Introduction to Computer Science and Programming Using Python
Computational Thinking using Python,
This course is the first of a two-course sequence: Introduction to Computer Science and Programming Using Python, and Introduction to Computational Thinking and Data Science. Together, they are designed to help people with no prior exposure to computer science or programming learn to think computationally and write programs to tackle useful problems. Some of the people taking the two courses will use them as a stepping stone to more advanced computer science courses, but for many it will be their first and last computer science courses. This run features lecture videos, lecture exercises, and problem sets using Python 3.5. Even if you previously took the course with Python 2.7, you will be able to easily transition to Python 3.5 in future courses, or enroll now to refresh your learning.
Since these courses may be the only formal computer science courses 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, they are not "computation appreciation" courses. They are challenging and rigorous courses in which the students spend a lot of time and effort learning to bend the computer to their will
What you'll learn
- A Notion of computation
- The Python programming language
- Some simple algorithms
- Testing and debugging
- An informal introduction to algorithmic complexity
- Data structures
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| Rating | 4.5★ based on 166 ratings |
|---|---|
| Length | 9 weeks |
| Effort | 9 weeks, 14–16 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $75 |
| From | Massachusetts Institute of Technology, MITx via edX |
| Instructors | Eric Grimson, John Guttag, Ana Bell |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Science |
| Tags | Computer Science Engineering Science |
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What people are saying
computer science
This is a well-crafted, fast-paced introduction to Computer Science, though a little dry at times.
It covered a wide range of lessons needed for computer programming and would recommend it for anybody who wants to learn computer science.
This is an excellent introduction into Computer Science using Python.
Very good introduction to computer science.
6.00.1x taught me many areas of computer science that I did not previously think about which I found quite nice.
This was an excellent course, half of a first course in computer science covering basic algorithmic thinking, functions, loops, recursion, debugging, searching and sorting, orders of growth, object-oriented programming and trees.
This is less of a programming course than it is a computer science course, because a lot of programming details (syntax, built-in functions, etc) is only briefly mentioned and you're expected to do some research yourself using the Python documentation, etc.
This was an excellent and rewarding course to take, but it definitely leans more towards the theoretical, math-heavy side of computer science.
MITx has now split its introduction to computer science and programming into two consecutive seven-week courses.
I never had any formal education or training in computer science before this course.
My only training before this course was self-taught, and I only focused on programming language syntax instead of computer science and problem solving abilities.
Fortunately for me, I had reviewed most of the course's content through MIT's OpenCourseWare class "Intro to Computer Science and Programming" (6.00SC).
In my personal opinion, an introductory background in Python and computer science is recommended for this course but is not required.
Python, and it covers topics that are essential but fundamental into computer science.
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eric grimson
The class is somewhat medium-to-hard to follow and requires quite an attention and regularity of attendance (it's an esteemed MIT after all) but presenters and authors MIT's Professors John V. Guttag, Eric Grimson and Ana Bell did an extraordinary job of making a learning curve as gentle and pleasant as humanly possible.
Personally, to me it's the very Eric Grimson's teaching style which kept me going.
I guess,what makes this course even more interesting is that it's being taught by former MIT Chancellor Prof. Eric Grimson.
The videos and slides available are a wonderful resource, Eric Grimson explains everything very well.
Eric Grimson is fantastic and provides very intelligible presentations for the material.
Because of this course, I started learning Python instead of R. I had no background in computer science or programming, but it was not hard to get a high grade in the course since lectures and explanations are excellent, prof. Eric Grimson is an amazing lecturer.
The instructor, Prof. Eric Grimson, is talented and organized.
+Eric Grimson not only teaches how to program but also teaches you in and out and why and how of python programming !!!
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problem sets
The exercises and the problem sets bear very little relationship to the lectures.
The problem sets were thorough, and the structure of presentation and evaluation made it so that I didn't slack off.
CONS: \- There were a few errors in the lectures and some very ambiguous wording in the problem sets, but most of the time the course staff took an attitude of "we're always right and you're probably just doing it wrong" towards the students.
\- I have to mention it again: some of the problem sets, exams, exercises, etc.
I spent the 12 hours per week on average, and spent a lot of time on the problem sets and quiz.
I enjoyed this course specially problem sets that I consider are challenging and very useful.
The problem sets are difficult, challenging and rewarding.
And lastly do not leave problem sets for the last minute, start working on them as soon as they get released.
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for someone
Okay, so for someone who has never coded, and wants to learn to program, you can safely assume this is the best course, yet the hardest out their.
Even for someone who has programmed for a year or so, this course can be tough.
I undoubtedly recommend this course for someone who wants to improve his/her knowledge at programming because it uses a really easy to learn programming language, i.e.
However, it can result a little difficult for someone who has no previous experience at programming.
I've tried, i really did, but for someone, who has no prior programming skills and not a huge amount of time (and willpower!
I'd say it is a challenging course especially for someone with not prior Python or coding experience.
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programming language
* Python is a great programming language for new computer programmers since its syntax is very easy to learn.
I am working as a software developer in a software house and my objective to take this course is to refresh my knowledge and to learn a new programming language.
Also, the choice of programming language, Python, turned out to be an interesting, a less intimidating and a valuable tool for me to enter in this area.
An excellent introduction to Computer Science concepts illustrated using the Python programming language.
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every week
This is not the easiest introductory course i have seen.This is an MIT introductory course.This mean you have to try hard to complete it.I was familiar with python and it took me 3-4 hours at least per week to complete the homeworks.I suppose that guys with no prior knowledge would need even a full day every week.
If you are not familiar with programming and you don't have a lot of time every week,then maybe there are other programming courses more suitable for you than this.
It's a fairly demanding course with a homework assignment every week which took me between 4 to 10 hours each.
On average I spent 20 to 30 hours on it every week.
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homework assignments
* The homework assignments are both rigorous and fun.
This would not normally be a disadvantage, however almost all the homework assignments are the same.
This was a new topic for this course and no homework assignments were given in this topic.
Homework assignments and exams had tight schedules.
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Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
Software Engineer R & D $87k
R&D Software Engineer 2 $94k
Software Engineer, R&D $101k
Software R&D Engineer $105k
Engineer- Software $111k
C/C++ Software Engineer $112k
Software Engineer (R&D) $116k
Engineer, Software $121k
Engineer Software 2 $124k
Engineer - Software $133k
Software Engineer (Eng. Software R&D) $134k
Software Engineer (C++) $251k
Reviews
Sorted by most helpful reviews first
Guest says:
Great. The profs in this course get very deep into the basics. A big part of CS is understanding the foundations and this course does it. I'm into data analysis and the sections on algorithms and data were really helpful for advancing my goal. I was split between this class and CS50 (from Harvard) since CS50 covers C. However, after taking 6.00x I'm very happy and even bought a verified certificate to put in my resume.
Guest says:
Hands down, this is one of the best courses to learn programming. I took AP computer science in high school and really didn't get a strong grasp of things like big o notation and understanding why some sorts are better than others. It wasn't my teacher's fault necessarily, but I think juggling Java and fifty other things is hard. Python makes it a bit easier. The way 6.00x builds on that foundation and takes it even further is what's really impressive. I took this course to refresh my CS knowledge, but I've found more than a few occasions where I use it in my personal and work life. I hope one day MIT will release a sequel for this class to do even more with CS (like building standalone applications / games with Python). Also I wish they would teach more about using external libraries, but that's easy enough to figure out on your own. Still, A+ for MIT!
Guest says:
Best introduction to CS ever, but very challenging. Worth spending 4-8 hours doing homework each week.
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| Rating | 4.5★ based on 166 ratings |
|---|---|
| Length | 9 weeks |
| Effort | 9 weeks, 14–16 hours per week |
| Starts | On Demand (Start anytime) |
| Cost | $75 |
| From | Massachusetts Institute of Technology, MITx via edX |
| Instructors | Eric Grimson, John Guttag, Ana Bell |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Science |
| Tags | Computer Science Engineering Science |
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