NIT Raipur Online STTP On “Advanced Machine Learning for Biosignal Data”
One week Virtual/Online Short Term Training Program (STTP) On
“Advanced Machine Learning for Biosignal Data”
NIT Raipur
8-12 October 2020
ABOUT:
Electrical Engineering Department & Information Technology Department NIT Raipur is organizing a One week Virtual/Online Short Term Training Program (STTP) On “Advanced Machine Learning for Biosignal Data” from 8-12 October 2020.
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, advanced machine learning algorithms, basic to advanced recent studies on biomedical signals and images, tools for implementation & virtual demo on biomedical signals and images.
Course Contents:
- Introduction to advanced machine learning
- Introduction to deep learning
- Applications to biopotentials
- Applications to medical images
- Online demo/training on implementation of advanced machine learning methods in python and MATLAB
Targeted Participants:
- UG/PG Students
- Research Scholars
- Academicians
- Industry
Registration Fees :
| Participants | Amount ( ₹ ) (Fees + 18% GST) |
| Students (UG) | 118 |
| Students (PG) | 236 |
| PhD Scholars | 354 |
| Faculty Member | 590 |
| Industry Delegate | 1180 |
For Register- CLICK HERE
Certification:
E-Certificates will be issued to the participants only after attending the complete course.
NOTE:
- Knowledge of basics of machine learning, computational platforms like python, MATLAB will help participants to benefit more from this course.
- Application in the prescribed format with registration fee in the form of DD/NEFT/RTGS drawn in favor of “Director, NIT Raipur” may please sent via email on or before 5th October 2020.
Contact:
Ph – 7903631620 / 9039898860
For more information, see below