This class presents the fundamental probability and statistical concepts used in elementary data analysis. It will be taught at an introductory level for students with junior or senior college-level mathematical training including a working knowledge of calculus. A small amount of linear algebra and programming are useful for the class, but not required.
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
- 5 stars63.61%
- 4 stars23.88%
- 3 stars7.81%
- 2 stars2.45%
- 1 star2.23%
Great course, excellent homework/quizzes and comparatively rigorous treatment by a great Prof.
I enjoyed the course. I wish there was perhaps a little more evaluation along the way (maybe occasional in-lecture questions), but otherwise very nice.
I liked the course. Need good maths skills. Would prefer to have a review/HW after each lecture than at the end of each week.
I wish this Johns Hopkins course is more interactive. Like the Ohio State Calculus One class.
关于 Advanced Statistics for Data Science 专项课程
Fundamental concepts in probability, statistics and linear models are primary building blocks for data science work. Learners aspiring to become biostatisticians and data scientists will benefit from the foundational knowledge being offered in this specialization. It will enable the learner to understand the behind-the-scenes mechanism of key modeling tools in data science, like least squares and linear regression.