View the complete course: http://ocw.mit.edu/6-034F10 Instructor: Patrick Winston In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabilistic inference. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

Programming Methodology (CS106A) is an Introduction to the engineering of computer applications emphasizing modern software engineering principles: object-oriented design, decomposition, encapsulation, abstraction, and testing. Uses the Java programming language. Emphasis is on good programming style and the built-in facilities of the Java language.

This course (CS 106B) is the successor to CS 106A and covers more advanced programming topics such as recursion, algorithmic analysis, and data abstraction. It is taught using the C++ programming language, which is similar to both C and Java. In the past when both CS 106A and CS106B were taught in C/C++, the coupling between the two classes was very tight and it was unheard for students to take CS106B without having completed our CS 106A (we recommended CS 106X instead). Nowadays, some students do go straight into CS106B, this is typically appropriate for a student who done well in an intro programming course (e.g., scored 4 or 5 on the CS AP exam or earned a good grade in a college course) and has sufficient familiarity with good programming style and software engineering issues (at the level of CS 106A) to use this understanding as a foundation on which to tackle advanced topics.

Programming Paradigms (CS107) introduces several programming languages, including C, Assembly, C++, Concurrent Programming, Scheme, and Python. The class aims to teach students how to write code for each of these individual languages and to understand the programming paradigms behind these languages.

COMPSCI 188, LEC 001 - Fall 2018 COMPSCI 188, LEC 001 - Pieter Abbeel, Daniel Klein Copyright @2018 UC Regents; all rights reserved "Slides (from 2018): https://inst.eecs.berkeley.edu/~cs188... Latest website: https://inst.eecs.berkeley.edu/~cs188 More resources: http://ai.berkeley.edu