Many developers enter the market from backgrounds that don’t involve a computer science degree, which can lead to blind spots of how to approach certain types of problems. Gary Bernhardt produces screen casts and articles that aim to teach these principles with code to make them approachable and easy to understand. In this episode Gary discusses his views on the state of software education, both in academia and bootcamps, the theoretical concepts that he finds most useful in his work, and some thoughts on how to build better software.
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- Your host as usual is Tobias Macey and today I’m interviewing Gary Bernhardt about teaching and learning Python in the current software landscape
- How did you get introduced to Python?
- As someone who makes a living from teaching aspects of programming what is your view on the state of software education?
- What are some of the ways that we as an industry can improve the experience of new developers?
- What are we doing right?
- You spend a lot of time exploring some of the fundamental aspects of programming and computation. What are some of the lessons that you have learned which transcend software languages?
- Utility of graphs in understanding software
- Mechanical sympathy
- What are the benefits of ‘from scratch’ tutorials that explore the steps involved in building simple versions of complex topics such as compilers or web frameworks?
Keep In Touch
- Destroy All Software
- Data Structures
- Computer Science
- Programming Bootcamps
- Graph Theory
- Julia Evans
- @b0rk on Twitter
- Allen Downey
- Jupyter Notebook
- Halting Problem
- Visual Basic 3.0
- Set Theory
- ML Family of Languages
- SML, a simple dialect of ML
- SML/NJ, a compiler for SML
- OCamL, a more modern dialect of ML
- F#, an even newer dialect of ML
- Clojure, a modern Lisp-like language
- Lua Grammar (scroll to the very bottom for the full grammar)
- John Carmack
- Twitter Thread Explaining Episode Context