AI for Scientific Research
Learn to apply AI and machine learning techniques to analyze scientific data and discover patterns in research datasets.
Learn to apply AI and machine learning techniques to analyze scientific data and discover patterns in research datasets.
This specialization teaches how to leverage artificial intelligence for scientific research and data analysis. Through four comprehensive courses, students learn to implement machine learning models, from basic classification to advanced neural networks and random forests. The program covers the complete machine learning pipeline, including data preparation, model selection, and practical applications in healthcare and genomics. The capstone project focuses on analyzing COVID-19 genome sequences for drug discovery.
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What you'll learn
Understand digital business ecosystems and transformation
Analyze digital business processes and models
Develop growth hacking strategies
Formulate digital strategic shifts
Apply digital innovation principles
Evaluate digital business opportunities
Skills you'll gain
This course includes:
46 Hours PreRecorded video
30 assignments
Access on Mobile, Desktop, Tablet
FullTime access
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There are 4 courses in this program
Introduction to Data Science and scikit-learn in Python
Course 1 · 13 Hours to complete · 4 modules
Machine Learning Models in Science
Course 2 · 11 Hours to complete · 4 modules
Neural Networks and Random Forests
Course 3 · 10 Hours to complete · 4 modules
Capstone Project: Advanced AI for Drug Discovery
Course 4 · 12 Hours to complete · 4 modules
Fee Structure
Payment options
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