NIT Raipur Online Training Program on Advanced Machine Learning for Biosignal Data

NIT Raipur Online Training: NIT Raipur organizing an Online Training Program on Advanced Machine Learning for Biosignal Data. The detail eligibility and applying process given below in the article.

About NIT Raipur: National Institute of Technology Raipur (Formerly Government Engineering College Raipur), that’s situated in the capital of a newly incepted state of Chhattisgarh, has proven to be “Avant-grade’ in the field of science and technology over the past few decades in this region.With sweet memory of the foundation ceremony by our president Hon’ble Dr. Rajendra Prasad on 14th September 1956. the institute started with two departments namely Metallurgical and Mining Engineering. Later the inauguration of the Institute building was done by our Prime Minister Hon’ble Pt. Jawahar Lal Nehru on 14th March 1963. From 1st December 2005, the institute has become the National Institute of Technology.

NIT Raipur Online Training:

Course Objective
  • The aim of this virtual/ online training program is to provide exposure to both basics and recent advances in machine learning and their applications to biosignal data i.e. 1D, 2D (image), and 3D (video) medical data to the students, budding researchers from both academics and industry as well as faculty members.
  • People from both medical and engineering communities can get benefited from this program.
  • This workshop mainly divided into three parts, firstly advanced machine learning algorithms, second basic to advanced recent studies on biomedical signals and images, third tools for implementation & virtual demo on biomedical signals and images.

In the present scenario, the medical disease prognosis, detection, and diagnosis suffers from many human errors and looking into the poor patient-doctor ratio worldwide, the development of computer-assisted technologies is the only solution. Hence, any academic and industry research is going hand on hand to develop such technologies and large work is going on their validation in a real-time scenario, their generalization with minimal computational efforts on a single platform.

In view of that, machine learning techniques is being use at large, and also they are being further develop to cater above tasks with ease. Such as very recent development in deep learning which is being vastly being explor now, having advantages of no feature engineering, intelligent deeper learning, learning migration, and many more.

  1. You will learn the Introduction to advanced machine learning
  2. Also, Introduction to deep learning
  3. here you will also learn Applications to biopotentials
  4. Applications to medical images
  5. Online demo/ training on the implementation of advanced machine learning methods in python and MATLAB.
  • Firstly, Advanced Machine Learning-I
  • Secondly, Advanced Machine Learning-II
  • Thirdly, Advanced Machine Learning Applications for Medical
  • Fourthly, Advanced Machine Learning Applications for Biopotentials-I
  • Lat, Advanced Machine Learning Tools & Algorithms
Who can Attend?

UG/ PG Students, Research Scholars, Academicians, and Industry invited to apply.

Registration Fees
  • Students (UG): Rs. 118
  • Students (PG): Rs. 236
  • Ph.D. Scholars: Rs. 354
  • Faculty Member: Rs. 590
  • Industry Delegate: Rs. 1180

So Registration Fees Payment can be made to the account of Director NIT Raipur; Account No.: 38027633250; IFSC: SBIN0002852; Branch: SBI GCET RAIPUR.

  1. Most important Unterstanding of the basics of machine learning, computational platforms like python, MATLAB will help participants to benefit more from this course.
  2. E-Certificates will be issued to the participants only after attending the complete course.
  3. To register for the course further below link
  4. To Apply: click here.

Phone Number: 7903631620

Email ID:

For full notification, click the link below.

Online Training Program on Advanced Machine Learning for Biosignal Data by NIT, Raipur

You Must also show interest in: SBI Post Doctoral Research Fellowship 2020

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