Free Online Course on Machine Learning Offered by IIT Kharagpur

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IIT Kharagpur has recently announced a free online course on machine learning that is open for applicants. Named Introduction to Machine Learning, the program offers a concise overview of the fundamental principles of machine learning and explains the algorithms applied in the field.

The course will be delivered on the NPTEL platform and includes an introduction to the most popular supervised learning algorithms such as k-nearest neighbor, decision trees, linear regression, logistic regression, as well as a brief background on Bayesian learning and the naive Bayes algorithm. Additionally, participants will have hands-on problem-solving opportunities that involve programming in Python, as well as some tutorial sessions.

The course will be headed by Sudeshna Sarkar, a professor and current Head of the Department of Computer Science and Engineering at IIT Kharagpur. The course fees include a certificate of completion and two credit points upon clearing an exam and paying Rs 1000.

Course takers can expect to gain insight into several topics, including issues surrounding machine learning algorithms, overfitting, hypothesis space, bias and variance, tradeoffs between representational power and learnability, evaluation strategies, and cross-validation.

The program begins on July 24, 2023, and ends on September 15, 2023, with registration open until July 31, 2023. Those who wish to take the exam must register by August 18, 2023, with the exam scheduled for Indian Standard Time on September 24, 2023. Anyone interested in learning more about the online course can visit the official website for additional information.

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Frequently Asked Questions (FAQs) Related to the Above News

What is the name of the free online course on machine learning offered by IIT Kharagpur?

The name of the free online course on machine learning offered by IIT Kharagpur is Introduction to Machine Learning.

What is included in the course curriculum?

The course curriculum includes an introduction to the most popular supervised learning algorithms such as k-nearest neighbor, decision trees, linear regression, logistic regression, as well as a brief background on Bayesian learning and the naive Bayes algorithm. Additionally, participants will have hands-on problem-solving opportunities that involve programming in Python, as well as some tutorial sessions.

Who will be heading the course?

The course will be headed by Sudeshna Sarkar, a professor and current Head of the Department of Computer Science and Engineering at IIT Kharagpur.

Is there a fee to register for the course?

No, the course is free to register for.

Is there a certificate of completion offered for the course?

Yes, a certificate of completion is offered upon clearing an exam and paying Rs 1000.

What topics can course takers expect to gain insight into?

Course takers can expect to gain insight into several topics, including issues surrounding machine learning algorithms, overfitting, hypothesis space, bias and variance, tradeoffs between representational power and learnability, evaluation strategies, and cross-validation.

When does the program begin and end?

The program begins on July 24, 2023, and ends on September 15, 2023.

When is registration open until?

Registration is open until July 31, 2023.

When is the exam scheduled for those who wish to take it?

The exam is scheduled for Indian Standard Time on September 24, 2023.

Where can I find additional information about the online course?

Anyone interested in learning more about the online course can visit the official website for additional information.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

Kunal Joshi
Kunal Joshi
Meet Kunal, our insightful writer and manager for the Machine Learning category. Kunal's expertise in machine learning algorithms and applications allows him to provide a deep understanding of this dynamic field. Through his articles, he explores the latest trends, algorithms, and real-world applications of machine learning, making it accessible to all.

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