AI ML in Drug Discovery, Bio-Pharma & Chemistry Hands-on Training Program With 3, 6 & 12 Months LIVE Project Work
AI ML in Drug Discovery, Bio-Pharma Hands-on Training Program
With 3, 6 & 12 Months LIVE Project Work
WORK IN PROJECTS | PUBLISH PAPERS | GET WORK EXPERIENCE in AI ML
Starts 11th NOV 2024
Dive into the future of Chemistry and Pharma with our specialized AI and ML training program. Designed for professionals and students, this comprehensive course integrates cutting-edge AI and ML techniques with essential concepts in chemistry and pharmaceutical sciences. The program includes hands-on project work options of 3, 6, or 12 months, allowing you to apply your skills to real-world problems.
Program Overview:
- Start Date: 11th Nov 2024
- Time: 7-8 PM IST
- Venue: Online
- Project work: 3,6, & 12 months duration
Why Join This Training?
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Expert-Led Instruction: Learn from industry leaders and academic experts who bring practical knowledge and research-based insights into AI and ML applications.
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Hands-On Experience: Engage in practical exercises using industry-standard tools like TensorFlow, RDKit, and KNIME. Our project work options enable you to gain deep, hands-on experience.
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Real-World Applications: Explore how AI/ML is transforming drug discovery, molecular design, and personalized medicine. Work on projects that mimic real-life challenges in the chemistry and pharma industries.
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Flexible Learning Paths: With options for 3, 6, and 12 months of project work, you can choose a learning path that fits your schedule and career goals.
Why Learn AI/ML in Chemistry and Pharma?
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Stay Ahead of the Curve: AI/ML is revolutionizing the pharma industry, enabling faster drug discovery, personalized treatments, and more efficient R&D processes.
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High Demand Skills: With the rise of AI/ML in the industry, professionals skilled in these areas are in high demand across the globe.
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Innovative Research Opportunities: AI/ML offers novel approaches to tackle complex problems in chemistry, such as molecular design and toxicity prediction.
Eligibility
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Educational Background: Ideal for students and professionals with a background in Biotech, Life Sciences, Chemistry, Pharmaceuticals, Bioinformatics, Computer Science, or related fields.
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Prerequisites: Basic understanding of Drug Discovery chemistry and computational tools. Prior experience in programming or data science is beneficial but optional.
Meet Your Instructor
Dr. Dolly Sharma
PhD | Chembiotech
Lead Scientist in Cheminformatics and Drug Discovery
Dr. Dolly Sharma is a distinguished expert in cheminformatics, drug design, and discovery, with a Ph.D. in Biotechnology from Amity University and an M.Tech. from Gautam Buddha University. Her groundbreaking research focuses on the design of biorelevant small molecules aimed at cancer treatment, which has led to the filing of three patents and the publication of over ten highly cited research papers.
Dr. Sharma has made significant strides in drug design and discovery, particularly in the development of DNA origami-based nanodevices and the establishment of advanced synthesis methodologies. Her expertise and innovative approach have been recognized through the successful acquisition of research grants totaling ₹92 lakhs from DST SERB, DBT, and UPCST. Additionally, she has secured an impressive ₹55 lakhs from the DBT Wellcome Alliance and EMBO for organizing a key scientific event.
With a profound understanding of cheminformatics and a proven track record in project management, Dr. Sharma is dedicated to pushing the boundaries of scientific discovery and is eager to bring her extensive knowledge and experience to your team.
30-Day Course Curriculum
Week 1: Foundations and Introduction to Tools
- Day 1: Introduction to AI, ML, and Cheminformatics
- Day 2: Data Handling and Preprocessing
- Day 3: Molecular Descriptors and Fingerprints
- Day 4: Introduction to Machine Learning Algorithms
- Day 5: Model Evaluation and Validation
Week 2: Advanced Techniques in Cheminformatics and ML
- Day 6: Quantitative Structure-Activity Relationship (QSAR)
- Day 7: Molecular Docking and Virtual Screening
- Day 8: Deep Learning in Cheminformatics
- Day 9: Neural Networks for Drug Discovery
- Day 10: Generative Models for Molecular Design
- Day 11: Cheminformatics Data Integration and Workflow Automation
- Day 12: Feature Engineering in Cheminformatics
Week 3: Specialized Applications and Case Studies
- Day 13: AI for Predicting ADMET Properties
- Day 14: AI in Pharmacophore Modeling
- Day 15: Machine Learning in Toxicology Prediction
- Day 16: AI-Driven Target Identification
- Day 17: Case Study: AI in COVID-19 Drug Discovery
- Day 18: Computational Chemistry and Molecular Dynamics
- Day 19: Chemoinformatics for Natural Products
- Day 20: Molecular Libraries and Databases
Week 4: Future Trends, Projects, and Presentations
- Day 21: AI in Personalized Medicine
- Day 22: Current Trends in AI/ML for Chemistry and Pharma
- Day 23: Regulatory Considerations in AI-driven Drug Discovery
- Day 24: Advanced AI Techniques: Reinforcement Learning in Drug Design
- Day 25-27: Project Work (Model Design, Development, Testing, Optimization)
- Day 28: Project Presentations
- Day 29: Course Recap and Future Directions
- Day 30: Optional Workshop/Networking Event
Project Work Options
3 Months: Short-term projects focusing on specific applications like QSAR modelling or molecular docking.
6 Months: Intermediate projects involving more complex models and integration with real-world datasets.
12 Months: Long-term research projects aiming at publication-quality results or industrial application.
Enrol Today!
Equip yourself with the skills to transform the future of Chemistry and Pharma. Whether you are looking to enhance your career, pivot to a new field, or contribute to groundbreaking research, this program offers the tools and knowledge to succeed.