AI for Scientific Research

Overview

Explore the pivotal role of Artificial Intelligence in revolutionizing scientific research with the "AI for Scientific Research" specialization on Coursera. This comprehensive program is designed for those eager to harness AI's power to uncover trends and patterns in complex data sets.

Beginning with an introduction to Python, crucial for data science, learners will quickly move on to utilizing existing libraries for data analysis. The initial course lays a solid foundation by teaching students to implement a classification model to accurately predict heart disease based on patient health data.

The curriculum progresses to encompass the full machine learning pipeline, addressing the collection, cleaning, and transformation of data, followed by the application of both fundamental and sophisticated machine learning algorithms.

The culmination of these skills will be showcased in a project that involves comparing various machine learning models utilizing Python.

Advancing further, we delve into complex AI techniques, highlighting the distinctions between basic models and advanced approaches. Participants will undertake a project focused on predicting similarities among health patients using random forests, pushing the boundaries of AI in healthcare.

The final capstone project is a demonstration of the specialization's comprehensive knowledge, where students will analyze genome sequences of COVID-19 mutations.

This endeavor aims to identify potential targets for drug therapy, presenting a formidable weapon in the fight against diseases through genome sequencing.

Offered by Coursera, this specialization aligns with multiple categories, including Artificial Intelligence, Data Analysis, and Science Courses, setting participants on a path to making significant contributions to scientific research using AI.

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Taught by

Neelesh Tiruviluamala, Rajvir Dua and Sabrina Moore

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Subjects