COM SCI M148
Introduction to Data Science
Description: (Same as Electrical and Computer Engineering M148.) Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: course 31 or Program in Computing 10A, and 10B, and one course from Civil and Environmental Engineering 110, Electrical and Computer Engineering 131A, Mathematics 170A, Mathematics 170E, or Statistics 100A. How to analyze data arising in real world so as to understand corresponding phenomenon. Covers topics in machine learning, data analytics, and statistical modeling classically employed for prediction. Comprehensive, hands-on overview of data science domain by blending theoretical and practical instruction. Data science lifecycle: data selection and cleaning, feature engineering, model selection, and prediction methodologies. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Winter 2024 - Fantastic professor. Not much else to say. Her lectures were great, and it's extremely appreciated how she records her lectures. She's nice and approachable, and the midterm exam was actually fair. The homework assignments are put together very well, and I honestly had fun doing them. I like that she knows what her class is supposed to focus on and doesn't go too far into the mathematics. I'm just really happy with this class and prof overall.
Winter 2024 - Fantastic professor. Not much else to say. Her lectures were great, and it's extremely appreciated how she records her lectures. She's nice and approachable, and the midterm exam was actually fair. The homework assignments are put together very well, and I honestly had fun doing them. I like that she knows what her class is supposed to focus on and doesn't go too far into the mathematics. I'm just really happy with this class and prof overall.
Most Helpful Review
Spring 2021 - Overall, I would say I like what they are going for in this class. They try and do a mix of teaching you the theoretical aspects of data science, while also giving you practical data science projects in python. Professor was absolutely horrible, though. His lectures were really hard to pay attention to and he was not clear in what he was teaching at all. At the end of this class, I would say I obtained a light understanding of the data science/ML theory and a good understanding of how to actually create models and using data science libraries.
Spring 2021 - Overall, I would say I like what they are going for in this class. They try and do a mix of teaching you the theoretical aspects of data science, while also giving you practical data science projects in python. Professor was absolutely horrible, though. His lectures were really hard to pay attention to and he was not clear in what he was teaching at all. At the end of this class, I would say I obtained a light understanding of the data science/ML theory and a good understanding of how to actually create models and using data science libraries.
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