IIIT Bangalore - Executive PG Programme in Machine Learning & AI
- Offered byupGrad
- Private Institute
- Estd. 2015
Executive PG Programme in Machine Learning & AI at upGrad Overview
Duration | 13 months |
Total fee | ₹3.35 Lakh |
Mode of learning | Online |
Credential | Certificate |
Executive PG Programme in Machine Learning & AI at upGrad Highlights
- Earn a certificate and alumni status from IIIT Bangalore
- EMI options available
- 25+ Mentorship Sessions from Industry Expert
- Learn from 15+ Case Studies and Assignments
- 6 Hands-on Capstone Projects for practical exposure
- Get resume feedback, job assistance, and interview preparation
- Networking opportunities with an alumni pool of 10,000+ keen professionals
Executive PG Programme in Machine Learning & AI at upGrad Course details
- Engineers, Software and IT Professionals, Data Professionals
- Python for Data Science
- Exploratory Data Analysis
- Linear Regression
- Tree Models
- Convolutional Neural Networks - Industry Applications
- Syntactical Processing
- Cloud Essentials: Intro to AWS
- This programme intends to produce extremely well-rounded data scientists and AI professionals with deep knowledge of mathematics, expertise in relevant tools/languages, and understanding of cutting-edge algorithms and applications. Will help learners familiarise with the advancements in ML and AI and also help understand the mathematics behind algorithms and how you can modify them to suit your needs so that you can transition to a Senior Data Science or Machine Learning role.
Executive PG Programme in Machine Learning & AI at upGrad Curriculum
Pre-Program Preparatory Content
Introduction to Python
Python for Data Science
Data Visualisation in Python
Data Analysis Using SQL (Optional)
Advanced SQL and Best Practices (Optional)
Data Analysis in Excel (Optional)
Analytics Problem Solving (Optional)
Math for Machine Learning
Statistics and Exploratory Data Analytics
Exploratory Data Analysis
Cloud Essentials: Intro to Git & Cloud
Investment Assignment
Inferential Statistics
Hypothesis Testing
Lending Club Case Study
Machine Learning - I
Linear Regression
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
Telecom Churn Case Study
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
Elective 1: DL with MLops
Cloud Essentials: Intro to AWS
Working with AWS: case study
MLOps: Introduction
MLOps: Data Lifecycle
MLOps: Model Lifecycle
MLops Assignment
Advanced CV
Advanced CV
MLOps + Deployment: DL (Theory)
MLOps + Deployment: DL (assignment)
Elective 2: NLP with Mlops
Cloud Essentials: Intro to AWS
Working with AWS: case study
MLOps: Introduction
MLOps: Data Lifecycle
MLOps: Model Lifecycle
MLops Assignment
Advanced NLP
Advanced NLP
MLOps + Deployment: NLP (Theory)
MLOps + Deployment: NLP (assignment)
Elective 3: AI strategy
Cloud Essentials: Intro to AWS
Working with AWS: case study
MLOps: Introduction
MLOps: Data Lifecycle
MLOps: Model Lifecycle
MLops Assignment
AI Strategy Framework, Structured Problem Solving/ Data Storytelling
Mapping ML with Data architecture strategy
Executing AI Strategy
AI strategy: Assignment
Capstone
Reinforcement Learning (Optional)
Classical Reinforcement Learning
Assignment -Classical Reinforcement Learning
Deep Reinforcement Learning
Reinforcement Learning Project