I'm going to school for computer science fall 2020 and want to learn stuff over this year to prepare. What are some good resources / ways to get started? (I'm currently in my gap year)

Tryna peep this too

it really depends on what language you wanna learn, python/html is p easy to learn but the best way is to "borrow" a programming textbook and go from there if you wanna teach yourself

STEM school or learning yourself.

Congrats. Did CS and stats undergrad. For now I’d enjoy life lol but start with fundamentals in java and python. Tons of courses on Coursera world work. If you have a decent handle on those going into freshman yr you should be good. Stay busy on sites like leetcode. Buy the book cracking the coding interview. Etc.

If you’re feeling to go over and above look into c++ and methodology like big o

Also prep yourself for how time consuming and challenging courses will probably be. I really struggled with abstract/logic courses and data structures. Also try to knock out calculus prereqs asap at a community college or some online program. They’re likely a lot easier than how they are at your future college.

Thanks for the info, what job did you get out of college? With a CS+Stats undergrad that could possibly open the door for machine learning / data science, right?

I'm actually interested in machine learning / ai myself but I'm debating it b/c of the possible need for a masters / phd to be really employable. I'm thinking it might be safest to get my CS degree and focus on internships then just try to get a job at FAANG here in Seattle (Where I'm going to school).

Hi - So are you starting a degree program soon or are you taking a gap year and will resume the program soon?

Starting

You're going to learn a lot of outdated material most likely but it's important to have a foundation.

The best experience you will get is networking and finding a job/internship in the field. You need to get hands on

I'm going to be real with you, college sucks when it comes to preparing you for after college. They're going to have you doing basic s*** in like C++ or Java your whole college career with the only challenges being algorithms which isn't really that challenging because the algorithm is already there you just have to get an understanding of it and put it into code. Youtube, Coursera and Udemy has some s*** you can watch and go along with and even labs you can do to learn the basics.

Pick a language I suggest one of the three:
Python
Javascript / Typescript
Go

And do mini projects and learn as you go by making mistakes and looking up best practices along the way. Do know that these three are vastly different especially Go compared to the other two so don't try to mix and match it can get confusing, on their own their pretty easy to get the hang of. Lastly, I do suggest learning full stack which kind of contradicts my mix and match statement because I doubt you'll be using anything other than Javascript for frontend work, but yea you get my point.

Go Developers make a lot of money currently, and I only see that going up fyi.

Javascript and Python are probably the two currently most popular languages with the best communities. Both of these have very good frameworks for each. If you're looking frontend I use React, but Angular is also a very heavily used framework. If you're looking backend NodeJs for JS. I'm not too familiar with Python but I know Django is big, also Python is heavily used with Machine Learning and AI.

ALSO, one last thing look into other tools to learn and work with the major tools that you'll need to know about and you will almost most definitely be using wherever you go for an internship or after college altogether are Docker & Kubernetes or Serverless. -> This is more of a DevOps thing but still get familiar with these or you'll be so confused by a lot of s*** after school.

Kk, I'm done. In all just make sure you look and learn outside the scope of what college is teaching, but still hold onto and understand the data structures and algorithms because tech interviews are terrible (whiteboard questions should never be a thing, sadly they are) and you'll have to know them if you want a job.

here are two of the textbooks i used in my python classes
drive.google.com/open?id=1cnM9NG7YYqmoG-Babv_BZmoGVM5s69kB

here are two of the textbooks i used in my python classes
drive.google.com/open?id=1cnM9NG7YYqmoG-Babv_BZmoGVM5s69kB

Codecademy worth looking at especially if you’re starting out. They have a CS track that’ll teach u python and data structures.

Try looking at some online tutorial for the simpler stuff.

This includes the below:

1- HTML/CSS
2- PHP
3- Bit of Javascript.
4- C language

Then pick up some online books on the following topics:

1- How internet works.
2- Software development lifecycle.

This will get you up to speed and perhaps put you at an advantage when you start your studies.

Try web development first

For sure happy to help. My major was a joint program between my school’s engineering and stats colleges. Basically my curriculum was a balanced mix of both majors.

I was always interested in stats and data a***ysis on top of cs so it was a good fit for me. Out of school I was def leaning towards big data / data science jobs although those terms can be buzzwords and be very broad. Currently I work at a financial banking company primarily as a data engineer but I’ve built several models too; depends on the workload and what my managers assign me

imo the idea that companies are only seeking higher tier education applicants for data scientist and ML engineer roles has some truth (esp at certain companies/industries - lot of gov positions are phd or bust) but it is also very inaccurate as well. You are going to learn the most on the job and the difference in knowledge between talented undergrad applicants vs. grad students can be small/nonexistent and managers pick up on that fast. If anything talented undergrad students stand out more than grad applicants - a github acct or portfolio with just 2-3 projects (not just school projects) can look better than an entire master’s education. Data science and machine learning aren’t new fields but it’s amazing how basic a lot of programs on them are. If anything schoolwise the biggest bang for your buck will be coming out with a good grasp on linear algebra and statistical probability, along with a solid programming core of classes.

You can easily come out of undergrad with a data science / ML position. It might not be at Airbnb but if you hit the ground running with solid internships during your summers, sky’s the limit.

Since you have a lot of time before school, you should look into companies with data science posititions in your area and email them seeing if you could shadow an employee or team for a day. Might take a few attempts but you could already have an internship waiting for you after your freshman year if you connect well with one of them

For sure happy to help. My major was a joint program between my school’s engineering and stats colleges. Basically my curriculum was a balanced mix of both majors.

I was always interested in stats and data a***ysis on top of cs so it was a good fit for me. Out of school I was def leaning towards big data / data science jobs although those terms can be buzzwords and be very broad. Currently I work at a financial banking company primarily as a data engineer but I’ve built several models too; depends on the workload and what my managers assign me

imo the idea that companies are only seeking higher tier education applicants for data scientist and ML engineer roles has some truth (esp at certain companies/industries - lot of gov positions are phd or bust) but it is also very inaccurate as well. If anything a lot of masters programs are cash cows from foreign students.

You are going to learn the most on the job and the difference in knowledge between talented undergrad applicants vs. grad students can be small/nonexistent and managers pick up on that fast. If anything talented undergrad students stand out more than grad applicants - a github acct or portfolio with just 2-3 projects (not just school projects) can look better than an entire master’s education. Data science and machine learning aren’t new fields but it’s amazing how basic a lot of programs on them are. If anything schoolwise the biggest bang for your buck will be coming out with a good grasp on linear algebra and statistical probability, along with a solid programming core of classes.

You can easily come out of undergrad with a data science / ML position. It might not be at Airbnb but if you hit the ground running with solid internships during your summers, sky’s the limit.

Since you have a lot of time before school, you should look into companies with data science posititions in your area and email them seeing if you could shadow an employee or team for a day. Might take a few attempts but you could already have an internship waiting for you after your freshman year if you connect well with one of them.

research labs and misc campus groups/activities too but still can’t stress enough how much your cs curriculum is likely going to kick your ass. If you’re going to university of washington, congrats again but buckle up. Easier said then done but make a really good habit of going to class and office hours; communicating with your profs; making friends in classes; etc. Gpa also isn’t be all / end all for cs. Anything above a 3.0-3.3 in my book is good imo.

The cs background will open more doors for you so I’d stick with that route. But follow what you want to do.

B****es. Start programming b****es. With tenderness, love and stern direction.

Excellent info, ty

I started programming when I was super young, but over time I’ve found that I learn new things the best by just starting projects (I want to build a program that does x, a site that looks like y, etc etc) and giving myself set due dates to complete the project by. You learn quickly when you have to actually put things into practice instead of just copying exercises from a page.

MOOC >

team treehouse

Learn Python the Hard Way is what taught me how to code. That's how I taught myself when I was 14 and I'm at a point now (19) where I could program anything I want to, from games to websites. I can't stress enough how much it helped me, I seriously believe anyone who wants to learn programming fr should do it this way.
learnpythonthehardway.org/book/intro.html

this too

Teamtreehouse then try to build your own saas app