Students are also taught methods from the modern machine learning toolbox and how they can be used to answer questions with datasets. Students learn the fundamentals of Python programming as well as the different parts of data engineering, including data cleaning, data manipulation, and data visualization. The Programming for Data Science course equips students with the technical programming skills to conduct data science research. Learn the programming skills to conduct interdisciplinary data science research projects She also received the energ圜atalyst grant from the Stanford Tom Kat Center for Sustainable Energy to pursue computer vision research.
In college, Anne was recognized as the top project in Stanford's CS109 (Probability for Computer Scientists) out of 100+ project submissions. She was also recognized as a #include fellow by she++, an organization for women in technology at Stanford University. In addition, Anne was named a Semifinalist in the Siemens Competition in Math, Science, and Technology and received First Place at the United Nations Sustainable Development Contest. At RSI, Anne conducted research at MIT's Computational Materials Design Lab and was the only student in her RSI class to receive top 5 awards for both her final paper and final presentation. In high school, Anne was invited to attend the Research Science Institute (RSI), a highly selective research fellowship hosted by MIT. Lessons in the course will incorporate experiences from the instructing team’s past experiences entering science fair competitions and conducting research from a young age.Īnne is an undergraduate studying computer science at Stanford University. Conducting research at a young age can be especially difficult, and the course is designed specifically to break down the research process for high school students. Finally, students are taught how to write academic research papers, create research posters, and deliver scientific presentations. Students are also taught techniques in exploratory data analysis and inferential statistics that can be used to answer research questions. Students are taught how to ask relevant research questions and how to decide what modern statistical and machine learning tools can be applied to develop and support answers to these questions. Students learn how to choose an initial field of interest, how to identify and interpret relevant background readings and literature, and how to find, augment, and scrape workable datasets. The Conducting Data Science Research course teaches students how to design and conduct interdisciplinary data science research projects from start to finish. Learn to design, conduct, and present a data science research project
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