In the AI for Scientific Research specialization, we'll learn how to use AI in scientific situations to discover trends and patterns within datasets. Course 1 teaches a little bit about the Python language as it relates to data science. We'll share some existing libraries to help analyze your datasets. By the end of the course, you'll apply a classification model to predict the presence or absence of heart disease from a patient's health data. Course 2 covers the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms.In the final project, we'll apply our skills to compare different machine learning models in Python. In Course 3, we will build on our knowledge of basic models and explore more advanced AI techniques. We’ll describe the differences between the two techniques and explore how they differ. Then, we’ll complete a project predicting similarity between health patients using random forests. In Course 4, a capstone project course, we'll compare genome sequences of COVID-19 mutations to identify potential areas a drug therapy can look to target. By the end, you'll be well on your way to discovering ways to combat disease with genome sequencing.
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AI for Scientific Research Specialization
Launch Your Career in Data Science. Use artificial intelligence to discover and test hypothesis.
Instructors: Sabrina Moore
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What you'll learn
How to use AI in scientific situations to discover trends and patterns within datasets
The complete machine learning process
Use artificial intelligence to predict sequences in datasets
Overview
Skills you'll gain
- Bioinformatics
- Random Forest Algorithm
- Dimensionality Reduction
- Classification And Regression Tree (CART)
- Data Processing
- Feature Engineering
- Data Manipulation
- Data Science
- Machine Learning Algorithms
- Data Transformation
- Machine Learning
- Data Cleansing
- Applied Machine Learning
- Exploratory Data Analysis
- Predictive Modeling
What’s included
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Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from LearnQuest
Specialization - 4 course series
What you'll learn
Employ artificial intelligence techniques to test hypothesis in Python
Apply a machine learning model combining Numpy, Pandas, and Scikit-Learn
Skills you'll gain
What you'll learn
Implement and evaluate machine learning models (neural networks, random forests, etc.) on scientific data in Python
Skills you'll gain
What you'll learn
Skills you'll gain
What you'll learn
Analyzing genome sequences to find similarities and identify target subsequences using predctive models.
Skills you'll gain
Earn a career certificate
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Frequently asked questions
To complete all four courses in the specialization, you will spend 3-5 hours per week for 14 weeks.
No specific background is required, but AI and Machine Learning are science-heavy, so an interest in science and mathematics is helpful.
Yes. Because the information builds across courses, it is recommended that you take them in order.
More questions
Financial aid available,