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Registration is open for the January 2018 cohort of “Weekly Python Exercise”

December 7, 2017 . By Reuven

Weekly Python Exercise logoWhen I started to program in Python more than 20 years ago, there weren’t a lot of resources out there. Sure, there were a handful of books, and a few Web sites, and (of course) forums and mailing lists. But that was about it.

Nowadays, Python is white-hot, with companies, universities, and individuals learning the language. Whether you’re a data scientist, Web developer, system administrator, test author, or hobbyist, you’re probably learning Python. Not surprisingly, there are oodles of books, courses, and resources for people learning the language.

And then? Well, then you’re on your own.

The problem is that there aren’t a lot of resources for intermediate-level Python developers to improve their fluency with the language. Sure, you can read through Stack Overflow and Reddit, as well as read blogs and watch conference videos. But given how much is out there for beginners, you would think that there would be something to help people who have already taken a Python course, and who are ready for the next stage.

The good news: I’m here to help.

More specifically: My course, Weekly Python Exercise, is just what the doctor ordered. WPE makes you a more fluent, more knowledgeable Python developer by forcing you to learn and practice your skills every week.

Every Tuesday, you’ll receive a new Python programming challenge. These challenges are designed to be relatively short and small, taking less than an hour of your time. The following Monday, you’ll receive my suggested answer, along with a description of why I chose to solve the problem in the way I did.

Along the way, you’ll learn about — or improve your understanding of — such topics as:

  • nested functions
  • iterators
  • generators
  • decorators
  • object inheritance
  • properties
  • threads and processes
  • the “logging” module
  • the “pickle” module

Most importantly, you’ll be solving these problems along with other developers from around the world. You’ll be able to participate in a forum, in which you can discuss possible solutions. Such interactions are the key to effective, deep learning, and I’m going to do my best to encourage active participation and discussion in our forum.

Moreover, I’ll offer live, online office hours every few weeks. This will give you a chance to ask me about the exercise questions, as well as the solutions. It’s your chance to discuss the exercises in greater depth.

I’m also going to include several multi-week projects, in which successive exercises build on previous ones. This will allow us to build larger projects, while remaining within the constraints of simple, weekly exercises.

This is the second time I’m offering Weekly Python Exercise. I’ve incorporated many suggestions I received from the first set of participants, making this the best way I can think of to improve your Python skills. I’ve improved the exercises, improved the social interactions, and made myself more available to discuss the questions (and answers) with all of the participants.

If you have a good knowledge of Python but want to make it even better, then Weekly Python Exercise is for you. But — and here’s the most important thing — the next cohort will be starting on January 2nd. After that, registration for WPE will be closed.

If you want to level up your Python, now is the time to sign up. I’m not sure when I’m next going to offer WPE, which means that once the course starts, you won’t be able to join.

If you have read a Python book, or taken a Python class, and want to know how to really “get” Python, look no further: Weekly Python Exercise is coming.

Click here to register for the January 2018 cohort of Weekly Python Exercise.

Wondering if WPE is for you? Contact me at reuven@lerner.co.il., and I’ll personally read (and respond to) your question.

If you’re on the fence, and want to sample WPE, you can just enter your e-mail address below, and receive (free of charge) two exercises from the most recent cohort:


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