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The Symbolic Systems Program or SymSys is a unique degree program at Stanford University for undergraduates and graduate students. It is an interdisciplinary degree encompassing the following: Computer Science; Linguistics; Mathematics; Philosophy; Psychology; Statistics; It is separate to Cognitive Science in that it is more expansive in scope ...
In 2022, Stanford started its first dual-enrollment computer science program for high school students from low-income communities, [151] as a pilot project which then inspired the founding of the Qualia Global Scholars Program. [152] Stanford plans to expand the program to include courses in Structured Liberal Education and writing. [151]
Stanford science went through three phases of experimental direction during that time. ... the acceptance rate dropped from 13% for the class of 2004 to 4.69% for the ...
Students go over a final review of the lessons they’ve learned in Introduction to Computer Science, a dual enrollment class through Stanford University, at Antioch High School in Antioch, Tenn ...
The rate is down from 5.05% last year, and will likely be the number Ivy League colleges will be chasing to become the 'most competitive' elite college. Stanford University's acceptance rate hit ...
Stanford OHS operates on a need-blind admissions process for both domestic and international students, and commits to ensuring that both continuing and newly admitted students can attend, regardless of their financial status. In the 2023–24 school year, Stanford OHS allocated over $2.5 million in financial aid, including Malone scholarships.
The Stanford Department of Electrical Engineering, also known as EE; Double E, is a department at Stanford University. Established in 1894, [ 7 ] it is one of nine engineering departments that comprise the school of engineering, [ 8 ] and in 1971, had the largest graduate enrollment of any department at Stanford University. [ 9 ]
Ng is a professor at Stanford University departments of Computer Science and electrical engineering. He served as the director of the Stanford Artificial Intelligence Laboratory (SAIL), where he taught students and undertook research related to data mining, big data, and machine learning. His machine learning course CS229 at Stanford is the ...