – II

• Advanced Regression
• Advanced Regression Assignment
• Support Vector Machine (Optional)
• Tree Models
• Model Selection – Practical Considerations
• Boosting
• Unsupervised learning: Clustering
• Unsupervised Learning: Principal Component Analysis

Deep Learning

• Introduction to Neural Networks
• Convolutional Neural Networks – Industry Applications
• Convolutional Neural Networks – Assignment
• Recurrent Neural Networks
• Neural Network Project – Gesture Recognition

Natural Language Processing

• Lexical Processing
• Syntactical Processing
• Syntactic Processing – Assignment
• Semantic Processing
• Case Study: Classifying Customer Complaint Tickets

AI Strategy (Elective)

• Cloud Essentials: Intro to AWS
• Working with AWS: case study
• MLOps: Introduction
• MLOps: Data Lifecycle
• MLOps: Model Lifecycle
• AI Strategy Framework, Structured Problem Solving/ Data Storytelling
• Mapping ML with Data architecture strategy

Capstone

• News Recommended System
• Credit Card Fraud Detection
• Eye for Blind – (Image Captioning)
• Sentiment analysis based Product Recommender system
• Sales forecasting
• Style Transfer using GAN’s

Reinforcement Learning (Elective)

• Classical Reinforcement Learning
• Assignment -Classical Reinforcement Learning
• Deep Reinforcement Learning
• Reinforcement Learning Project