Dabeaz – Advanced Programming with Python 2025-8
English | Tutorial | Size: 3.92 GB
I’ve been programming for more than 30 years and naturally that might give you the impression that I’ve figured everything out–you would be mistaken. This course is a pragmatic journey into interesting and useful things I’ve learned about problem solving, programming, testing, and design. It’s also a course about current programming topics I am still learning about in relation to all of those things. Ultimately, it’s a course about making better software, but also embracing the idea of being flexible and writing code for the future.
Major subjects include data abstraction, layering, object-orientation, functional programming, event-driven systems, problem modeling, testing, and lightweight program verification techniques. However, a greater theme of the course concerns the idea of “composibility.” Much of what we do in modern programming isn’t driven by the need to code low-level algorithms. Instead, we often need to pull existing components together to form greater systems. When doing this, it’s useful to think about how the parts interact and how our design choices might have a far-reaching impact on the whole. Ultimately, the goal is to manage software complexity and to make informed choices in your own projects.
Why Would I Take This Course?
There are many books, courses, and tutorials that focus on “Advanced Looking” programming. These are typically focused on understanding isolated (and often esoteric) programming language features, libraries, and frameworks. That is NOT the focus of this course. Instead, our focus is on advanced programming concepts and asking deeper questions about the practice of programming itself. The ultimate goal is to write software that looks simple because some thought has been put into it.
Target Audience and Prerequisites
This course is aimed at programmers who want to improve their coding of larger libraries and applications. Much of this involves thinking about “big picture” issues about how the parts of such systems are put together, how they can be tested, and more. Because the course is taught in Python, you should be comfortable using Python’s builtin types, writing functions, and defining simple classes. It is not necessary to have deep knowledge of “advanced” Python features. I also assume general knowledge of common data structures and algorithms as might be covered in a typical “algorithms” course.
Instruction Format
This course is heavily focused on hands-on programming and group discussion. The course consists of approximately 10 coding projects that explore different facets of programming, problem solving, and design.
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