Students gain a strong foundation in data science by applying machine learning fundamentals to professional astronomical data through hands-on projects at a leading university.
The Academy for Data Science Research (using Astronomical Data) at the University of Texas at Austin offers high school students an immersive, hands-on experience in data science and machine learning. Participants will learn to analyze real-world astronomical data, applying the scientific method to uncover meaningful insights. The curriculum introduces essential tools like Jupyter Notebook, NumPy, Matplotlib, and Pandas, and explores various machine learning models using Scikit-Learn. Students will engage in hands-on projects, including obtaining data from professional databases, data cleaning, exploratory data analysis, and regression analysis of astronomical data. The program emphasizes interpreting and evaluating results, as well as communication and team-building skills. By the end of the academy, students will have a strong foundation in data science and an understanding of data-driven discovery making.
A typical day involves learning data science fundamentals, exploring essential tools like Jupyter Notebook and Python libraries, and working on hands-on projects applying the scientific method to astronomical data.
This academy is ideal for high school students entering 10th-12th grade with an interest in astronomy, physics, computer science, and/or interdisciplinary STEM fields, who have at least one semester of Python programming experience.
University of Texas at Austin
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