HealthyStudyBalance

Big O notation is the worst case running time for an algorithm, and is the number of operations it takes to complete based on an input size n

O(1) - constant time - the running time doesn’t change even when the amount of inputs change

O(log n) - the algorithm cuts n in half for each iteration

O(n) - running time is directly proportional to the number of inputs

O(n log n) - algorithm has to look at each element at least once, then there’s an additional step that divides n in half for each iteration. log n! simplifies to n log n

Online lectures:

Discrete Mathematics (x) (x) (x) (x) (x)

Data Structures (x) (x) (x) (x) (and Object Oriented Programming (x) )

Software Engineering (x)

Database (x)

Operating Systems (x) (x) (x) (x) (x) (x) (x)

Structure and Interpretation of Computer Programs (x)

Computer Architecture (x)

Programming (x) (x) (x) (x) (x) (x) (x)

Linear Algebra (x) (x) (x)

Artificial Intelligence (x) (x)

Algorithms (x)

Calculus (x) (x) (x)

Tutorials (programming) and other online resources:

Programming languages online tutorials and Computer Science/Engineering online courses

Java tutorial

Java, C, C++ tutorials

Memory Management in C

Pointers in C/C++

Algorithms

Genetic Algorithms

Websites for learning and tools:

Stack Overflow

Khan Academy

Mathway

Recommended books:

Computer organization and design: the hardware/software interface. David A.Patterson & John L. Hennessy.

Artificial intelligence: a modern approac. Stuart J. Russel & Peter Norvig.

Database systems: the complete book. Hector Garcia-Molina, Jeffrey D. Ullman, Jennifer Widom.

Algorithms: a functional programming approach. Fethi Rabbi & Guy Lapalme.

Data Structures & Algorithms in Java: Michael T. Goodrich & Roberto Tamassia.

The C programming language: Kernighan, D. & Ritchie.

Operating System Concepts: Avi Silberschatz, Peter Baer Galvin, Greg Gagne.

Study Tips:

How to Study

Exam Tips for Computer Science

Top 10 Tips For Computer Science Students

Study Skills: Ace Your Computing Science Courses

How to study for Computer Science exams

How to be a successful Computer Science student

Writing in Sciences, Mathematics and Engineering:

Writing a Technical Report

Writing in the Sciences (Stanford online course)

Good morning, everybody! This morning I was feeling a little down regarding my choice of career: Computer Science. It has always been seen as a man’s line of work, more than a woman’s, and even today women are disregarded in this field. I have even been prejudiced by classmates as the one who doesn’t do her work and lets her partner do it all.

See, I have done approximately a 75% of all the overall work of all the projects (counting individual AND in pairs). I have even done a project that was not mine, to begin with. So, I started to think this morning and I came to realize, this is a woman’s profession more than it is a man’s. Men have taken all the glory in what women have accomplished. I am vastly aware that this is not the only field, of course. But it is the one that bothers me personally most.

I wrote a Twitter thread this morning about the most known women in Computer Science, even if most people don’t even know of their existence. Still, at least one of them rings a bell. As I feel the need to share this with the world, I will be adding it all here. They are not in any particular order, anyway, enjoy.

1. Ada Lovelace

The one and only, Ada. She was the first person to believe computers wouldn’t just compute, but could also have other applications. She created the first computer algorithm despite not being able to try it since the Babbage Engine was not finished. Despite that, she is the world’s most known woman in this field.

Edit: She is also considered the first person to come up with the idea of a loop. Thank you, @a-25!

2. Grace Hopper

An American navy admiral who was also the inventor of the first compiler, and she also executed the first debug. She has had broad recognition, for example, she is one of the first 10 people to be “senior programmers”, and she is the first woman of any nationality and first American to be made a Distinguished Fellow of the British Computer Society.

3. Hedy Lamarr

Oh, you’re going to love her. She is the one who you have to thank for if you use WiFi or GPS. She was a genius and an actress, she was also the first female orgasm on cinematography history.

She was married to a German Nazi and learned about all that they had to say. Further on, she had an American lover who loved to play the xylophone and, as she switched sides, she used the xylophone as inspiration to jump from frequency to frequency within the radio so the Nazis couldn’t catch her as she gave information to the enemy.

4. Margaret Hamilton

You might have seen her standing next to a huge amount of stacked papers, the ones that have the code written by her (and her team) to take Apollo 11 to the moon. Apollo 11 had a critical point in its mission, where the guidance computer started turning in errors and had to postpone some tasks that could not be attended in real time. Margaret, with the help of her team, created the asynchronous flight software. She was also CEO of her co-founded business HOS (High Order Software).

She is still alive to this day and she is also still being recognized, the last thing on her Wikipedia dates to this past April.

5. Joan Clarke

Have you ever heard of Alan Turing? She is the only woman who worked in his team at Bletchley Park. She reached deputy head at some point, but because of her gender, she wouldn’t reach any higher and would be paid less than her other mates. Side note: Alan Turing proposed to her although he had admitted his homosexuality to her. Long after he died, she worked for GCHQ (Government Communications Headquarters).

If you’d like to learn about more women in computing, you can see a timeline on this link: https://en.wikipedia.org/wiki/Women_in_computing.

I would like anyone who reads this to please stop stereotyping this field as a man’s line of work. Women like the ones above need to be given the chance to shine in Computer Science.

29.05.17 • day 1/30

here’s the first page of my June spread and some bio notes I did today!!

will be aiming to achieve 30 days of productivity starting from today in preparation for mid-years right after June break ;-;

I was asked to make a masterpost on websites like Codecademy, so I’ve tried to compile a list of the best (and mostly free!!). In no particular order: 

1. Codecademy [x]

I couldn’t not include Codecademy! Just in case you haven’t checked it out, it’s pretty neat. It has courses for learning languages and web developer skills.

Languages: Python, Ruby, Java, PHP, jQuery, JavaScript, HTML/CSS

Extras: Git, SQL, Command Line, AngularJS, Ruby on Rails

2. Code School [x]

This is pretty similar to Codecademy with the in-browser coding and such. It also has additional features like teaching videos. A good introduction to programming languages.

Languages: Python, Ruby, Javascript, HTML/CSS

Extra: iOS development with Objective-C or Swift, Git, SQL

3. Learnaroo [x]

Has tutorials followed by mini challenges based on the concepts you’ve just learnt! It also has some reference pages called “Learn x by Example”. Looks pretty good.

Languages: Python, Java, Ruby, HTML/CSS

Extra: Algorithms, Mathematics, + a bunch of premium membership stuff

4. Learn … 

A set of related websites (see below) which have mini tutorials on language concepts followed by mini challenges, similar to Learnaroo.

Languages: Python, Java, C, C#,  JavaScipt, PHP, Shell

5. Code Combat [x]

Basically, it turns learning to code into a game! As you move through the levels, new concepts are introduced, so the code you need to write to play the game gets harder. 

Languages: Python, Java, JavaScript, CoffeeScript, Clojure, Lua

6. Codingame [x]

Similar idea to Code Combat, but a little more advanced. 

Languages: Python, Java, Ruby, C, C++, C#, Haskell, VB … there’s actually loads it supports.

7. Code Wars [x]

This is more for ‘training’ with a language you already know. It offers plenty of practice through challenges, so it’s really good for improving your coding skills. 

Languages: Python, Ruby, Java, C#, Haskell, JavaScript, CoffeeScript, Clojure

8. Coderbyte [x]

This offers some video tutorials and challenges for a few languages, plus special courses on specific algorithms and bootcamp/interview prep. You need a premium membership for quite a lot of things, though (e.g. I don’t think you can watch any of the videos with a free membership).

Languages: Python, Ruby, JavaScript

Extras: Algorithms, Bootcamp Prep, Job Interview Prep

9. Free Code Camp [x]

Mini tutorials followed by mini challenges. Has a number of courses on the languages below!

Languages: HTML/CSS, jQuery, JavaScript

Extras: Git, Algorithms, + a bunch of projects to complete

10. Programmr [x]

Has courses to learn various languages through doing little exercises/challenges in the browser, similar to previous examples. Also has ‘zones’ for more languages, where you can find challenges, example code and projects people have shared. 

Languages: Python, Java, C++, C#, PHP, jQuery

11. CheckIO [x]

Only offers Python, but I still think it’s really great. You move from level to level, getting challenges which are gradually trickier. Learn by doing!

12. Rails for Zombies [x]

For people who already know a bit of Ruby, but nothing about Ruby on Rails!  Each level begins with a short video followed by interactive challenges where you program Rails in the browser.

Notetaking

Sound Note - take notes while you record audio

Evernote - notetaking that syncs across platforms

Paper 53 - minimal notetaking that syncs

Microsoft OneNote - collaboration and syncing, best for Office users

Google Keep - jot things down, best for Google suite users

Notability - take notes and annotate PDFs

Mindly - create mind maps

Day One - a digital journal

Flash Cards

Quizlet - the quintessential flash card app

StudyBlue - another commonly used app

Cram - best for its “cram mode”

Eidetic - uses spaced repetition for effective memorization

Planner 

My Study Life - schedules, tasks, reminders, and more

StudyCal - keeps track of tasks, exams, and grades

24me - automated reminders and event planning

iStudiez - schedule and prioritized task list

Google Calendar - a calendar, best for Google users

Glass Planner - a calendar and to do list with incredible functionality

To Do List

Clear - organized to-do and reminders

MinimaList - simple to-do and focus timer

Trello - collaborative project organizer

Todoist - clean and functional task manager

Default notes app on your phone

Time Management

Forest - plant trees by staying focused

Pomotodo - pomodoro timer with to-do list

Timeglass - custom timers

Tide - pomodoro with white noise

Alarmy - forces you out of bed 

Pillow - smart alarm that tracks sleep cycles

Productivity

Workflow - automate tasks

Habitica - turn your habits into an RPG

Continuo - simple, colorful activity tracking

Freedom - block distracting apps

Free Learning

Coursera - free MOOCs

TED - listen to Ted Talks

Duolingo - language learning

Memrise - spaced repetition language vocabulary

Khan Academy - free video lessons

Ambient Noise

8tracks - curated playlists

Spotify - online music streaming

Coffitivity - cafe ambience

Noisli - background sound generator

Rain Rain - rain sounds

Binaural - binaural beats

Health

Rockin Ramen - recipes based on ramen

MealBoard - meal planning

Lifesum - healthy eating

Stop Breath And Think - mindfulness meditation

Pacifica - mental health management

Sworkit - personalized video workouts

Waterlogged - hydration tracker

Reference

WolframAlpha - Google on steroids

Oxford Dictionary - all of English at your fingertips

RefMe - citation generator

PhotoMath - solve math problems by taking a photo

Mathway - step by step math help

Desmos - free graphing calculator

Wikipedia - not the best source, but it’s handy

Miscellaneous 

Companion - stay safe when walking alone

Mint - money management

Toshl - finance manager

Here are some reminders to myself. Hopefully, they are also helpful to some freshmen or anyone who’s curious:

1. University is not school.

You can’t shilly-shally around, take your sweet time and expect to just roll with it. Trust me, you will be in for a rude awakening. Find a goddamn studying method early in and stick with it. Flashcards and quizlets, whatever works for you. The deadlines and exams will draw closer faster than you think they will.

2. Your profs are not decoration.

Ask. Questions. Seriously. And go to office hours if you have any particular problem to resolve. Make use of that time. A lot of them will actually be thankful anyone is showing up. Against popular belief, professors indeed do make a mental note of a lot of their students. Don’t be one of those 20 people standing infront of their office for the first time a week before the exam.

3. Get as much work as possible done until noon.

It’s 12 and you have already studied for three and a half hours? Amazing. Look, I know, I am not a morning person either. But at least try it out. Get your sleep schedule in check. It will feel so much better than to procrastinate until evening and then you HAVE to do it anyway.

4. If you can explain it, you have understood it.

Done studying? Bet you’re not. Try explaining yourself the material loudly like teaching it to a clueless person. Or get yourself a study buddy and explain your subjects to each other. It’s even better if you don’t have the same majors. If you are able to explain the topic and have the other person understand it, you actually know the topic. If not, you now know where the shoe pinches. It’s also great practice!

5. You may feel a bit lonely at first.

Okay, I don’t want to scare anyone. I did find a lot of friends. Especially at first, everyone is your friend. Because everyone is scared of missing the boat and feeling left out. There will be so many people around you. Still – or maybe that’s the reason – you will probably feel a bit lonely at first. I want to tell you that this is normal. It’s because everyone is still a stranger to you and maybe you’ve just moved out! Maybe you are far away from home for the very first time. I’ve struggled with this. That’s fine! Everything will be fine. You will feel at home eventually.

8.6.19

So i just realized i never posted these here… oops

🌸  05.08.19  🌸

I don’t have any experience in machine learning (I do a machine learning unit in a year and a half), but I’ve found what I can through other people’s recommendations. Most of these require knowledge/proficiencies with python so you should be okay with that first. 

machine learning with python 3 (reddit thread)

link: https://www.reddit.com/r/learnprogramming/comments/cfxxcd/machine_learning_get_started_with_python/

This is a series of videos suggested by someone with more experience which teach the basics of machine learning, with python! I believe you’d have to have a python understanding first to understand this. Python 3 to be specific.

stanford coursera online machine learning course {PAID}

link: https://www.coursera.org/learn/machine-learning

I’ve heard some good things about courser courses, however I have not tried them myself. You can display the certificate of completion on your LinkedIn profile, so that’s a bonus. 

code academy w/ python {PAID… unless you speed run it}

link: https://www.codecademy.com/learn/machine-learning

I’ve sung my praises of code academy before and I’ll do it again. This is another python machine learning course under the code academy PRO feature. This has a monthly/six monthly/annual fee, but is free for your first week when you sign up. So… theoretically you could sign up and try to speed run the whole course in 7 days if you’re up to it.