WEKA: Exploring Machine Learning for Healthcare – Batch 4
Last day of Registration: 7th August, 2025
- Description about the Workshop
- Profile of the Instructor
- Session Schedule
- Eligibility
- Certification
- Fees for the Workshop
- Session Details
- Reviews (0)
Profile of the Instructor
Prof. M Michael Gromiha received his Ph.D from Bharathidasan University, India and served as STA fellow, RIKEN Researcher, Research Scientist and Senior Scientist at Computational Biology Research Center, AIST, Japan till 2010. Currently, he is working as a Professor at Indian Institute of Technology (IIT) Madras, India. He is teaching courses on bioinformatics, protein structure and function, protein interactions: computational techniques and handling computational biology lab. His main research interests are computational studies on protein structure and function, mutational analysis, machine learning techniques and development of databases and algorithms. He has published over 350 research articles/reviews, 10 editorials and two books on Protein Bioinformatics (Elsevier/Academic Press) and Protein interactions (World Scientific). His papers received about 14,000 citations and his h-index is 61. He has received several awards including Institute Research and Development Award, Tamil Nadu Scientist Award, ASC Masila Vijay Award for excellence in scientific research and publications. He is serving as Associate Editor/Editorial Board Member in 10 internationally reputed journals. He is ranked as topmost 0.5% of researchers in Bioinformatics/Biophysics/overall in the world. He is a Fellow of the Indian National Science Academy (FNA). Session Schedule
Day 1 :
Module 1: Development of Algorithm (10:00 a.m. - 11:30 a.m)
Concepts Covered:
Datasets/features/methods/evaluation.Learning outcome:
Efficiently and systematically approaching a bioinformatics problem.Module 2: An Introduction to Weka Machine Learning Workbench (11:30 a.m. - 01:00 p.m.)
Concepts Covered:
Machine learning techniques/input features/interpretation of outputLearning outcome:
Features available in Weka and details on input and output files.Module 3: Live Demo (02:00 p.m. - 04:00 p.m.)
Concepts Covered:
Working exampleLearning outcome:
Learn methods and validation procedures in WEKAAssessment: Multiple Choice Question
Day 2 :
Project 1: (10:00 a.m. - 01:00 p.m.)
Distinguishing between disease and neutral mutationsLearning outcome:
Reliable methods and interpretations for discriminationProject 2: (02:00 p.m. - 04:00 p.m.)
Predicting inhibitory concentration of compounds for a drug targetLearning outcome:
Reliable methods and interpretations for predictionAssessment : Short Project
Eligibility
Desirable academic qualification:
B.Sc/B.Tech/ M.Sc/M.Tech /PhD etc. (Pursuing/ Completed); Basic knowledge in programming would be beneficial, but not mandatory.Intended Audience:
Students, PhD scholars, Teachers, IndustryCertification
- Regular attendance, A short assessment (MCQ) and Project.
Number & Type of Assessment :
- Assessment with objective type question - 1 Short Projects - 2


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