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CS 61B Data Structures, Spring 2023 UC Berkeley

sp23.datastructur.es

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Re: CS 61B Data Structures, Spring 2023 UC Berkeley

#21

Post by Myrmornis »

noobdev9000 wrote: post #16

Is there a point for working programmer to learn these in 2023, rather than just treating them as abstract interfaces?

Much of the industry uses algorithm and data structure problems as a way of assessing "smartness" in interviews -- the idea is that even though it's often not needed for the job, giving people the challenge of learning that area at the intersection of computer science and software engineering correlates with how strong a contributor they'll be. I.e. if you don't know it but can pick up an area like that, that's a good signal. So a course like this (doing all the homework exercises) would definitely help with interviewing and getting jobs that people are competing for, if that is something that interests you.

The actual content in this data structures course obviously will mostly not appear in any interview, but the homework exercises will make you stronger in a way that is definitely desirable for interviews. And of course, interviews aside, it will all be interesting for anyone that has an intellectual interest in software engineering.

Re: CS 61B Data Structures, Spring 2023 UC Berkeley

#24

Post by SinePost »

mailey wrote: post #22

speaking of, are there any benefits/disadvantages of learning data structures in java/python compared to C/C++ ?

This spring, I completed a data structures course at a large state school. We used Java at our university because Princeton did, and I imagine Princeton did because of the ease of segmenting concepts into classes because Java bytecode is the same between the students' devices and the machines which were used to grade their assignments (our grades were determined as a fraction of the number of test-cases our code would pass).

Re: CS 61B Data Structures, Spring 2023 UC Berkeley

#25

Post by specialist »

Myrmornis wrote: post #21
noobdev9000 wrote: post #16

Is there a point for working programmer to learn these in 2023, rather than just treating them as abstract interfaces?

Much of the industry uses algorithm and data structure problems as a way of assessing "smartness" in interviews -- the idea is that even though it's often not needed for the job, giving people the challenge of learning that area at the intersection of computer science and software engineering correlates with how strong a contributor they'll be. I.e. if you don't know it but can pick up an area like that, that's a goo…

Just like with dating preferences, leet code interviews are merely a fast rejection heuristic. Because there needs to be some kind of filter. And we haven't found any better.

If we took more time, with dating and interviewing, we'd probably find a lot more diamonds in the rough. But ain't nobody got no time for all that.

Re: CS 61B Data Structures, Spring 2023 UC Berkeley

#26

Post by pigsinzen »

bloemheuvel1 wrote: post #9

could somebody explain how to recreate his coding environment in sublime text? looks very nice for learning and following along.

> in sublime text?

Not sure if you're under the impression that he is using Sublime Text or we're looking at different editors. In the video from his second class, it looks like he is using a Jetbrains[0] product.

[0] https://www.jetbrains.com/

Re: CS 61B Data Structures, Spring 2023 UC Berkeley

#27

Post by papaver »

noobdev9000 wrote: post #16

Is there a point for working programmer to learn these in 2023, rather than just treating them as abstract interfaces?

the difference is using tools vs building your own tools when you need to. the idea of these algorithms is not to memorize them but to understand how they are build and what goals they are trying to accomplish. understanding of the basic building blocks allows approaching and solving problems in a different light.

Re: CS 61B Data Structures, Spring 2023 UC Berkeley

#28

Post by ericjmorey »

blagie wrote: post #15

Here's my question: This seems wonderful for 2010. It's 2023. We have 3B1B, SoME, Python Tutor (which now does many languages), and various types of fairly smart tools to support kids as they're coding (e.g. Jupyter/Pluto-notebook style system, ones like Khan Academy, and ones with a split pane). Has this progress been applied to algorithms? If not, why not?

I don't understand what your question is? How is the 2023 course material taught at UC Berkeley being publicly accessible not exactly the thing you're asking about?
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