sniperpilot16 / dsps

Data Science for Physical Scientists

Welcome to Data Science for Physical Scientists, a class developed and taught by Federica Bianco at the University of Delaware Physics and Astronomy Departmant : PHY 467/667

This class has a Code of Conduct Before you do any thing else, please review the code of conduct. If you have questions of concerns about it let me know promptly

Please review the Syllabus

Course Description This course will teach you the basis of data driven inference in the physical sciences. You will learn a examples of machine learning methods applied to current problems in Phsyics and the Natural Sciences. You will acquire basic computational skills, knowledge of statistical analysis, error analysis, good practises for handling, processing, and analyzing data and (including big-data) programmatically, and communication and visualization skills. Some of the simpler algorithms will be explored in detail and implemented from scratch, others will be implemented through the use of dedicated python libraries.

Don't worry about how much you already know, especially do not compare it to what other students know. You may have the wrong perception of your skills, and of the skills of your classmates, and your strengths and the strengths of your background may lie in another set of skills, just as important for a Physical Scientist. Some of you may have a good handle and understanding of some or all of the physics problems we will study, others a good handle on coding, others yet an easy time understanding the details of the analysis. All these components make proficiency in this class, and all these components make a good scientist. We, the class assistnts and I, are here to help you develop the skills you do not yet have and strengthen the skills you already have.

By the end of this class you should be able to formulate an appropriate analysis plan for a research question, select, gather, and prepare data for analysis, and choose and apply machine learning methods to the data.