New Delhi: IIT Hyderabad in association with IHub Data is to offer a 12-week course on ‘Machine Learning for Chemistry and Drug Design’ from March 10, 2022. This is to provide the learners necessary knowledge on both theoretical and practical aspects of AI and ML.
An official statement regarding the course by IIIT Hyderabad reads, “There would be a series of lectures covering topics in both sciences and AI/ML to help build a strong theoretical foundation. The course will also offer hands-on tutorial sessions to help the participants pick-up practical problem-solving abilities.”
IIIT Hyderabad ML for Chemistry and Drug Design Course: Highlights
| Course Provider | IHub-Data, in association with IIIT Hyderabad |
|---|---|
| Course Duration | 12 week |
| Course Mode | Online |
| Course Format | 90 minute weekly lectures -150 minute weekly hands-on programming tutorial sessions -Weekly/bi-weekly assignments -Weekly office-hours with teaching assistants for one-on-one interaction |
| Course Fees | INR 7,500 (for UG and Master’s students) -INR 15,000 (for PhD students) -INR 30,000 (for industry professionals) -INR 5250 for female UG students -Partial wavering for students from underrepresented communities and selected PhD students without funding |
| Application Link | Click Here |
IIIT Hyderabad ML for Chemistry and Drug Design Course: Eligibility Criteria
Interested candidates who wish to attend the course by IHub-Data and IIIT Hyderabad, can look into the eligibility criteria, as stated in the official notice. Here are the requirements:
- Students, researchers, professional workers with Science background, especially Computer Science and Mathematics
- Candidates have to possess Indian nationality
- Any exposure to any programming language (Especially Python) will be preferable
- Background in Class 12 mathematics is necessary
IIIT Hyderabad ML for Chemistry and Drug Design Course: Objectives
Here are the primary course objectives:
- Providing fundamental theoretical and practical knowledge about the concepts in AL and ML and their application for Drug Discovery
- Hands-on Experience on using several tools, libraries for multiple machine learning and deep learning methods
- Internship or research opportunities for the top performers
- Opportunity to collaborate with ML experts for your projects or thesis
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