Online courses directory (713)

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2 votes
Khan Academy Free Closed [?] Education Coach resources Khan Academy in the classroom

Learn about Khan Academy's vision of a classroom of the future and get an overview of KA resources, including our interactive exercises and coach reports. An intro to Khan Academy. Why use Khan Academy?. Khan Academy Vision. The biggest misconceptions about Khan Academy. Take a tour of the Khan Academy site. Take a tour of our data reports. Take a tour of KA exercises. Take a tour of KA's Computer Science in the classroom. Try it out!. An intro to Khan Academy. Why use Khan Academy?. Khan Academy Vision. The biggest misconceptions about Khan Academy. Take a tour of the Khan Academy site. Take a tour of our data reports. Take a tour of KA exercises. Take a tour of KA's Computer Science in the classroom. Try it out!.

57 votes
Khan Academy Free Closed [?] Education Coach resources Khan Academy resources

Overview of the videos, exercises, reports, and Computer Science resources available on Khan Academy, with emphasis on how resources can be used in classrooms. For more information, check out http://www.khanacademy.org/toolkit/ka-resources. For a mapping of Khan Academy content to Common Core standards, check out khanacademy.org/commoncore. Khan Academy overview. Khan Academy reports overview. Khan Academy Exercise Overview. Khan Academy Computer Science in the classroom. Khan Academy overview. Khan Academy reports overview. Khan Academy Exercise Overview. Khan Academy Computer Science in the classroom.

101 votes
Khan Academy Free Closed [?] Education Coach resources Khan Academy resources

Overview of the videos, exercises, reports, and Computer Science resources available on Khan Academy, with emphasis on how resources can be used in classrooms. For more information, check out http://www.khanacademy.org/toolkit/ka-resources. For a mapping of Khan Academy content to Common Core standards, check out khanacademy.org/commoncore. Khan Academy overview. Khan Academy reports overview. Khan Academy Exercise Overview. Khan Academy Computer Science in the classroom.

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 : 2017-03-02
No votes
edX Free English Computer Science EdX Math TsinghuaX

Our lives are full of combinations. Combinatorial mathematics is just the science to deal with combinations of discrete items. As an ancient field, the history of combinatorial mathematics can be traced back over 4000 years to the age of the Great Yu in ancient China. Today, combinatorial mathematics is regarded as the basis of computer science since the algorithms in programming heavily rely on the analysis of the discrete elements.

Instead of relying on the traditional mathematical "theorem - proof" format, this course demonstrates various principles in an intuitive manner with ancient stories, the scenes of movies and even a magic show. What you’ll learn:

  • The counting principles based on the basic operations “+”, “-”, “*”, “/”; 
  • Generating functions
  • Recurrent number serials such as Fibonacci number, Catalan number, and more
  • Pigeon hole principles
  • Inclusion and exclusion principles
  • Polya counting based on group theory

This course is based on a highly regarded on-campus Tsinghua class called Combinatorics, and is ideal for students who are interested in mathematics or computer science. Enroll today and learn the mathematical theory needed to solve the real-world problems!

 

我们生活的方方面面都充满着组合,而组合数学正是研究离散事物的学科。作为一个具有悠久历史的学科,组合数学的发展可以追溯到4000年前的大禹时代。而如今组合数学随着计算机学科的发展开启了新的篇章,由于程序算法的分析和实现正是基于对离散对象的分析,因此组合数学已经发展成为计算机学科的基础理论。

而本课程一改以往数学教学的“定理-证明”模式,引领大家由浅入深地逐步探索知识的源泉,这里有古代故事,有电影片段,甚至用魔术来演绎数学概念。而这些形式就是为了引领大家去感受数学的美。具体的教学内容包括:

  • 基于四则运算的计数法则;
  • 母函数;
  • 递推序列,如斐波那契数,卡特兰数等;
  • 鸽巢原理;
  • 容斥原理;
  • 基于群论的波利亚定理。

本课程的内容和大纲主要基于清华大学精品课《组合数学》,通过本课程的学习,学习者可以深入了解计数的抽象理论和具体方法,从而深入理解组合数学对计算机理论发展的推动作用。。

 


FAQ

I don’t speak Chinese, can I learn the course?

All the materials are in English. Though the original video was recorded in Chinese, the course team record the corresponding dubbing in English. All the audio and subtitles are processed to fit the English dubbing as much as possible, so that you can enjoy this wonderful course in English.

What are the textbook and the reference books for this course?

There is no textbook requirement for this course. The handouts distributed every week are critical. The following books are references

  • Richard A. Brualdi; Introductory Combinatorics (5th edition), Pearson, 2009
  • J.H.van Lint and R.M. Wilson; A course in Combinatorics, Cambridge University Press, 2001
  • 卢开澄,《组合数学》第四版,清华大学出版社

What is the grading breakdown?

  • 70% quizzes and exercises
  • 30% final exam

How can I get the certificate?

If your final score is no less than 60.

Do I need to know how to program to learn this class?

Not necessary. This course is a math course which is based on fundamental theory. But to help the students to have the intuitive feel of the effects of the theory, we also provide a code lib that you can compare different implementations by running different programs.    

No votes
Study.com Free Closed [?] Business EPA Social Science

Build your earth science vocabulary and learn about cycles of matter and types of sedimentary rocks through the Education Portal course Earth Science 101: Earth Science. Our series of video lessons and accompanying self-assessment quizzes can help you boost your scientific knowledge ahead of the Excelsior Earth Science exam . This course was designed by experienced educators and examines both science basics, like experimental design and systems of measurement, and more advanced topics, such as analysis of rock deformation and theories of continental drift.

Starts : 2003-09-01
11 votes
MIT OpenCourseWare (OCW) Free Business MIT OpenCourseWare Sloan School of Management Undergraduate

Competition in Telecommunications provides an introduction to the economics, business strategies, and technology of telecommunications markets. This includes markets for wireless communications, local and long-distance services, and customer equipment. The convergence of computers, cable TV and telecommunications and the competitive emergence of the Internet are covered in depth. A number of speakers from leading companies in the industry will give course lectures.

No votes
ALISON Free Business Course Type: course Free to Access Mime Type - Scorm 1.2

This is a continuation of our series of accounting courses that will greatly increase your knowledge and understanding of the theory of accounting and accounting practices. This free online accounting course explains the processes used to close your accounts at the end of an accounting period, from creating a worksheet that facilitates the generation of the Income Statement and Retained Earnings statement to the generation of the Balance sheet. You will also be shown how a Classified Balance sheet is broken down into current and long-term assets and liabilities. The important Current Ratio figure is calculated and explained in context. You will also learn a little about the history of accounting systems and the impact of computerization on the process. This free online accounting course will be of great interest to entrepreneurs and business professionals who would like to get a thorough introduction to accounting principles, and to any learner who is interested in accounting as a future career.<br />

Starts : 2008-02-01
12 votes
MIT OpenCourseWare (OCW) Free Computer Sciences MIT Music and Theater Arts OpenCourseWare Undergraduate

This class explores sound and what can be done with it. Sources are recorded from students' surroundings - sampled and electronically generated (both analog and digital). Assignments include composing with the sampled sounds, feedback, and noise, using digital signal processing (DSP), convolution, algorithms, and simple mixing. The class focuses on sonic and compositional aspects rather than technology, math, or acoustics, though these are examined in varying detail. Students complete weekly composition and listening assignments; material for the latter is drawn from sound art, experimental electronica, conventional and non-conventional classical electronic works, popular music, and previous students' compositions.

No votes
Udacity Free Georgia Tech Masters in CS

This class is offered as CS6505 at Georgia Tech where it is a part of the [Online Masters Degree (OMS)](http://www.omscs.gatech.edu/). Taking this course here will not earn credit towards the OMS degree. In this course, we will ask the big questions, “What is a computer? What are the limits of computation? Are there problems that no computer will ever solve? Are there problems that can’t be solved quickly? What kinds of problems can we solve efficiently and how do we go about developing these algorithms?” Understanding the power and limitations of algorithms helps us develop the tools to make real-world computers smarter, faster and safer.

Starts : 2009-02-01
10 votes
MIT OpenCourseWare (OCW) Free Computer Sciences Electrical Engineering and Computer Science MIT OpenCourseWare Undergraduate

6.004 offers an introduction to the engineering of digital systems. Starting with MOS transistors, the course develops a series of building blocks — logic gates, combinational and sequential circuits, finite-state machines, computers and finally complete systems. Both hardware and software mechanisms are explored through a series of design examples.

6.004 is required material for any EECS undergraduate who wants to understand (and ultimately design) digital systems. A good grasp of the material is essential for later courses in digital design, computer architecture and systems. The problem sets and lab exercises are intended to give students "hands-on" experience in designing digital systems; each student completes a gate-level design for a reduced instruction set computer (RISC) processor during the semester.

Starts : 2016-09-06
No votes
edX Free English Computer Science EdX Electronics Engineering MITx

Digital systems are at the heart of the information age in which we live, allowing us to store, communicate and manipulate information quickly and reliably. This computer science course is a bottom-up exploration of the abstractions, principles, and techniques used in the design of digital and computer systems. If you have a rudimentary knowledge of electricity and some exposure to programming, roll up your sleeves, join in and design a computer system!

This is Part 1 of a 3-part series on digital systems, teaching the fundamentals of digital circuit design and is based on a course offered by the MIT Department of Electrical Engineering and Computer Science. Topics include digital encoding of information, principles of digital signaling; combinational and sequential logic, implementation in CMOS, useful canonical forms, synthesis; latency, throughput and pipelining.

Using your browser for design entry and simulation, you’ll get to design and debug circuits at both the transistor- and gate-level, culminating in the creation of a 32-bit arithmetic and logic unit.

 

Learner Testimonial

“This course is like a dream coming true...as kid (10 - 12 years) I was already building circuits and reading books about Digital Circuits. Due to all kind of circumstances I never got to pursue a study and career in electronics ...now I am almost 50... I see this as a second chance. Thank you very very much for this awesome course. One of the best, (if not the best) MOOCs I've ever taken.” -- Previous Student

Starts : 2016-11-29
No votes
edX Free English Computer Science EdX Electronics Engineering MITx

Digital systems are at the heart of the information age in which we live, allowing us to store, communicate and manipulate information quickly and reliably. This computer science course is a bottom-up exploration of the abstractions, principles, and techniques used in the design of digital and computer systems. If you have a rudimentary knowledge of electricity and some exposure to programming, roll up your sleeves, join in and design a computer system!

This is Part 2 of a 3-part series on digital systems, teaching the fundamentals of computer architecture and is based on a course offered by the MIT Department of Electrical Engineering and Computer Science. Topics include instruction set architectures and assembly language, stacks and procedures, 32-bit computer architecture, the memory hierarchy, and caches.

Using your browser for design entry and simulation, you’ll implement a 32-bit computer using our gate library and write assembly language programs to explore the hardware/software interface.

 

Learner Testimonial

“If you look back, we've done sooooo much: assembly programming, stack crawling (detective work), building a 32-bit computer, for crying out loud, and also learnt about caches as the cherry on top (which really helped me because I always had trouble understanding how temporary memory worked). And to top it off, they're promising us more exciting courses in the future.” -- Previous Student

Starts : 2017-02-28
No votes
edX Free English Computer Science EdX Electronics Engineering MITx

Digital systems are at the heart of the information age in which we live, allowing us to store, communicate and manipulate information quickly and reliably. This computer science course is a bottom-up exploration of the abstractions, principles, and techniques used in the design of digital and computer systems. If you have a rudimentary knowledge of electricity and some exposure to programming, roll up your sleeves, join in and design a computer system!

This is Part 3 of a 3-part series on digital systems, providing an introduction to the hardware/software interface and is based on a course offered by the MIT Department of Electrical Engineering and Computer Science. Topics include pipelined computers, virtual memories, implementation of a simple time-sharing operating system, interrupts and real-time, and techniques for parallel processing.

Using your browser for design entry and simulation, you’ll optimize your processor design from Part 2 for size and speed, and make additions to a simple time-sharing operating system.

 

Learner Testimonial

"Out of the many edX courses I have taken, the first two parts of 6.004x were clearly the best. I am looking forward to the third part.” -- Previous Student

Starts : 2009-09-01
No votes
MIT OpenCourseWare (OCW) Free Media Arts and Sciences MIT OpenCourseWare Undergraduate

A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information can be synthesized.

We will discuss and play with thermal cameras, multi-spectral cameras, high-speed, and 3D range-sensing cameras and camera arrays. We will learn about opportunities in scientific and medical imaging, mobile-phone based photography, camera for HCI and sensors mimicking animal eyes. We will learn about the complete camera pipeline. In several hands-on projects we will build physical imaging prototypes and understand how each stage of the imaging process can be manipulated.

Starts : 2009-09-01
14 votes
MIT OpenCourseWare (OCW) Free Closed [?] Computer Sciences Graduate Media Arts and Sciences MIT OpenCourseWare

A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information can be synthesized.

We will discuss and play with thermal cameras, multi-spectral cameras, high-speed, and 3D range-sensing cameras and camera arrays. We will learn about opportunities in scientific and medical imaging, mobile-phone based photography, camera for HCI and sensors mimicking animal eyes. We will learn about the complete camera pipeline. In several hands-on projects we will build physical imaging prototypes and understand how each stage of the imaging process can be manipulated.

No votes
OLI. Carnegie Mellon University Free Computer Sciences Carnegie Mellon University Open Learning Initiative

This course presents material in discrete mathematics and computation theory with a strong emphasis on practical algorithms and experiential learning. Discrete mathematics, also called finite mathematics or decision mathematics, is the study of mathematical structures that are fundamentally discrete in the sense of not supporting or requiring the notion of continuity. Objects studied in finite mathematics are largely countable sets such as integers, finite graphs, and formal languages. Concepts and notations from discrete mathematics are useful to study or describe objects or problems in computer algorithms and programming languages. The CDM course is currently under development and we are making the course available while it is under development. Only one of the planned fifteen modules is currently available. The module on Groups that is currently available would appear mid-way through the complete course.

Starts : 2017-02-20
No votes
edX Free English Computer Science EdX TsinghuaX

Geometry can be traced back to ancient Greece, but Computational Geometry evolved less than 40 years as a branch of computer science. The Computational Geometry taught in this course is derived from classical discrete/combinatorial geometry and modern computer science.

Computational Geometry first appeared on the horizon when M. I. Shamos presented his Ph.D. dissertation in 1978. Since then, this phrase has been used to refer to algorithmic study on discrete and combinatorial geometric structures and can also be regarded as the geometric version of Algorithm Design and Analysis. Computational Geometry is now considered the basis of robotics, computer aided design and manufacturing (CAM and CID), and geographic information systems (GIS).

Starts : 2003-09-01
13 votes
MIT OpenCourseWare (OCW) Free Computer Sciences Aeronautics and Astronautics Graduate MIT OpenCourseWare

16.225 is a graduate level course on Computational Mechanics of Materials. The primary focus of this course is on the teaching of state-of-the-art numerical methods for the analysis of the nonlinear continuum response of materials. The range of material behavior considered in this course includes: linear and finite deformation elasticity, inelasticity and dynamics. Numerical formulation and algorithms include: variational formulation and variational constitutive updates, finite element discretization, error estimation, constrained problems, time integration algorithms and convergence analysis. There is a strong emphasis on the (parallel) computer implementation of algorithms in programming assignments. The application to real engineering applications and problems in engineering science is stressed throughout the course.

Starts : 2016-09-12
No votes
edX Free English Computer Science Data Analysis & Statistics EdX Engineering MITx

Probability and inference are used everywhere. For example, they help us figure out which of your emails are spam, what results to show you when you search on Google, how a self-driving car should navigate its environment, or even how a computer can beat the best Jeopardy and Go players! What do all of these examples have in common? They are all situations in which a computer program can carry out inferences in the face of uncertainty at a speed and accuracy that far exceed what we could do in our heads or on a piece of paper.

In this data analysis and computer programming course, you will learn the principles of probability and inference. We will put these mathematical concepts to work in code that solves problems people care about. You will learn about different data structures for storing probability distributions, such as probabilistic graphical models, and build efficient algorithms for reasoning with these data structures.

By the end of this course, you will know how to model real-world problems with probability, and how to use the resulting models for inference.

You don’t need to have prior experience in either probability or inference, but you should be comfortable with basic Python programming and calculus.

 

“I love that you can do so much with the material, from programming a robot to move in an unfamiliar environment, to segmenting foreground/background of an image, to classifying tweets on Twitter—all homework examples taken from the class!” – Previous Student in the residential version of this new online course.