9 Best NPTEL Machine Learning Courses

This article contains a list of the top 9 NPTEL Machine Learning online courses, MOOCs, classes, and specialization by NPTEL. The NPTEL Machine Learning courses available are suitable for any type of learner be it a beginner, intermediate or professional. So check out this list and find the most suitable course for yourself.

National Programme on Technology Enhanced Learning is a project that is being handled by the seven Indian Institutes of Technology. The program is to be used as a core curriculum content for training purposes and aims to provide a variety of courses in the field of Engineering and Core Sciences. Also, they have introduced a variety of Machine Learning Nptel courses in different disciplines that are suitable for all types of learners to take.

NPTEL Machine Learning Courses:

NPTEL along with providing a variety of online courses, certifications, specialization, and MOOCs in different fields has also managed to introduce NPTEL Machine Learning courses. Those who are interested in learning the fundamentals, the logic, it’s working in short everything about these courses are welcome to join in any of the courses.

Machine Learning

• • • Stanford University via Coursera
    • 64 hours of effort required
    • 2,975,908+ students enrolled
    • ★★★★★ (129,908 Ratings)

Introduction to Machine Learning

• • • Prof. Sudeshna Sarkar via NPTEL
    • Co-ordinated by: IIT Kharagpur
    • 8 Weeks duration
    • Discipline: Computer Science and Engineering

This Introduction to Machine Learning Nptel Machine Learning course covers extensive knowledge of Machine Learning. Sudeshna Sarkar, the Head of the Department of Computer Science and Engineering at IIT Kharagpur, has carefully formatted the syllabus of this Introduction to Machine Learning course. A major focus of this course will be fundamental concepts in Machine Learning and popular machine learning algorithms. It also covers the standard and most popular supervised learning algorithms including linear regression, logistic regression, decision trees, k-nearest neighbor, etc. By the end of this Introduction to Machine Learning Nptel Machine Learning course, you will have in-depth knowledge about Bayesian learning and the naïve Bayes algorithm, support vector machines, basic clustering algorithms, and a lot more.

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Machine Learning

• • • Prof. Carl Gustaf Jansson via NPTEL
    • Co-ordinated by: IIT Madras
    • 8 Weeks duration
    • Discipline: Computer Science and Engineering

Want to learn about Artificial Intelligence (AI) and how it is affecting our industries? Then this course is perfect for you. Prof. Carl Gustaf teaches how the scientific discipline of Machine Learning is focusing on the development of an algorithm for finding patterns or making predictions from empirical data. Know how Artificial Intelligence is frequently utilized by many professions and industries to optimize processes and implement adaptive systems. This Nptel Machine Learning course will also help you in acquiring techniques such as decision tree-based inductive learning, inductive logic programming, and reinforcement learning, etc. If you’re interested to enroll for a machine learning course from top organizations and universities like Google, New York University, Stanford, Harvard and others, please follow here.

Introduction to Machine Learning (Course sponsored by Aricent)

• • • Dr. Balaraman Ravindran via NPTEL
    • Co-ordinated by: IIT Madras
    • Self-Paced
    • Discipline: Computer Science and Engineering

This Nptel Machine Learning course would be valued by any company in the data analytics, data science, and big data domain. Learn the basic concepts of machine learning along with the various data-driven disciplines such as analytics. Furthermore, in this Nptel Machine Learning course, Professor Balaraman Ravindran will cover the different learning paradigms and some of the more popular algorithms and architectures used in each of these paradigms. At the end of this Nptel Machine Learning course, you will have comprehensive knowledge about linear regression, multivariate regression, early models, perceptron learning, partitional clustering, hierarchical clustering, and a lot more. Enroll yourself now and learn from a mathematically well-motivated perspective.

Practical Machine Learning with Tensorflow

• • • Prof. Ashish Tendulkar via NPTEL
    • Co-ordinated by: IIT Madras
    • 8 Weeks Duration
    • Discipline: Computer Science and Engineering

For those of you who want to learn about Machine Learning using TensorFlow, then this course might grasp your attention. With this Nptel Machine Learning course, you can cover the basics of TensorFlow and Machine Learning. This course syllabus has been formulated by Prof. Balaraman Ravindran, an associate professor in Computer Science at IIT Madras, and Mr. Ashish Tendulkar, an experienced AI/ML professional. Get an overview of machine learning Nptel, data input, preprocessing with TensorFlow, and machine learning Nptel model building. Moreover, with this course, you’ll gain information about advance TensorFlow, hardware accelerators, monitoring and evaluating models using the Tensor board, etc. After this Nptel Machine Learning course, you will be able to build ML models using TensorFlow.

Machine Learning for Engineering and Science Applications

• • • Prof. Ganapathy & Prof. Balaji Srinivasan via NPTEL
    • Co-ordinated by: IIT Madras
    • 12 Weeks Duration
    • Discipline: Computer Science and Engineering

Through this  Machine Learning Nptel, the course learns about Functional Programming. In this Nptel Machine Learning course, you can study Haskell and how its programming features are being used for both building rapid prototypes and actual deployment. Prof. Balaji Srinivasan and Prof. Ganapathy Krishnamurthi will help you in understanding linear algebra, probability, numerical computation, and optimization, etc. Plus, learn about linear and logistic regression, neural networks, convolutional neural networks, and recurrent neural networks. In the end, you’ll have all of the classical techniques regarding Bayesian regression, binary trees, k-Means, KNN, GMM, etc. Similarly, you’ll havhttps://www.https://www.takethiscourse.net/online-specializations/e all of the advanced techniques regarding structured probabilistic models, Monte Carlo methods, autoencoders, and generative adversarial networks. Checkout online engineering courses.

Essential Mathematics for Machine Learning

• • • Dr. S. K. Gupta & Dr. Sanjeev Kumar via NPTEL
    • Co-ordinated by: IIT Roorkee
    • 08 Weeks Duration
    • Discipline: Mathematics

This essential mathematics for the Nptel machine learning course contains a variety of video lectures it that has everything explained in a step-by-step guide. The whole course has been divided into different weeks and completing each week will enhance your mathematics skills for machine learning. The course starts with a thorough introduction to the course and then you will get to know about vectors. After that, you will get to learn the definitions and examples of vector spaces, and then the properties, basics, and dimensions of vector subspaces will be discussed. Similarly, going further, you will learn about linear transformations in detail. Next, you will be taught what orthogonal complements and projection operators are. Thus this and many other topics will be taught in this course. you can also find out the comparison between Deep Learning Vs Machine Learning.

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Applied Optimization for Wireless, Machine Learning, Big Data

• • • Prof. Aditya K. Jagannatham via NPTEL
    • Co-ordinated by: IIT Kanpur
    • 12 Weeks Duration
    • Discipline: Electrical Engineering

This course is a complete introduction to the properties of vectors, norms, positive semi-definite matrices, and Gaussian random vectors. When you start the Nptel Machine Learning course, you will first understand what vector and matrices, linear independence, and rank are. Similarly, the next lecture video will be about Eigenvectors and Eigenvalues of matrices and their properties. Going further, you will be taught all about what positive semidefinite and positive definite matrices are and their properties in detail. After that, you will learn about the inner product space and its properties. Other topics like properties of norm, linearity, symmetry, and more will be discussed in detail. Checkout comparison between big data and data mining by click here.

ACM Summer School on Algorithmic and Theoretical Aspects of Machine Learning, 2019 – Bangalore

• • • Meenakshi D’Souza via NPTEL
    • Co-ordinated by: IIT Madras
    • 08 Weeks Duration
    • Discipline: Special Series

A unique, engaging, and yet challenging course that will help you develop an understanding of finite state automata and decision sessions. The NPTEL Machine Learning course has such type of video lectures in it that can help you understand all the theoretical and algorithmic aspects of machine learning in detail. After that, the course has almost 10 video lectures in probability where you will get to know all the technicalities and concepts involved in probability. Similarly, there will be 3 sessions on Algebra for machine learning where the instructor of the Nptel Machine Learning course has explained every single concept of algebra relevant to machine learning Nptel in detail. After that, you will learn about cryptography and machine learning. Then, the next topic will be a neural network, then you will learn about the enterprise applications of ML and more. You might also be interested in

Bandit Algorithm (Online Machine Learning)

• • • Prof. Manjesh hanawal via NPTEL
    • Co-ordinated by: IIT Bombay
    • 10 Weeks Duration
    • Discipline: Computer Science and Engineering

This Nptel Machine Learning course has a complete introduction to what the bandit algorithm is and all its technicalities and concepts have been explained in detail. Machine Learning Nptel course is covered in a variety of weeks in the form of video lectures and starts with a thorough introduction to online learning. Next, you will understand the basics of statistical learning. Similarly, what is empirical risk minimization will also be taught in detail. Moving forward, you will understand all about the consistency halving algorithm. Other topics like online learnability, standard optimal algorithm, weighted majority, adversarial bandit setting, and regret bound of Exp3, and many more will be taught in detail as well. So enroll now in this informational course and start learning today. If you have interest in machines, you might consider looking into NPTEL mechanical engineering courses.

Deep Learning Specialization

• • • deeplearning.ai via Coursera
    • 96 hours of effort required
    • 305,958+ students enrolled
    • ★★★★★ (202,442 Ratings)

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

• • • deeplearning.ai via Coursera
    • 125,592+ students enrolled
    • ★★★★★ (6,449 Ratings)
    • This course is part of the TensorFlow in Practice Specialization

IBM AI Engineering Professional Certificate

• • • IBM via Coursera
    • 128 hours of effort required
    • 11,497+ students enrolled
    • ★★★★☆ (8,314 Ratings)

Further, you can check out nptel online courses for computer sciences. So take any of the courses now and never stop learning.