IIT Madras has recently launched five free online courses for Computer Science (CS) students through the SWAYAM platform, making high-quality education accessible to all. This initiative aligns with IIT Madras’s commitment to providing excellent educational resources and opportunities for learners across India, especially in the field of computer science and engineering.
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About the IIT Madras
Indian Institute of Technology Madras (IIT Madras or IIT-M) is a public technical university located in Chennai, Tamil Nadu, India. It is one of the eight public Institutes of Eminence of India. As an Indian Institute of Technology (IIT), IIT Madras is also recognized as an Institute of National Importance.
Founded in 1959 with technical, academic, and financial assistance from the then government of West Germany, IITM was the third Indian Institute of Technology established by the Government of India. IIT Madras has consistently ranked as the best engineering institute in India by the Ministry of Education’s National Institutional Ranking Framework since the ranking’s inception in 2016.
In 1956, the West German Government rendered technical assistance to establish a state-of-the-art engineering institute in India. Soon, the first Indo-German agreement was signed in Bonn, West Germany in 1959 for the establishment of the Indian Institute of Technology in Madras (now Chennai).
IIT Madras was started with technical, academic, and financial assistance from the Government of West Germany and was at the time the largest international educational project sponsored by the West German government. The Government of the Federal Republic of Germany has agreed to provide the following assistance in the establishment of a higher technological institute at Madras:
Eligibility Criteria
IIT Madras Launched 5 Free Online Courses for CS Students.
Here are 5 Free Online Courses of IIT Madras
1. Introduction To Machine Learning – IITKGP
This course provides a concise introduction to the fundamental concepts in machine learning and popular machine learning algorithms. We will cover the standard and most popular supervised learning algorithms including linear regression, logistic regression, decision trees, k-nearest neighbour, an introduction to Bayesian learning and the naïve Bayes algorithm, support vector machines and kernels and neural networks with an introduction to Deep Learning.
We will also cover the basic clustering algorithms. Feature reduction methods will also be discussed. We will introduce the basics of computational learning theory. In the course we will discuss various issues related to the application of machine learning algorithms.
We will discuss hypothesis space, overfitting, bias and variance, tradeoffs between representational power and learnability, evaluation strategies and cross-validation. The course will be accompanied by hands-on problem solving with programming in Python and some tutorial sessions.
Course Link Click Here
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2.Big Data Computing
In today’s fast-paced digital world , the incredible amount of data being generated every minute has grown tremendously from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and GPS signals from cell phone to name a few.
This amount of large data with different velocities and varieties is termed as big data and its analytics enables professionals to convert extensive data through statistical and quantitative analysis into powerful insights that can drive efficient decisions.
Course Link Click Here
3. Demystifying networking
This course will provide students with an overview of networking concepts and technologies. It is meant as a primer for non-majors, i.e., for students who don’t have networking as a core course in their curriculum. After this primer, students may choose to take other networking courses for delving deeper into specific technologies.
Course Link Click Here
4.Python for Data Science
The course aims at equipping participants to be able to use python programming for solving data science problems.
Course Link Click Here
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5.C Programming and Assembly Language
Students who complete their bachelors degree (BE/ BTech) in computer science or electrical engineering do extensive course work in Microprocessors and then in C programming. However, what is missing in the current curriculum is to explicitly establish the link between the two. Specifically we look at how a C program is translated to assembly language and how it eventually gets executed on a microprocessor. Through, animations we show what happens in the stack, data and code segment, of the microprocessor when a C program is executed.
Course Link Click Here
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