AI ML in Drug Discovery Training Program - 14 Days & 3 Months (With Project & Paper Publication Assistance)

AI & ML are the HOTTEST Topics of Discussion in Every Field, Including Life Sciences.

YOU DON'T WANT TO BE LEFT BEHIND IF YOU ARE AN ASPIRING SCIENTIST!

Enroll in our AI ML in Drug Discovery Training Program, available as 14 days short-term & 3 months Training program with project & Paper publication assistance.

Be a pioneer in the evolving landscape of AI & Machine Learning applications within the Biopharma industry.

Enroll Today and Be Part of the Revolution in Drug Discovery!

This 14-day intensive training program is designed for beginners in the field of drug discovery, particularly tailored for students and professionals in the Life Sciences and Biotech sector, including B.Sc., M.Sc., B.Tech., M.Tech., B.Pharm, M.Pharm, Ph.D., and Post-Doc students. The program offers a comprehensive introduction to the integration of Artificial Intelligence (AI) and Machine Learning (ML) in drug discovery, providing an essential toolkit for those aiming to revolutionize their research and development strategies.

Program Overview

14 Days Short Term Training

• Start Date: 15th Feb 2024
• Duration: 14 Days
• Timings: 6 pm to 7 pm
• Mode: Online
  

3 Months of Training with Project & Paper Publication Assistance

• Start Date: 15th Feb 2024
• Duration: 3 Months
• Timings: 6 pm to 7 pm
• Mode: Online

Why Should Life Science / Biotech Students Learn AI/ML?

• Bridging Technology and Biology: Understanding AI and ML is crucial in today's technology-driven research landscape. It enables biotech professionals to stay at the forefront of innovation in drug discovery.
• Data-Driven Decisions: AI/ML empowers researchers with the ability to make informed, data-driven decisions, which is essential in complex fields like drug development.
• Career Advancement: With the growing demand for AI and ML expertise in the life sciences sector, this training opens doors to numerous high-potential career paths.

Course Structure

UNIT-1: Introduction to Drug Discovery and AI/ML Basics

• DAY-1: Introduction to Drug Discovery, Overview of drug development phases. Importance of target identification and validation.
• DAY-2-3: Introduction to AI/ML in Drug Discovery, Basic artificial intelligence and machine learning concepts. Overview of how AI/ML is transforming drug discovery. Biology and Chemistry Basics for AI/ML, Brief review of molecular biology and biochemistry concepts. Key biological and chemical terms relevant to drug discovery.

UNIT-2: Machine Learning Models for Drug Discovery

• DAY-4: Supervised Learning in Drug Discovery, Overview of supervised learning algorithms. Case studies of drug discovery applications. Unsupervised Learning in Drug Discovery, Clustering techniques and applications. Dimensionality reduction for large datasets.
• DAY-5: Deep Learning in Drug Discovery, Introduction to neural networks. Applications of deep learning in drug discovery.

UNIT-3: Cheminformatics and Bioinformatics Tools

• DAY-6: Cheminformatics, Overview of chemical informatics tools. Molecular docking and virtual screening.
• DAY-7: Bioinformatics Drug Database and its relevance. Structural bioinformatics tools.
• DAY-8-9: Explore Python coding for drug discovery.
• DAY-10-11: Real-world Case Studies and Practical Applications, Analyzing successful AI/ML applications in drug discovery. Challenges and limitations in implementation.
• DAY-12-14: Practical Sessions using GitHub repository Hands-on exercises using relevant tools and datasets. Group projects focusing on specific drug discovery problems.
• Course Module for 3 Months Training with Project & Paper Publication Assistance will be more detailed & elaborate with Hands-on training + Individual assistance.

About the Instructor:

Ms. Nilofer K Shaikh, PhD With a strong background in big data analysis using computational approaches in cancer omics data, Ms. Nilofer K Shaikh brings a wealth of experience from MIT ADT University. Her expertise spans cancer research, drug design, molecular dynamics simulation, data mining, and various omics technologies. She is proficient in Python, R, and computational methodologies and has a deep understanding of genomics, metabolomics, proteomics, transcriptomics, pharmacogenomics, and AI for cancer treatment. Her skillset also includes machine learning, MySQL database management, and natural language processing (NLP).

Why Attend This Training?

1. Expert-Led Sessions: Learn from industry professionals and academics who are pioneers in integrating AI and ML in drug discovery.

2. Hands-On Experience: Engage in practical sessions and group projects to apply your learning in real-world scenarios.

3. Networking Opportunities: Connect with fellow students and professionals from diverse life sciences and biotech backgrounds.

4. Skill Development: Acquire practical skills in AI/ML applicable to drug discovery scenarios.

5. Career Advancement: Enhance your resume and open doors to diverse career paths in the biotech and pharmaceutical industries.

6. Certificate of Completion: Receive a recognized certificate upon successfully completing the program.

Who Can Attend?

This program is ideal for students and professionals in B.Sc., M.Sc., B.Tech., M.Tech., B.Pharm, M.Pharm, Ph.D., and Post-Doc courses related to Life Sciences and Biotech who are keen on expanding their knowledge and skills in AI and ML applications in drug discovery.

Benefits

• Comprehensive Understanding: Gain a deep understanding of how AI and ML are revolutionizing drug discovery.
• Skill Enhancement: Develop technical skills in AI/ML, bioinformatics, and cheminformatics.
• Career Development: Equip yourself with the skills needed to excel in the rapidly evolving field of drug discovery.

Enroll Today and Be Part of the Revolution in Drug Discovery!

Note: We do not guarantee paper publication & job placement under this program. We will guide you throughout the training course to ensure you are ready enough to get a job & publish papers in well-reputed journals.