Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Candidates looking for an undergraduate or postgraduate course in machine learning should enroll in the Introduction to Machine Learning program. It is an elective twelve-week course in the field of computer science and engineering, programming, artificial intelligence, and data science. A collaboration of IIT Madras and NPTEL, this course is an initiative by the Ministry of Education, Government of India, and is available on the learning platform Swayam.
Introduction to Machine Learning certification will be taught by professor Balaraman Ravindran. The syllabus includes various topics from the data-driven disciplines such as machine learning and analytics. Candidates will be introduced to different learning paradigms and some popular algorithms and architectures used in these paradigms.
Introduction to Machine Learning is an online free audit course that offers an e-certificate for interested participants. Candidates will attend the online lectures, and submit assignments periodically. There is also an optional offline examination for participants who want to achieve certification.
The Highlights
- Ministry of Education, Government of India initiative
- The elective course of 12 weeks
- IIT Madras educator
- A free online audit course
- Verifiable e-certificate available
- Undergraduate/postgraduate course in computer science and engineering, programming, artificial intelligence, and data science
- FDP course approved by AICTE
- Assignments and optional offline exam
- Books and reference for extra learning
Programme Offerings
- Free online audit course
- assignments
- Optional offline exam
- Undergraduate/Postgraduate Course
- Computer Science and Engineering
- Books And References
- elective course
- 12 weeks duration
- IIT Madras educator
- Verifiable e-certificate available
Courses and Certificate Fees
| Fees Informations | Certificate Availability | Certificate Providing Authority |
|---|---|---|
| INR 1000 | yes | IIT Madras (IITM) |
- Introduction to Machine Learning training MOOC is a free course. There is no enrollment fee. An exam fee of Rs 1,000 is applicable for participants who want to attempt the end-of-term examination.
Introduction to Machine Learning program fee structure
Course Name | Fee |
Introduction to Machine Learning (Exam fee) | Rs. 1,000 |
Eligibility Criteria
Interested candidates are encouraged to study up the basics of programming, linear algebra, and probability theory before joining the Introduction to Machine Learning program.
Certificate Qualifying Details
Participants of the course will have to submit all the assignments, appear for the final exam and get the minimum passing score in assignments, final exam, and final score to get an e-certificate for the course.
What you will learn
Introduction to Machine Learning program will cover the following topics:
- Mathematically well-founded introduction to machine learning
- Data analytics
- Algorithms and architecture in different learning paradigms
Who it is for
Introduction to Machine Learning is designed for undergraduate and postgraduate engineering students, MS students, and doctoral candidates.
Admission Details
Candidates can enrol in Introduction to Machine Learning by Swayam by following this step-by-step guideline:
- Go to the website https://onlinecourses.nptel.ac.in/noc23_cs98/preview on the Swayam learning platform and select the ‘Sign in/Register’ button on top of the page.
- Enter your credentials and sign in. If you are using Swayam for the first time, create an account by choosing a username and password and enter a valid email address.
- After the registration process is complete, fill up the online form and provide any documents that may be required.
- Next, pay the exam fee if you want to attempt the exam.
Once the payment is complete, your enrollment is complete, and you can start learning on the start date.
Application Details
Introduction to Machine Learning program has an online form. But it can only be accessed after the registration or login process is complete. To complete the registration process, individuals need to enter a valid email address and choose an unused username and password. They can also register using their Microsoft, Facebook, or Google account.
The Syllabus
- Linear algebra
- Probability theory
- Convex optimisation - (Recap)
Introduction: statistical decision theory
- Regression
- Bias Variance
- Classification
- Shrinkage methods
- Principal component regression
- Linear regression
- Partial least squares
- Multivariate regression
- Subset selection
- Linear classification
- Linear discriminant analysis
- Logistic regression
- Perceptron
- Support vector machines
Neural Networks
- Introduction
- Early Models
- Perceptron Learning
- Backpropagation
- Initialization
- Training & Validation
Parameter estimation
- MLE
- Bayesian estimation
- MAP
- Decision Trees
- Regression Trees
- Stopping Criterion & Pruning loss functions
- Categorical Attributes
- Multiway Splits
- Missing Values
- Decision Trees
- Instability Evaluation Measures
- Bootstrapping & Cross Validation
- Class Evaluation Measures
- ROC curve
- MDL
- Ensemble Methods
- Bagging
- Committee Machines
- Stacking
- Boosting
- Gradient Boosting
- Random Forests
- Multi-class Classification
- Naive Bayes
- Bayesian Networks
- Undirected Graphical Models
- HMM
- Variable Elimination
- Belief Propagation
- Partitional Clustering
- Hierarchical Clustering
- Birch Algorithm
- CURE Algorithm
- Density-based Clustering
- Gaussian Mixture Models
- Expectation Maximization
- Learning Theory
- Introduction to Reinforcement Learning
- Optional videos (RL framework, TD learning, Solution Methods, Applications)
Evaluation process
While Introduction to Machine Learning training has an online exam, it is not the only criteria to achieve certification. Participants need to submit all the assignments and get the minimum passing score in the final exam and assignments.
A final score will be calculated based on 25% of the assignment marks and 75% of the exam marks. The final passing score is 40/100. Only candidates who score 10/25 and above in assignments and 30/75 and above in the exam in addition to the passing score will be awarded the certificate.
Instructors
IIT Madras (IITM) Frequently Asked Questions (FAQ's)
Yes, Introduction to Machine Learning is a 100% digital program.
Yes. The first step of the admission process is to register or login into the Swayam website.
Yes. The educator of this course is professor Balaraman Ravindran from IIT Madras.
No. Candidates can access the course for free.
No, the offline exam will be proctored.