This is a course to teach basic Python programming skills through data analysis. The book and course materials are all free and licensed as Creative Commons. There is no complex math in the course, the programs are generally quite short, and the workload is no more than a few hours per week. By the time you complete the course, you will understand be able to read, parse, and manipulate data using Python. Hopefully at the end of the course you will like programming well enough to take another course in programming or web development. You can register and launch, take the course, and earn your place on the map at any time and at your own pace
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.
Prose Simiancompleted this course, spending 1 hours a week on it and found the course difficulty to be very easy.
Probably the gentlest introduction to programming for adults possible - so especially suitable for someone who feels a bit intimidated by computers &/programming - with a very helpful forum and a forgiving grading policy. Four stars because although it's well taught - Dr Chuck is really very good at explaining things* - it doesn't cover so much. But the relaxed pace makes it unlikely someone will 'hit the wall'- as can happen in faster-paced courses.
After a bit of Codecademy, Udacity's CS101 & Rice's IIPP - which both ramp up the difficulty more quickly - could be good followups.
*Seriously! He's got a 10 min video about Bayes' Theorem on youtube that finally enabled me to understand how to use it - after explanations in several other MOOC just left me confused.
Robertcompleted this course, spending 4 hours a week on it and found the course difficulty to be easy.
Good course for learning the pure fundamentals for Python. Dr. Chuck is a great instructor and his lectures are certainly not boring.
If you have any previous programming background (even minimally), you may find the first several lessons rather easy and skippable. However, as the course progresses the concepts and particularly the assignments become more and more challenging.
I would definitely consider taking a more advanced Python course from Dr. Chuck.
I've tried (and failed) to learn basic programming in the past. This course was accessible, easy to follow and fun. The lectures and exercises demystify Python and programming in general. Plus Chuck is one of the most entertaining lecturers I've ever had. There were a lot of times when I laughed out loud. Not something I would've expected from a course on programming. Highly recommended.