Algorithmic Toolbox

DSA or "data structures and algorithms" is what the freshman CS course is called and what you should google. I like Coursera's Algorithmic Toolbox online course, which is free to take if you don't need a certificate. It's part of a 6 course series. I've taken the second one and it's pretty good too.

A great introduction to "computer architecture" and "digital logic" is Charles Petzold's "Code: The Hidden Language of Computer Hardware and Software". It's for a layperson but it doesn't hide away from real concepts.

Aside from that, freeCodeCamp.org is all around good resource for learning theoretical concepts.

Good MOOC on algorithms/data structures?

Hi! What is best way today to take alorithms/data structures course? I had high hopes to coursera new one (https://www.coursera.org/learn/algorithmic-toolbox/home/welcome) and followed but their assigments/quizzes behind paywall now :(((

You shouldn't openly trivialize other people's struggles with a subject. And you should provide resources to those online videos and books. I would recommend these two Coursera classes

https://www.coursera.org/learn/algorithms-part1

https://www.coursera.org/learn/algorithmic-toolbox

as well as the free Python data structures book

http://interactivepython.org/runestone/static/pythonds/index.html

I too am interested. I did the algorithms course offered through Coursera UCSD(https://www.coursera.org/learn/algorithmic-toolbox?specialization=data-structures-algorithms).

Learned quite a bit, I wonder how much harder the GA class is.

Backend Web Development

I'm looking to make a career switch to backend. *My goal is to get a JR Backend Developer job* in San Diego as soon as possible. I have a little experience with front end, OOP with C# in visual studio, and relational dbs. Other than that I'm basically starting from scratch. I'm putting together a gameplan and wanted to get some more input before I dive in.

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Here's what I have so far.

1. Coursera Algorithms course: https://www.coursera.org/learn/algorithmic-toolbox/lecture/EagcP/welcome

2. Accompanied with hackerrank exercises (in C#)

3. Follow Web API Tutorials:

4. https://docs.microsoft.com/en-us/aspnet/core/tutorials/first-web-api?view=aspnetcore-3.0&tabs=visual-studio

5. Database

6. SQL Server Developer

7. Git and GitHub

8. Projects

9. Basic Fitness app: allow user to enter exercises, weight, reps etc and store on backend.

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Here are my questions

1. Right now I'm planning to learn C# ASP.NET core with SQL Server Developer. Are these the best technologies for my goal, or should I choose a different stack?

2. Should I add any concepts to my list?

3. How should I allocate my time to each of these areas?

4. Do you have better tutorials/resources to recommend?

5. How much front end dev do I need to understand?

6. Do you have any other recommendations for me?

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Thanks in advance!

Internship for MS student?

Hi! I am going to start my MS in Statistics (my second MS) this coming fall, and I'm starting to look at internship opportunities for summer 2020. I'm looking for some advice, if you don't mind!

I have no prior industry experience.

For academic experience, I have 2 years of working as a GTA for physics, a small research project on parallel/distributed computing, and a few class projects for an ML class. Starting this fall I'll be a GTA for statistics (my uni is in top 50 for statistics). I've taken undergrad classes on Mathematical Stats, Bayesian Stats, Regression, AI, ML, Data Viz and I'm learning some Algorithms and SQL this summer (there will be certificates). I will be taking graduate classes on Statistical Theory, Statistical Methods, and Multivariate Analysis this fall.

I'm looking at internships in data science, machine learning or research. Is it feasible? What kind of companies/positions should I apply to? Overall, what should I do to improve my chances? Thanks!

https://www.coursera.org/learn/algorithmic-toolbox

"decent programming base"

You know that's pretty laughable, since AP courses in comp sci are pretty useless ever since CSAB was removed... the classes are easy if you do class work in CSP and read the textbook for CSA (the test are literally based off of the online textbook questions), but if you ACTUALLY want to learn any sort of CS you have to seek it elsewhere, my personal recommendation is to start with Algorithmic Toolbox by University of San Diego on coursera. The course is free if you audit (lower right corner, very sneaky) and gives a good general overview of basic CS thinking. There's also the option of Programming Team at our school, a student initiated club that may or may not be offering lessons next year (we haven't decided yet). I'm not advertising or anything, and I'm totally not in the club. pleasejoinweneedmorepeople

Start going on codewars and hackerrank for your languages now and try to solve some problems every day.

When you're ready to dig deeper, try this one - https://www.coursera.org/learn/algorithmic-toolbox

I haven't done the Princeton one, not having the capacity to do multiple courses on the same topic :D I only finished the first 3 modules so far, currently I'm pausing my studies there due to work. Maybe I'll pick up in a month or so.

You can audit the course and look at all the videos and slides for free!

You can read my reviews here and here . Search for "Greg G." :)

It's good practice and good to know this stuff, although it is indeed rarely needed in daily software development practice and some optional proofs are quite heavily math based.

The name of the course is Algorithmic Toolbox by San Diego university on coursera. https://www.coursera.org/learn/algorithmic-toolbox/home/welcome

I start at WGU on Aug 1. So, I can share what I've learned before starting, but I can't confirm that I chose the right things.

At WGU, we need to know Python and Java. I had very little experience with these, but a lot of C++ experience. I went through Udemy Complete Python Developer: Zero to Mastery and YouTube - freeCodeCamp.org - Learn Python - Full Course for Beginners. I am probably going to go through a Java Udemy as well. I used a Udemy 7 day free trial, but after you reach your actual start date, it sounds like we get Udemy for free. (Even between orientation and your start date, you don't have access to it.)

I've also been through a lot of things for Data Structures and Algorithms. Once you have a confirmed start date (or maybe it's once you're through orientation) you have access to coursera for free, or at least most things there for free. I went through U of Cali San Diego Algorithmic Toolbox, U of Cali San Diego Data Structures, and may go through some of Stanford's Algorithms Specialization courses. I've been through some of CS50 as well, and there's definitely overlap which allowed me to go through some of it quite quickly.

I'm probably doing some overkill, but I expect that I'll already know most of C949 DS/A I, C950 DS/A II, and some of C960 DM II (the portion of it that focuses on Big-O.) I'll also note I've heard the coursera courses go more in depth than WGU does.

Daily Algorithm Analysis (Day 2)

Hi guys,

It was awesome seeing everyone participate yesterday. I don't have anything in the resource folder for today's problem but I'll try to compile some useful documentation in a file to share later.

If anyone has any resources they think would be helpful for newcomers in solving this problem, or if anyone has any suggestions at all, let me know.

Onto Day 2!

Rules and Guidelines

- Please wrap code and solutions in spoiler tags when possible.

- Discuss the structure of your code thoroughly and provide an analysis.

- All language implementations are welcome.

- Please do not plagiarize the code of others and give credit where credit is due.

- Please adhere to all other Reddit and r/learnprogramming rules.

- Use the resource section to view the problem if you are struggling to understand the question. Reddit formatting limits the way in which I can post these questions.

- if there are benchmarks, try to meet them. Meeting the program benchmarks is just as important as solving the problem.

Resources:

Algorithmic Toolbox Course

GoogleDrive Folder For Daily Problem Resources

Day 1

Day 2

Today's problem was excerpted from CodeWars. All credit goes to the folks over there for designing the problem.

Polycarpus works as a DJ in the best Berland nightclub, and he often uses dubstep music in his performance. Recently, he has decided to take a couple of old songs and make dubstep remixes from them.

Let's assume that a song consists of some number of words. To make the dubstep remix of this song, Polycarpus inserts a certain number of words "WUB" before the first word of the song (the number may be zero), after the last word (the number may be zero), and between words (at least one between any pair of neighbouring words), and then the boy glues together all the words, including "WUB", in one string and plays the song at the club.

For example, a song with words "I AM X" can transform into a dubstep remix as "WUBWUBIWUBAMWUBWUBX" and cannot transform into "WUBWUBIAMWUBX".

Recently, Jonny has heard Polycarpus's new dubstep track, but since he isn't into modern music, he decided to find out what was the initial song that Polycarpus remixed. Help Jonny restore the original song.

Input:

The input consists of a single non-empty string, consisting only of uppercase English letters, the string's length doesn't exceed 200 characters

Output:

Return the words of the initial song that Polycarpus used to make a dubsteb remix. Separate the words with a space.

Sample:

 song_decoder("WUBWEWUBAREWUBWUBTHEWUBCHAMPIONSWUBMYWUBFRIENDWUB")   
 # =>  WE ARE THE CHAMPIONS MY FRIEND