Machine Learning for Drug Discovery
This course is ideal for students pursuing their Bachelor's, Master's, or Ph.D. and who are beginning their studies in drug discovery. The applications of computational drug discovery and artificial intelligence for science students are specifically addressed in this course, which was specifically built with their starting level understanding in mind. By the time this course is finished, participants will have the fundamental skills needed to manage their drug development project while utilizing AI and ML-based technologies.
Join the course at an affordable price:
Indian Nationals - Rupees 10,000 + GST
Foreign Nationals - $160 (USD)
Key Takeaways from the Internship:
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Introduction to drug discovery and applications of AI & ML techniques at different stages
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Introduction to types of Artificial Intelligence & Machine learning
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Introduction to the potential of AI & ML in Drug Discovery
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AI-based systems modeling to understand disease mechanisms
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AI-based systems modeling of novel drug-like molecules
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Certificates of Completion
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Video Lectures
Introduction to Drug Discovery and AI-ML
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Introduction to Drug Discovery
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Introduction to AI-ML
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Installing pre-requisites
Supervised Learning
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Random Forest
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Decision Tree
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Logistic Regression
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Support Vector Machine
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Lasso Regression
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Application/Exercise
Disease Prediction
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Disease Selection
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ChemBL Database
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Lipinski's Calculation
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Plotting Drug Data
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Assignments/Exercise
Machine Learning Type
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Supervised learning
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Unsupervised Learning
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Semi-Supervised Learning
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Reinforcement Learning
Unsupervised Learning
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K-Means Clustering
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Mean Shift Algorithm
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DBSCAN Algorithm
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Principle Component Analysis
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Assignments/Exercise
Molecular Fingerprints
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Model Training on Dataset
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Model building
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Training, Testing, Validation
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Model prediction
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Model analysis
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