This playlist is the complete course on Object-Oriented Programming in Python.

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

MIT 18.404J Theory of Computation, Fall 2020 Instructor: Michael Sipser View the complete course: https://ocw.mit.edu/18-404JF20 YouTube Playlist: • MIT 18.404J Theory of Computation, Fall 2020 Introduction; course outline, mechanics, and expectations. Described finite automata, their formal definition, regular languages, regular operations, and regular expressions. Proved that the class of regular languages is closed under union. Started proving closure under concatenation. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.

Theory of Computation is one of the most fundamental as well as abstract courses of Computer Science. It is a branch in theoretical Computer Science that deals with whether problems can be solved and how efficiently problems can be solved on a model of computation, using an algorithm. The lectures in this series gives you an intuitive understanding of the course and helps you to understand deeper about designing machines, about the working of machines and much more and helps you understand it in a simple yet effective way. You will find lectures on the following topics: 1. Introduction to Theory of Computation 2. Finite State Machines 3. Deterministic Finite Automata 3. Non-deterministic Finite Automata 4. Conversion of NFA to DFA and their equivalence 5. Mealy Machine and Moore Machine 6. Regular Expression 7. Context Free Languages 8. Turing Machine 9. Undecidability

Operating systems are an essential part of any computer system. Similarly, a course on operating systems is an essential part of any Computer Science as well as Electronics course. This field is undergoing rapid change, as computers are now prevalent in virtually every application. Yet the fundamental concepts remain fairly clear and that is what will be taught in this course. In brief, an operating system acts as an intermediary between the user of a computer and the computer hardware. The purpose of an operating system is to provide an environment in which a user can execute programs in a convenient and efficient manner. Every important aspects of an Operating System will be taught in this course so as to get a proper understanding about Operating Systems and their design and working. You will find lectures on the following topics: 1) Introduction to OS 2) Operating System Structures 3) Process Management 3.1) Processes 3.2) Threads 3.3) CPU Scheduling 3.4) Process Synchronization 3.5) Deadlocks 4) Memory Management 4.1) Main Memory 4.2) Virtual Memory 5) Storage Management 5.1) File System Interface 5.2) File-System Implementation 5.3) Mass-Storage Structure 5.4) I/O Systems 6) Protection and Security 7) Distributed Systems 7.1) Distributed System Structures 7.2) Distributed File Systems 7.3) Distributed Coordination 8) Special Purpose Systems

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