Overview and use of data science tools in R and/or Python for data retrieval, analysis, visualization, reproducible research, and automated report generation. Case studies will illustrate the practical use of these tools.
4
UnitsOptional
Grading1, 2, 3
PasstimeNone
Level LimitLetters and science
CollegeCannot hear the professor at all and he refuses to wear a mic. Made the final questions we had never gone over in class and barely curved. Would not recommend
Dr. Coburn was great in lectures, and made the concepts seem simple to understand, but the ease of homework, examples and quiz questions left me improperly prepared for the midterm and final question styles. Very accesible, and office hours are helpful. Weekly homework and quizzes, a midterm and a final exam.
The professor is calm and cool. The exams are a bit hard and I would recommend studying with lots of practice problems weeks before exams. I found that the practice exams were not as helpful as the lecture examples.
honestly 120A was fine if you studied and showed up to class. it was hard but idk who expects it to be easy
All my friends said that he was the easy professor for 120A, but his practice tests were NOTHING like the actual exams. Lectures were boring and not useful. Fully made me lose the passion that I had for statistics. Ended up taking this class P/NP and dropped my stats minor. None of the content is interesting or applicable to the real world.
Test materials are different from lectures. He said he would not test the materials he had taught in the last several minutes, yet he still gave one.