Courses tagged with "Computer Science" (650)

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Starts : 2017-01-16
527 votes
edX Free Computer Sciences English ColumbiaX Computer Science EdX

What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?

They are all complex real world problems being solved with applications of intelligence (AI).

This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.

Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.

Starts : 2015-09-11
369 votes
Coursera Free Popular Closed [?] Business English Artificial Intelligence Computer Science Computer Science Economics & Finance Theory

The course covers the basics: representing games and strategies, the extensive form (which computer scientists call game trees), repeated and stochastic games, coalitional games, and Bayesian games (modeling things like auctions).

Starts : 2016-09-20
367 votes
edX Free Computer Sciences English Computer Science EdX UC BerkeleyX

Part 2 of the UC Berkeley Agile Development Using Ruby on Rails XSeries Program will teach you to use JavaScript to enhance applications and create more sophisticated apps by adding relationships between models within the Ruby on Rails framework. You will also learn about what happens after the apps are deployed to real users, including how to monitor performance, identify and fix common performance problems, and avoid compromising customer data. Finally, learners will see how to apply Agile techniques to enhance and refactor legacy code and practice app deployment to real users to monitor performance, identify and fix common performance problems, and avoid compromising customer data. 

Other topics covered in this software engineering course include:

  • How to form, organize and manage small programming teams
  • Introduction to design patterns: what they are and how to recognize opportunities to apply them
  • Using Rails for more advanced features like third-party authentication and elegantly expressing design patterns that arise frequently in SaaS

There will be three homework assignments: two programming assignments and one assignment about operations/deployment. There will also be several short quizzes. The videos and homework assignments used in this offering of the course were revised in October 2013.

Starts : 2014-09-15
328 votes
Coursera Free Popular Computer Sciences English Computer Science Software Engineering

This course is designed to be a fun introduction to the basics of programming in Python. Our main focus will be on building simple interactive games such as Pong, Blackjack and Asteroids.

Starts : 2014-09-12
324 votes
Coursera Free Popular Closed [?] Business English Artificial Intelligence Computer Science Economics & Finance

Find out how modern electronic markets work, why stock prices change in the ways they do, and how computation can help our understanding of them.  Build algorithms and visualizations to inform investing practice.

Starts : 2015-09-04
308 votes
Coursera Free Popular Closed [?] Computer Sciences English Computer Science Computer Science Software Engineering Theory

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers basic iterable data types, sorting, and searching algorithms.

Starts : 2015-01-19
307 votes
Coursera Free Popular Closed [?] Computer Sciences English Artificial Intelligence Computer Science Statistics and Data Analysis

Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Starts : 2016-03-16
306 votes
Coursera Free Popular Closed [?] Computer Sciences English Computer Science Computer Science Software Engineering Theory

This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations.

Starts : 2015-02-02
304 votes
Coursera Free Popular Computer Sciences English Artificial Intelligence Computer Science Computer Science Mathematics Statistics and Data Analysis Theory

Learn the concepts and methods of linear algebra, and how to use them to think about computational problems arising in computer science. Coursework includes building on the concepts to write small programs and run them on real data.

Starts : 2015-10-05
297 votes
Coursera Free Popular Closed [?] Computer Sciences English Computer Science Theory

In this course you will learn several fundamental principles of algorithm design: divide-and-conquer methods, graph algorithms, practical data structures (heaps, hash tables, search trees), randomized algorithms, and more.

Starts : 2015-04-27
297 votes
Coursera Free Popular Closed [?] Computer Sciences English Computer Science Computer Science Software Engineering Systems & Security

Learn about traditional and mobile malware, the security threats they represent, state-of-the-art analysis and detection techniques, and the underground ecosystem that drives such a profitable but illegal business.

Starts : 2015-10-26
295 votes
Coursera Free Popular Closed [?] Computer Sciences English Computer Science Computer Science Systems & Security Theory

Learn about the inner workings of cryptographic primitives and how to apply this knowledge in real-world applications!

Starts : 2013-10-07
281 votes
Coursera Free Popular Closed [?] Computer Sciences Computer Science Information Software Engineering Tech & Design

Helping you build human-centered design skills, so that you have the principles and methods to create excellent interfaces with any technology.

Starts : 2016-06-07
274 votes
edX Free Computer Sciences English Computer Science EdX HarveyMuddX

Looking to get started with computer science while learning to program in Python?

This computer science  course provides an introduction to computer science that’s both challenging and fun. It takes a broad look at the field of computer science through a variety of demonstrations and projects. We’ll cover both low- and high-level concepts, from how the circuits inside a computer represent data to how to design algorithms, as well as how all of this information affects the technology we use today. Additionally, we’ll teach the basics of Python programming, giving us a a way to put our new CS knowledge into practice.

No need to know any programming before starting the course; we’ll teach everything you need to know along the way. All you need to start is a good grasp of algebra, and you can fall in love with both the concepts and the practice of computer science.

Starts : 2016-05-01
180 votes
edX Free Computer Sciences English Computer Science EdX UC San DiegoX

Today, computer graphics is a central part of our lives, in movies, games, computer-aided design, virtual simulators, visualization and even imaging products and cameras.  This course teaches the basics of computer graphics that apply to all of these domains.

Students will learn to create computer-generated images of 3D scenes, including flybys of objects, make a real-time scene viewer, and create very realistic images with raytracing.  We will start with a simple example of viewing a teapot from anywhere in space, understanding the basic mathematics of virtual camera placement.  Next, you will learn how to use real-time graphics programming languages like OpenGL and GLSL to create your own scene viewer, enabling you to fly around and manipulate 3D scenes.  Finally, we will teach you to create highly realistic images with reflections and shadows using raytracing.CSE167x teaches the foundations of computer graphics. 

This course runs for 6 weeks and consists of four segments. Each segment includes an individual programming assignment:

  1. Overview and Basic Math (Homework 0: 10% of grade)
  2. Transformations (Homework 1: 20% of grade)
  3. OpenGL and Lighting (Homework 2: 35% of grade)
  4. Raytracing (Homework 3: 35% of grade)

This term, students who earn a total score of 50% or greater will have passed the course and may obtain a certificate from UC San DiegoX.


FAQ

What is the format of the class?

The class will consist of lecture videos, brief exercises, and homework assignments. Each of the four segments of the course will have 2-3 lectures. Each lecture includes 3-5 lecture videos, which last between 10 and 20 minutes. There will be a brief exercise after each lecture video to help you test your understanding of the material. 

Your score will be determined entirely by programming assignments for which you will receive immediate autograder feedback. You may submit your assignment to the autograder multiple times; only your last submission will count.

Programming projects are to be implemented individually without copying code from other students, largely identical online resources, or previous instances of the class. However, short of posting or sharing actual explicit code, you are encouraged to collaborate and discuss problems in the discussion forums.

Will the text of the lectures be available?

Yes. All of our lectures will have transcripts synced to the videos.

Do I need to watch the lectures live?

No. You can watch the lectures at your leisure. You can "work ahead" if you want to move faster than the due dates. Conversely, you can progress at a slower pace. Please note that certificates will only be awarded to students who obtain the requisite score by turning in assignments by the established deadlines.

How much does it cost to take the course?

Nothing: the course is free. If you expect to be doing a lot of graphics programming in the future, we would recommend the OpenGL and GLSL programming guides, but it is by no means required to purchase them. There are many free online resources for these topics, and we will be posting links to them.

What computer system do I need for the course?

The course material involves C++/OpenGL/GLSL programming that is portable. We provide skeleton code for all major platforms (Windows, Mac OS, Linux). This is a modern course involving programmable shaders, but any machine built in the last few years should be adequate. We provide many compilation hints and tips, and Homework 0 is to ensure you can compile and work with the autograder. You do need some kind of C++ development environment; we provide several resources to get you started for Homework 0. In the highly unlikely event you cannot get your machine to work, you will hopefully have adequate time to find another system.

Will I learn Maya/DirectX/3D Studio Max etc.?

This is a course on the foundations of computer graphics and covers concepts, not the intricacies of a particular software package. That said, you will be able to write complex interactive and offline 3D graphics programs at the end of the course in C++, OpenGL and GLSL.

Can I contact the Instructor or Teaching Assistants?

Yes, but not directly. The discussion forums are the appropriate venue for questions about the course. The instructors will monitor the discussion forums and try to respond to the most important questions; in many cases response from other students and peers will be adequate and faster.

I have a disability (visual/hearing etc.) Can I take the course?

In most cases, yes. We provide transcripts for all lectures. Many leading computer graphics researchers have had visual impairments like color-blindness. However, this being a computer graphics course that relies on visual image comparisons, we probably cannot provide adequate support for those who are legally blind.

I have a busy schedule this fall. Can I still take the course?

The course does require about 12 hours per week of work, and the assignments (where you are given two weeks) require the time. Certificates of achievement require a passing score. Of course, you are welcome to just go through the lectures or attempt some of the assignments if you are not interested in a certificate; we hope to provide something for everyone.

 

Starts : 2014-03-17
123 votes
Coursera Free Computer Sciences English Computer Science Computer Science Software Engineering Systems & Security

This course will discuss the major ideas used today in the implementation of programming language compilers. You will learn how a program written in a high-level language designed for humans is systematically translated into a program written in low-level assembly more suited to machines!

Starts : 2015-01-12
120 votes
Coursera Free Computer Sciences English Computer Science Computer Science Software Engineering Systems & Security

This course introduces concepts, languages, techniques, and patterns for programming heterogeneous, massively parallel processors. Its contents and structure have been significantly revised based on the experience gained from its initial offering in 2012. It covers heterogeneous computing architectures, data-parallel programming models, techniques for memory bandwidth management, and parallel algorithm patterns.

Starts : 2015-02-02
118 votes
Coursera Free Computer Sciences English Computer Science Engineering Systems & Security

A modern VLSI chip has a zillion parts -- logic, control, memory, interconnect, etc.  How do we design these complex chips?  Answer: CAD software tools.  Learn how to build these tools in this class.

Starts : 2015-01-05
117 votes
Coursera Free Closed [?] Computer Sciences English Artificial Intelligence Biology & Life Sciences Computer Science Computer Science Information Software Engineering

An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research.

Starts : 2016-01-04
116 votes
Coursera Free Closed [?] Computer Sciences English Artificial Intelligence Computer Science Engineering Mathematics

In this class you will look behind the scenes of image and video processing, from the basic and classical tools to the most modern and advanced algorithms.