Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study, Virtual Classroom	Video and Text Based

Course Overview

The Executive PG Programme in Machine Learning & AI is a year-long course. It will help you expand your knowledge of ML and AI through classes from IIIT Bangalore. There are nearly 20 programming languages, tools, and libraries, including NumPy, Pandas, NLTK, matplotlib, and more covered by the course. You are sure to develop skills in Reinforcement Learning, NLP, and Deep Learning.

The course pedagogy for the Machine Learning and AI online course will involve lectures from industry experts. Your classes will be conducted online, and you will be a part of numerous industry projects throughout the course. Additionally, the course has been designed for working professions and thus has an industry-oriented approach to learning. Besides, you can join the course without giving up your job since it offers a flexible experience.

Finishing the Machine Learning and AI programme will grant you IIIT B alumni status. The course will also allow you to attend profile-building workshops. Most importantly, you will earn a certificate and will be able to build your career with new opportunities.

The Highlights

12-month course
Online classes
IIIT B alumni status
Case studies
Assignments
Profile building workshops
Certificate upon completion
450+ hours of content
Industry oriented
Career mentor
Placement assistance
Capstone projects
20 Programming Languages covered

Programme Offerings

online learning
assignments
Case Studies
Projects
Coding classes
Capstone Projects
Profile Building Workshops
Mentoring
Certificate
IIIT alumni status
programming languages

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	IIIT Bangalore

The fees for the Machine Learning and AI certificate course will be payable after you receive your offer letter.

Programme Name	Amount
Executive PG Programme in Machine Learning & AI	Rs. 3,40,000/-
EMI	Rs. 7,500/month

Eligibility Criteria

To join the Machine Learning and AI course, you must have a Bachelor’s degree with a minimum of 50% marks. Additionally, you must have one year of working experience or a degree in Statistics or Mathematics.

Certificate qualifying details

By completing all the course content and assessments, you’ll be eligible for the IIIT B recognition.

What you will learn

Knowledge of deep learningData science knowledgeMachine learningNatural Language Processing

After completing the Operation Theatre Technician syllabus, you will have a thorough knowledge of topics such as:

Aspects of Machine Learning
Aspects of Deep Learning
Natural Language Processing
Statistical and Exploratory Data Analytics
Deployment and Capstone Projects
Data Science Toolkit
Reinforcement Learning

Who it is for

The Machine Learning and AI programme is aimed at working professionals looking for career growth and career transition in Programming.

Admission Details

Step 1: Visit https://www.upgrad.com/machine-learning-ai-pgd-iiitb/ to start your application process for the Machine Learning and AI PGP.

Step 2: Clear the online Eligibility Test. This will be a 40-minute test with 18 questions. It will determine whether you are ready to take on the programme.

Step 3: If you clear the Eligibility Test, you will be sent an Offer Letter.

Step 4: Accept the Offer Letter and make an initial payment of Rs. 25,000 to confirm your admission.

Application Details

The Machine Learning and Artificial Intelligence course have an application form that can be accessed on the programme’s webpage. To apply, enter your email id or contact number and select the Start Application tab.

The Syllabus

Conditional Probability and Probability Distributions
Advanced Linear Algebra and Linear Transformations
Multivariate Calculus
GenAI for Coding and Problem-Solving
Object-Oriented Programming
Python Data Science Libraries
Database Design and SQL Querying
Introduction to NoSQL Databases
Version Control

Data Analysis with Python
Exploratory Data Analysis
Inferential Statistics and Hypothesis Testing

Cloud Computing with AWS / GCP / Microsoft Azure
Big Data Analysis with PySpark

Machine Learning Paradigms
Linear and Logistic Regression
K Nearest Neighbors
Regularisation and Hyperparameter Tuning
Decision Trees and Ensembles
Clustering Models

Deep Learning Fundamentals
Convolutional and Recurrent Neural Networks
Lexical / Syntactic / Semantic Processing

Support Vector Machines
Naive Bayes
Feature Engineering and Model Selection
Dimensionality Reduction
Time Series Analysis
Association Rule Mining
Recommendation Systems
Explainable AI
Advanced CNN Architectures
LSTMs and GRUs
Transfer Learning Techniques
Encoder-Decoder Architectures and Seq2Seq
Machine Translation
Attention Mechanisms and Transformers
Fundamentals of Generative AI and Prompt Engineering
Computer Vision
Variational Autoencoders
Generative Adversarial Networks
Data and Model Security Principles
End-to-End Data Pipelining Fundamentals
Pipeline Automation with AWS Lambda
GCP Functions and Azure Automation
Data Monitoring with Amazon CloudWatch
Google Cloud Monitoring and Azure Monitor
Feature Stores and Vector Databases
Real-Time Processing with Flink and Kafka
Real-Time Analytics with Spark Streaming
Real-Time Analytics with Amazon Kinesis
Google Cloud Pub/Sub and DataFlow
Azure Stream Analytics and Event Hubs
Multicloud and Hybrid Cloud Operating Principles
Scala
Data Build Tool (DBT)
Azure Data Factory
Model Pipelining Principles
Scheduling and Triggers
Parallel Model Training and Real-Time Model Serving
Data Versioning and Model Versioning
Model Monitoring and System Design

Support Vector Machines
Naive Bayes
Feature Engineering and Model Selection
Dimensionality Reduction
Time Series Analysis
Association Rule Mining
Recommendation Systems
Explainable AI
Advanced CNN Architectures
LSTMs and GRUs
Transfer Learning Techniques
Encoder-Decoder Architectures and Seq2Seq
Machine Translation
Attention Mechanisms and Transformers
Fundamentals of Generative AI and Prompt Engineering
Computer Vision
Variational Autoencoders
Generative Adversarial Networks
Data and Model Security Principles
Advanced Prompt Engineering and GenAI System Design
Prompting Multimodal Models
LLM Frameworks such as LangChain and LLaMa Index
LLM Evaluation Methods
Data Security and Governance
AI Ethics
Information Retrieval Principles
Embeddings and Vector Databases
Retrieval-Augmented Generation (RAG) and RAG Architectures
Agentic Systems and Multi-Agent Systems
Advanced Multimodal GenAI Models
LLM Deployment
Advanced Computer Vision and 3D Vision
GenAI Optimisations
AI Ethics
Building an LLM from End-to-End

Instructors

IIIT Bangalore Frequently Asked Questions (FAQ's)

1: What is the refund policy for the Machine Learning and AI programme?

You can cancel your admission and request a refund before the course commences to the Admissions Counsellor. Your refund will be processed in 30 working days but a processing fee of Rs. 10,000 will be levied.

2: Is taking the eligibility test compulsory?

If you have a degree in Mathematics or Statistics, you do not need to take the eligibility test for the Machine Learning and AI course.

3: Which certificate will I receive at the end of the course?

After completing the Machine Learning and AI programme, you will receive an Executive PG Programme in Machine Learning & AI certificate from IIIT Bangalore.

4: What time is the Student Support available?

The Student Support for the Machine Learning and AI certification is available on all days from 9:00 am to 9:00 pm, IST.

5: What is the recommended learning time for the Machine Learning and AI course?

You are recommended to devote 15 hours of study to the Machine Learning and AI course per week.