Introduction to Computer Science with Python Course description This course is an introduction to computer science for students without prior programming experience. We explore problem-solving methods and algorithm development using the high-level programming language Python after a brief introduction to computational concepts using Scratch.
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Programming in C and Intel IA32 assembly. COS 226. Algorithms and Data Structures. The most important algorithms and data structures in use on computers today.
Princeton University Climbing two places in this year's world ranking for computer science, Princeton University ranks 11th worldwide and sixth in the US. Notable alumni include Amazon CEO and founder Jeff Bezos and Google executive Eric Schmidt, as well as Alan Turing.
The department, now in a period of major growth, has strong groups in artificial intelligence and machine learning, theory, programming languages, graphics and vision, systems and networking, computer architecture, computational biology and neuroscience, security, privacy, and information technology policy.
The computer science department at Princeton offers undergraduates courses in the core areas of computer science and in an array of application and interdisciplinary areas.
Massachusetts Institute of TechnologyHere are the best computer science masters programsNAME/RANKPEER ASSESSMENT SCOREMassachusetts Institute of Technology Cambridge, MA #1 in Computer Science Save5.0Carnegie Mellon University Pittsburgh, PA #2 in Computer Science (tie) Save4.9Stanford University Stanford, CA #2 in Computer Science (tie) Save4.98 more rows
degree is granted by six departments of the School of Engineering and Applied Science: Civil and Environmental Engineering, Chemical & Biological Engineering, Computer Science, Electrical and Computer Engineering, Mechanical and Aerospace Engineering and Operations Research and Financial Engineering.
This is an extremely difficult load -- many students find doing both COS 226 and COS 217 simultaneously very difficult. Very few students can handle the even tougher load of COS 226 and 217 in conjunction with 323 or 240.
Princeton Day School in Princeton was also among the nation's top STEM schools, with an overall score of 91.39 out of 100. Princeton Day School, which is an independent, coeducational day school for students from Pre-K through Grade 12, ranked 351 out of the top 500.
Students considering majoring in Computer Science, please click on your year and degree for additional information - AB'24 and BSE'25. This website contains much of the information to consider when deciding whether to become a CS major.
Computer Science is the only department at Princeton which offers both A.B. and B.S.E. degrees.
So, if you're looking for a computer science degree, consider that while all of the Ivy League schools can give you a solid and reliable CS education; the top options are Harvard and Columbia.
Best Schools For Computer Science Majors by Salary PotentialRankSchool NameMid-Career Pay4Harvard UniversityMid-Career Pay:$179,4005Carnegie Mellon UniversityMid-Career Pay:$178,3006Massachusetts Institute of TechnologyMid-Career Pay:$177,2007Princeton UniversityMid-Career Pay:$177,10021 more rows
The course will present a computer science approach to thinking and modeling. Students will be introduced to fundamental concepts such as NP-completeness and cryptography that arise from the world view of efficient computation.
An introduction to the principles of typed functional programming. Programming recursive functions over structured data types and informal reasoning by induction about the correctness of those functions. Functional algorithms and data structures. Principles of modular programming, type abstraction, representation invariants and representation independence. Parallel functional programming, algorithms and applications.
Provides a broad introduction to different machine learning paradigms and algorithms, providing a foundation for further study or independent work in machine learning, artificial intelligence, and data science. Topics include linear models for classification and regression, support vector machines, neural networks, clustering, principal components analysis, Markov decision processed, planning, and reinforcement learning.
The goal is to prepare students for higher-level subjects in artificial intelligence, machine learning, computer vision, natural language processing, graphics, and other topics that require numerical computation. The course focuses on tying together the underlying mathematical principles, numerical algorithms, and how they are used to solve problems computationally. Assignments consist of both conceptual problems and coding portions completed in Python.
View the undergraduate and graduate course schedule for current and past semesters.
Descriptions of the undergraduate and graduate courses our faculty may teach.
Computer Science: An Interdisciplinary Approach. An introduction to computer science in the context of scientific, engineering, and commercial applications. The course will teach basic principles and practical issues, and will prepare students to use computers effectively for applications in computer science, physics, biology, chemistry, ...
The course will present a computer science approach to thinking and modeling through such topics as dealing with uncertainty in data and handling large data sets . Students will be introduced to fundamental concepts such as NP-completeness and cryptography that arise from the world view of efficient computation. Prerequisites COS 126 and 226 (or sufficient mathematical background), and MAT 202 or MAT 204 or MAT 217. COS 226 can be taken along with COS 340 in the same term.
Emphasis is on the development of real programs, writing code but also assessing tradeoffs, choosing among design alternatives, debugging and testing, and improving performance. Issues include compatibility, robustness, and reliability, while meeting specifications.
An introduction to the principles of typed functional programming. Programming recursive functions over structured data types and informal reasoning by induction about the correctness of those functions. Functional algorithms and data structures. Principles of modular programming, type abstraction, representation invariants and representation independence. Parallel functional programming, algorithms and applications.
The first three courses constitute the core breadth requirement. All students must fulfill the breadth requirements by the end of the second year, demonstrating minimum competence in three main areas of computer science: Systems, Artificial Intelligence (AI), and Theory.
Course requirements are fulfilled by taking six courses for a grade. As least three of the six courses must be 500-level, and the additional courses may be chosen from 318, 320, 324, 326, 352, 375, or any 400-level course. Students must take a minimum of 4 courses in year 1.
An introduction to the intellectual enterprises of computer science and the art of programming.
This course is a variant of Harvard University's introduction to computer science, CS50, designed especially for lawyers (and law...
Learn to use machine learning in Python in this introductory course on artificial intelligence.
This is CS50’s introduction to technology for students who don’t (yet!) consider themselves computer persons.
Take your introductory knowledge of Python programming to the next level and learn how to use Python 3 for your research.
An introduction to programming using Python, a popular language for general-purpose programming, data science, web programming,...