STAT 05 W — Statistics for Artificial Intelligence, Machine Learning, and Data Science: An Introduction
WHAT MAKES OUR ONLINE COURSES UNIQUE:
- Course sizes are limited.
You won't have 5,000 classmates. This course's enrollment is capped at 65 participants.
- Frequent interaction with the instructor.
You aren't expected to work through the material alone. Instructors will answer questions and interact with students on the discussion board and through weekly video meetings.
- Study with a vibrant peer group.
Stanford Continuing Studies courses attract thoughtful and engaged students who take courses for the love of learning. Students in each course will exchange ideas with one another through easy-to-use message boards as well as optional weekly real-time video conferences.
- Direct feedback from the instructor.
Instructors will review and offer feedback on assignment submissions. Students are not required to turn in assignments, but for those who do, their work is graded by the instructor.
- Courses offer the flexibility to participate on your own schedule.
Course work is completed on a weekly basis when you have the time. You can log in and participate in the class whenever it's convenient for you. If you can’t attend the weekly video meetings, the sessions are always recorded for you and your instructor is just an email away.
- This course is offered through Stanford Continuing Studies.
To learn more about the program, visit our About Us page. For more information on the online format, please visit the FAQ page.
Weekly course lecturers will be conducted via live videoconferencing sessions. The first session will take place on Tuesday, January 21 from 6:00 - 7:30 pm PT. The remaining class meetings will be held on Monday evenings from 6:00 - 7:30 pm PT. The duration will be approximately 90 minutes, but the lectures could run slightly shorter or longer depending on student questions. Most of the course material will be covered during the live sessions, and although the lectures will be recorded, student attendance is recommended.
This course has no specific prerequisites and can be taken on a variety of levels. Beginners are encouraged to listen to the lectures and learn basic concepts. By the end of the course, beginners should have a sense of what these algorithms do. On a higher level, intermediate students can work some of the introductory problems that will be provided. On an advanced level (for students with a substantial math background who are interested in becoming data scientists), difficult math and stats problems will be covered. Students should be aware that this course will not make them an AI expert (this is not possible in nine sessions). On a basic level, the course will give students a taste of what statistics for AI is all about. On the highest level, the course will give students a strong sense of what they need (and should be excited about) in order to pursue a career in this area.