The Course
Dive right into the dynamic world of pharmaceuticals where artificial intelligence and machine learning are revolutionizing how we discover new drugs. Over 14 intensive days, you'll get to grips with the core subjects of AI and ML, uncovering patterns in complex biological data and predicting which drug candidates could be winners. From the intricacies of molecular docking to the nuances of predictive toxicity, you'll learn the tools and techniques that are propelling the industry forward. And it doesn't stop at theory; you'll apply what you've learned to real-world scenarios, understanding how this tech breakthrough can slash years off the drug development process and save lives.
But that's just the beginning! For those eager to make a tangible impact, an additional 3-month project period takes you from student to trailblazer. With mentoring from experts, you’ll spearhead a research project, getting hands-on experience that culminates with the chance to publish your findings. Imagine adding your voice to the scientific community while still sharpening your skills! This is an opportunity to not only boost your resume but also contribute to a field where AI and ML deliver hope to millions waiting for the next medical breakthrough. Embrace the blend of cutting-edge technology and applied science – it's your moment to be at the forefront of an exciting paradigm shift in drug discovery.
What you will learn
I started crafting this program with a clear vision in mind – to demystify the complex world of AI & ML in drug discovery for beginners like you. It's all about taking those first confident steps in a field that's reshaping medicine as we know it. With a curriculum that's both thorough and digestible, I've laced every module with real-world examples, ensuring you not only learn but truly comprehend how these technologies are revolutionizing pharmaceuticals. The course structure flows logically, guiding you from fundamental concepts to more advanced applications, with hands-on projects and mentorship that open doors to practical experience and even scholarly contributions through paper publications. Rest assured, I've put everything in place to make your journey as insightful and well-supported as it can be.
Curriculum
- Day 1 : Introduction to Drug Discovery, Overview of drug development phases. Importance of target identification and validation (68:05)
- Day 2: Introduction to AI/ML in Drug Discovery, Basic concepts of artificial intelligence and machine learning. Overview of how AI/ML is transforming drug discovery (57:21)
- Day 3 : Biology and Chemistry Basics for AI/ML, Brief review of molecular biology and biochemistry concepts. Key biological and chemical terms relevant to drug discovery. (55:04)
- Day 4: Supervised Learning in Drug Discovery, Overview of supervised learning algorithms. (62:34)
- Day 5 : Deep Learning in Drug Discovery, Introduction to neural networks. Applications of deep learning in drug discovery. (57:36)
- Day 6 : Cheminformatics, Overview of chemical informatics tools. Molecular docking and virtual screening. (62:17)
- Day 7: Bioinformatics Drug Database and its relevance. Structural bioinformatics tools. (59:22)
- Day 8 : Explore Python coding for drug discovery (57:14)
- Day 9: Explore Python coding for drug discovery (47:07)
- Day 10: Real-world Case Studies and Practical Applications (62:22)
- Day 11: Analyzing successful AI/ML applications in drug discovery. Challenges and limitations in implementation. (70:42)
- Day 12: Practical Sessions using GitHub repository Hands-on exercises using relevant tools and datasets. (58:11)
- Day 13 :Group projects focusing on specific drug discovery problems. (50:07)
- Day 14: Group projects focusing on specific drug discovery problems. (59:18)
- Test Link
- 7th March 2024 (57:12)
- 12th march 2024 (54:36)
- 14th March 2024 (54:05)
- 19th March 2024 (49:11)
- 21st march 2024 (56:06)
- 26th March 2024 (50:40)
- 28th March 2024 (36:51)
- 02nd April 2024 (36:36)
- 4th April 2024 (49:10)
- 09th April 2024 (44:48)
- 11th April 2024 (75:38)
- 12th April 2024 (57:06)
- 15th April 2024 (57:30)
- 16th April 2024 (60:00)
- 17th April 2024 (61:13)
- 18th April 2024 (59:25)
- 19th April 2024 (91:01)
- 22th April 2024 (58:14)
- 23rd April 2024 (76:33)
- 24th April 2024 (56:16)
- 25th April 2024 (43:22)
- 26th April 2024 (37:08)
- 29th April 2024 (53:19)
- 30th April 2024 (37:24)
Your instructor
As an educator entrenched in the bustling intersection of biotechnology and computer science, I bring a wealth of experience to the AI ML in Drug Discovery Training Program. My journey through academia and industry has equipped me with an in-depth understanding of the transformative potential of artificial intelligence and machine learning in revolutionizing the pharmaceutical landscape. With a background that marries theoretical knowledge with practical expertise, I am uniquely positioned to guide students through the intricacies of drug discovery and the innovative AI techniques that are reshaping this field.
My connection to the AI ML in Drug Discovery Training Program is rooted in my passion for nurturing the next generation of scientists and researchers. I firmly believe in the power of hands-on experience, which is why I am deeply invested in providing students with not only rigorous instruction but also the opportunity to engage in real-world projects and contribute to scientific literature through paper publication assistance. This program reflects my commitment to high-quality education that bridges the gap between theoretical learning and practical application, ensuring that our graduates are well-equipped to make meaningful contributions to the future of drug discovery.
Comprehensive
Mastering the Frontier of Pharmaceutical Innovation
Intensive
From Concepts to Real-World Applications in Pharmacology
Transformative
Catalyzing Change in Drug Development Through Artificial Intelligence