ABOUT 6.00X
Introduction to Computer Science and Programming
6.00x is an introduction to using computation to solve real problems. The course is aimed at students with little or no prior programming experience who have a desire (or at least a need) to understand computational approaches to problem solving. Some of the people taking the course will use it as a stepping stone to more advanced computer science courses, but for many, it will be their first and last computer science course.
Since the course will be the only formal computer science course many of the students take, we have chosen to focus on breadth rather than depth. The goal is to provide students with a brief introduction to many topics so they will have an idea of what is possible when they need to think about how to use computation to accomplish some goal later in their career. That said, it is not a “computation appreciation” course. It is a challenging and rigorous course in which the students spend a lot of time and effort learning to bend the computer to their will. Those who earn a passing grade will get an honor code certificate from MITx.
PREREQUISITES
High school algebra and a reasonable aptitude for mathematics.
COURSE STAFF
John Guttag
Professor Guttag is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT. He leads the Computer Science and Artificial Intelligence Laboratory’s Data Driven Medical Research Group. The group works on the application of advanced computational techniques to medicine. Current projects include prediction of adverse medical events, prediction of patient-specific response to therapies, non-invasive monitoring and diagnostic tools, and tele-medicine. He has also done research, published, and lectured in the areas of data networking, sports analytics, software defined radios, software engineering, and mechanical theorem proving.
Professor Guttag received his bachelors degree in English and his master's in applied mathematics from Brown University. His doctorate is from the University of Toronto.
From January of 1999 through August of 2004, Professor Guttag served as Head of MIT’s Electrical Engineering and Computer Science Department. He is a Fellow of the ACM and a member of the American Academy of Arts and Sciences.
Chris Terman
Chris Terman is a Senior Lecturer in the MIT Department of Electrical Engineering and Computer Science and a Principal Investigator at the MIT Computer Science and Artificial Intelligence Laboratory. Chris does research in the area of digital systems, computer-aided design tools and interactive educational technology for design-oriented courses. For the past four decades, he has been an award-wining teacher in computer science, mainly in the area of digital systems and their applications, including participating in MITx's inaugural course on Circuits and Electronics.
Chris received his BA in Physics from Wesleyan University and headed to MIT for graduate school in 1973. He completed his MS, EE and PhD degrees in Computer Science and Engineering and subsequently joined the MIT EECS faculty. Chris escaped from MIT in 1985 and was a cofounder of several firms, including Symbolics Inc. (manufacturer of Lisp Machines), TLW Inc. (VLSI designs for communications and multimedia), and Curl Co. (software technology for the Web). He returned to MIT in 1995 and subsequently participated in the design of the Ray and Maria Stata Center, CSAIL's home, and has served as Associate Director and later Co-Director of CSAIL.
Eric Grimson
W. Eric L. Grimson is the Chancellor of the Massachusetts Institute of Technology, a professor of computer science and engineering, and the Bernard M. Gordon Professor of Medical Engineering. He was named Chancellor of MIT in 2011.
A member of the MIT faculty since 1984, Professor Grimson previously served as head of the Department of Electrical Engineering and Computer Science, as its associate department head, and as its education officer. Professor Grimson is internationally recognized for his research in computer vision, especially in applications in medical image analysis. He and his students have developed techniques for activity and behavior recognition, object and person recognition, image database indexing, image guided surgery, site modeling, and many other areas of computer vision.
Professor Grimson has been actively engaged with students throughout his career. For 25 years he lectured subject 6.001 Structure and Interpretation of Computer Programs, and is now engaged in teaching 6.00 Introduction to Computer Science and Programming and 6.01 Introduction to EECS. He has also taught undergraduate subjects in computer architecture, software engineering, and signal processing. In all, Professor Grimson has taught more than 10,000 MIT undergraduates and served as the thesis supervisor to almost 50 MIT PhDs.
Professor Grimson is a native of Saskatchewan, Canada. He received the BSc (Hons) degree in mathematics and physics from the University of Regina in 1975 and his PhD in mathematics in 1980 from MIT. He is a recipient of the Bose Award for Excellence in Teaching in the School of Engineering at MIT. He is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and a fellow of the Institute of Electrical and Electronics Engineers (IEEE).
FREQUENTLY ASKED QUESTIONS
What type of computing environment do I need for this course?
You need to have a computer running one of the following operating systems:
- Microsoft Windows, version XP or greater (XP, Windows Vista, or Windows 7)
- Apple OSX, version 10.2 or greater
- Linux - most distributions that have been released within the past two years should work
What is the format of the class?
The class will consist of lecture videos, which are broken into small chunks, usually between eight and twelve minutes each. Some of these may contain integrated "check-yourself" questions. There will also be programming assignments and standalone exams/quizzes, which are not part of the video lectures.
How can I learn more about the course content?
Please watch the video on this page that we recorded especially for this offering of the course.
Will the text of the lectures be available?
Yes, transcripts of the course will be made available.
Do I need to watch the lectures live?
No. You can watch the lectures at your leisure.
How much does it cost to take the course?
Nothing: the course is free. The recommended textbook will not be free, and will be announced and published at least a week before class starts. There will be free online alternatives to buying the textbook, if you prefer that option.
What programming language(s) will this course use?
6.00x will be using the Python programming language, version 2.7. You are not expected to have any prior programming knowledge - this course is intended for students who have little to no experience with any programming language.
If you have any questions about edX generally, please see the edX FAQ.
If you have any further questions about 6.00x that are not answered in this or the edX FAQ, please email mit-600x@edx.org.
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