And nice to meet you. I'm writing to follow up with some questions and thoughts, some of which I touched on with you briefly when we talked afterward.
About This Course Let's start with the strategic goals of this course: Help students who may or may not intend to major in computer science to feel justifiably confident of their ability to write small programs. Map scientific problems into computational frameworks.
Position students so that they can compete for jobs by providing competence and confidence in computational problem solving. Prepare college freshmen and sophomores who have no prior programming experience or knowledge of computer science for an easier entry into computer science or electrical engineering majors.
Prepare students from other majors to make profitable use of computational methods in their chosen field. Learning a language for expressing computations—Python Learning about the process of writing and debugging a program Learning about the process of moving from a problem statement to a computational formulation of a method for solving the problem Learning a basic set of "recipes"—algorithms Learning how to use simulations to shed light on problems that don't easily succumb to closed form solutions Learning about how to use computational tools to help model and understand data 6.
Once you acquire this skill, your first instinct when confronted with many tasks will be to write a program to do the task for you.
Said another way, we want to help you learn to apply computational modes of thought to frame problems, and to guide the process of deducing information in a computational manner. This means that the primary knowledge you will take away from this course is the art of computational problem solving.
Unlike many introductory level courses, having an ability to memorize facts will be of little help in 6. This course is about learning to solve problems, not learning facts. This, by the way, is exactly why all exams are open book. Prerequisites and Preparation This course is aimed at students with little or no prior programming experience but a desire to understand computational approaches to problem solving.
Now, by definition, none of you are under-qualified for this course. In terms of being over-qualified — if you have a lot of prior programming experience, we really don't want you wasting your time, and in this case we would suggest that you talk to me about how well this class suits your needs, and to discuss other options.
In addition, we want to maintain a productive educational environment, and thus we don't want over-qualified students making other students feel inadequate, when in fact they are only inexperienced.
Since computer programming involves computational modes of thinking, it will help to have some mathematical and logical aptitude. You should be confident with your math skills up to pre-calculus.
Textbook The original textbook for 6. The book is NOT required. We will not be referring to it in assignments or depending upon it to cover holes in the lectures. Introduction to Computation and Programming Using Python. A second edition of the textbook is now available.
However, there may be some discrepancies between the original course lectures included on this course site and the sections in this second edition of the textbook. Introduction to Computation and Programming Using Python: With Application to Understanding Data.
If you choose not to purchase the textbook, you will probably find it useful to buy or borrow another book that covers Python. You might check your local public library's resources, or search online for a free Python text, such as How to Think Like a Computer Scientist or Online readings will be posted on the appropriate session pages.
A more complete list of readings and references not all of which are specifically assigned during lectures can be found in the References section. Technical Requirements Since one of the goals of this course is to become familiar with programming, you will need to install and use the Python programming language and the interpreter IDLE.
Please see the Software section for information and instructions on downloading the required software. Most lectures involve programming demonstrations, and the code involved will generally be posted twice: Additionally, many problem sets have accompanying code required for completing the assignment, and these are posted as.
If you do not have the software installed, you will not be able to properly open and use these files. We would also like to thank Eric Grimson for his role in the development of 6.Watch video · Dear Internet Archive Supporter, I ask only once a year: please help the Internet Archive today.
MIT Introduction to Computer Science and Programming, Fall Movies Preview MIT Introduction to Computer Science and Programming, Fall by MIT OpenCourseWare.
Publication date Are there answers available to the problem sets in the MIT open course: Introduction to Computer Science and Programming? In what order do I have to learn and watch the computer science course on MIT OpenCourseWare?
Ask New Question. Still have a question? Ask your own! Ask. » MIT OpenCourseWare» Electrical Engineering and Computer Science» Introduction to Algorithms (SMA ), Fall Calendar The calendar below provides information on the course lecture (L) and recitation (R) sessions.
Home > Courses > Electrical Engineering and Computer Science > Nonlinear Programming. Syllabus. Help support MIT OpenCourseWare by shopping at rutadeltambor.com! MIT OpenCourseWare offers direct links to rutadeltambor.com to purchase the books cited in this course. This free OpenCourseWare is offered through the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), but would be beneficial for students in other fields of study as well. This course is the header course for the MIT/EECS Engineering Concentration of Theory of Computation. You are expected to have taken Structure and Interpretation of Computer Programs and J / J Mathematics for Computer Science, and received a grade of C or higher in both classes.
Event: Academic Organisations» OpenCourseWare Consortium» MIT OpenCourseWare» MIT Introduction to Computer Science and Programming - Fall MIT Introduction to Computer Science and Programming - Fall MIT_OCW_introduction-to-computer-science-and-programming-in-python-fall MIT OCW Introduction to Computer Science and Programming in Python Ana Bell, Eric Grimson, and John Guttag.
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