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Resources for learning Computer Information Systems topics
https://github.com/willisman31/Awesome-CIS-Resources

List: Awesome-CIS-Resources

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Resources for learning Computer Information Systems topics

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# Awesome-CIS-Resources



This is a list of free Computer Information Systems resources.  The full scope of this list ventures outside the realm of CIS, but all of them should be interesting and useful to other students. Support open source projects by donating or contributing whenever possible! 



* [Information Security](https://github.com/willisman31/CIS-Resources/tree/main/InfoSec)

* [Web Development](https://github.com/willisman31/CIS-Resources/tree/main/Webdev)

* [Programming](https://github.com/willisman31/CIS-Resources#programming)

* [Systems Development](https://github.com/willisman31/CIS-Resources#systems-development)

* [Cloud Computing](https://github.com/willisman31/CIS-Resources#cloud-computing)

* [Databases](https://github.com/willisman31/CIS-Resources#databases)

* [Artificial Intelligence](https://github.com/willisman31/CIS-Resources#artificial-intelligence)

* [News](https://github.com/willisman31/CIS-Resources#news)

* [Certifications](https://github.com/willisman31/CIS-Resources#certifications)



If you are enrolled in a large school or university, you likely have a subscription to O'Reilly books included; this is a yearly subscription which offers access to thousands of books, videos, and other technical study resources. If you are a current student, you can check for access [here](https://learning.oreilly.com/home/) and sign in with your university credentials.



## Programming



### Practice



* [Coderbyte](https://coderbyte.com)

* [Codewars](https://www.codewars.com/)

* [Codingbat](https://codingbat.com/java)

* [Github's Learn to Code Collection](https://github.com/collections/learn-to-code)

* [HackerRank](https://www.hackerrank.com/)

* [Leetcode](https://leetcode.com/)

* [Repl.It Online IDE](https://replit.com/)



### Containers



Containers are used as a means of providing a consistent environment for distributed applications.  What this means is that a container contains an app and all the dependencies that app needs to run on the kinds of systems in which it is expected to be used.  If you're familiar with the concept of a virtual machine, containers are very similar.  Docker is the most common container engine, but it has fairly recently become a paid service.



* [Containerd](https://containerd.io/docs/)

* [Docker Handbook](https://www.freecodecamp.org/news/the-docker-handbook/)

* [Podman](https://podman.io/)



### C#



* [C# Tutorial from FreeCodeCamp](https://www.youtube.com/watch?v=GhQdlIFylQ8)

* [Microsoft C# Reference](https://docs.microsoft.com/en-us/dotnet/csharp/programming-guide/)



### C++



* [CISCO Net Academy](https://www.netacad.com/courses/programming)

* [Codecademy](https://www.codecademy.com/)

* [C++ Beginner to Advanced](https://www.youtube.com/watch?v=8jLOx1hD3_o)



### Java



* [API](https://docs.oracle.com/javase/7/docs/api/)

* [Java: The Complete Reference](https://drive.google.com/file/d/1FWUTT4x8BI-v0_SIf50HHNvyKdPw1gYq/view) by Herbert Schildt 9th Edition(2014)



### Javascript



* [Data Visualization with JavaScript](https://www.freecodecamp.org/learn/data-visualization/)

* [Revolunet JS Books](https://jsbooks.revolunet.com/)



### Python



* [Automate the Boring Stuff with Python](https://automatetheboringstuff.com/)

* [Intro to CS and Python Programming](https://www.youtube.com/playlist?list=PLUl4u3cNGP63WbdFxL8giv4yhgdMGaZNA) by MIT

* [Programming for Computations](https://link.springer.com/book/10.1007/978-3-030-16877-3)

* [Python for Everyone](https://www.py4e.com/lessons)

* [Python Handbook](https://www.freecodecamp.org/news/the-python-handbook/)

* [Revolunet Python Books](https://pythonbooks.revolunet.com/)



### R



* [Data Visualization with R](https://socviz.co/)

* [R for Data Science](https://r4ds.had.co.nz/introduction.html)



### Rust



* [The Rust Programming Language](https://doc.rust-lang.org/stable/book/title-page.html)

* [Why Rust?](https://www.oreilly.com/content/why-rust/)



## Systems Development



* [Agile Manifesto](https://agilemanifesto.org/)

* [Agile Alliance](https://www.agilealliance.org/)

* [Extreme Programming](https://ronjeffries.com/xprog/what-is-extreme-programming/)

* [infoQ: Software Development News](https://www.infoq.com/?variant=homepage_collections)

* [Kaizenko](https://www.kaizenko.com/) - Scrum Training

* [Mountain Goat Software: What is Scrum?](https://www.mountaingoatsoftware.com/agile/scrum)

* [Scrum Alliance](https://www.scrumalliance.org/)

* [Scrum Guide](https://scrumguides.org/)

* [What is SDLC?](https://www.freecodecamp.org/news/what-is-sdlc-software-development-life-cycle-phases-methodologies-and-processes-explained/)



### DevOps



* [The Agile Admin](https://theagileadmin.com/)

* [Chef](https://www.chef.io/blog)

* [Code as Craft](https://codeascraft.com/)

* [Juju](https://jaas.ai/)

* [Martin Fowler](https://martinfowler.com/)

* [Transparent Uptime](http://www.transparentuptime.com/)



## Hosting



### Kubernetes



Kubernetes is an orchestration platform- it is used to distribute systems across numerous different **nodes** and build systems for reliability and durability.  



* [Kubernetes Basics](https://kubernetes.io/docs/tutorials/kubernetes-basics/)

* [Kubernetes Security Guide](https://www.techrepublic.com/resource-library/downloads/kubernetes-security-guide-free-pdf/)

* [Kubernetes the Hard Way](https://github.com/kelseyhightower/kubernetes-the-hard-way)



### Cloud Computing



Cloud computing is one of the fastest growing areas of information systems; it has evolved into a multi-billion dollar industry which is in need of skilled practitioners. Students of participating universities are eligible for up to hundreds of dollars in free credits from major CSPs.  AWS offers $100 per year to students to learn how to use their platform; they also offer free usage on new accounts of some products for the first year, Azure also offers $100-200 of computing resources depending on your program of study.



* [AWS Training](https://www.aws.training/)

* [Azure Tutorials](https://docs.microsoft.com/en-us/learn/browse/?terms=Azure)

* [Digital Ocean](https://www.digitalocean.com/community/tutorials)

* [Google Cloud Tutorial](https://cloud.google.com/docs/get-started)



## Databases



### Big Data



* [Big Data Algorithms](https://www.youtube.com/playlist?list=PL2SOU6wwxB0v1kQTpqpuu5kEJo2i-iUyf) by Harvard

* [Learn Hadoop](https://www.tutorialspoint.com/hadoop/index.htm) Big Data Analysis Framework

* [Tech Target](https://searchoracle.techtarget.com/)



### SQL



* [Basic SQL Tutorial Video](https://www.youtube.com/watch?v=HXV3zeQKqGY&t=3159s)

* [Convert CSV to SQL Commands](https://www.convertcsv.com/csv-to-sql.htm)

* [Databases and SQL Long Tutorial Video](https://www.youtube.com/watch?v=4cWkVbC2bNE&t=596s)

* [postgresql](https://www.postgresql.org/)

* [SQL Tutorial](https://www.sqltutorial.org/)

* [w3schools](https://www.w3schools.com/sql/)



## Artificial Intelligence



### Math



* [Advanced Algorithms](https://www.youtube.com/playlist?list=PL2SOU6wwxB0uP4rJgf5ayhHWgw7akUWSf) by Harvard

* [Intro to Algorithms](http://stellar.mit.edu/S/course/6/sp06/6.046/) MIT Course

* [Khan Academy](https://www.khanacademy.org/math)

* [Linear Algebra for Everyone](http://math.mit.edu/~gs/everyone/) By Gilbert Strang

* [Math for Machine Learning](https://mml-book.github.io/book/mml-book.pdf)

* [Math of Big Data and Machine Learning](https://www.youtube.com/playlist?list=PLUl4u3cNGP62uI_DWNdWoIMsgPcLGOx-V) by MIT



### Machine Learning



* [Computing Machinery and Intelligence](https://www.csee.umbc.edu/courses/471/papers/turing.pdf) by Alan Turing; Mind 1950

* [Hands on Machine Learning with R](https://bradleyboehmke.github.io/HOML/)

* [Journal of Machine Learning Research](https://www.jmlr.org/)

* [Open Source YouTube ML Resources](https://laconicml.com/computer-science-curriculum-youtube-videos/)

* [Probabilistic Machine Learning: An Introduction](https://probml.github.io/pml-book/book1.html) By Kevin Patrick Murphy



### Statistical Learning



* [Elements of Statistical Learning](http://web.stanford.edu/~hastie/ElemStatLearn/)

* [Introduction to Statistical Learning with Applications for R](https://drive.google.com/file/d/1kKGNXAmR2IYo9FUAbaU7iUfr1d7zgBcn/view?usp=sharing)



### Deep Learning



* [Deep Learning](https://www.deeplearningbook.org/) by Ian Goodfellow and Yoshua Bengio and Aaron Courville; MIT Press 2016

* [Fast.AI](https://course.fast.ai/)

* [Intro to Deep Learning Video Series](https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI) by MIT

* [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/)

* [TensorFlow Playground](http://playground.tensorflow.org/#activation=relu&batchSize=10&dataset=spiral&regDataset=reg-plane&learningRate=0.03&regularizationRate=0&noise=0&networkShape=8,8,4,2&seed=0.32263&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false)

* [Interactive Visualization of Word Vectorization](https://github.com/lamyiowce/word2viz)

* [Yann LeCun's Deep Learning Course at CDS](https://cds.nyu.edu/deep-learning/)



## Linux



* [Arch Linux](https://archlinux.org/)

* [Bash Commands](https://ss64.com/bash/)

* [Bash Scripting](https://www.shellscript.sh/index.html)

* [Linux](https://www.linux.org/)

* [Linux Foundation](https://www.linuxfoundation.org/)

* [Linux NFS](http://nfs.sourceforge.net/)

* [Linux Privilege Escalation](https://tbhaxor.com/linux-privilege-escalation/)

* [Operating Systems From 0 to 1](https://github.com/tuhdo/os01/blob/master/Operating_Systems_From_0_to_1.pdf)

* [Ubuntu](https://ubuntu.com/) A good place to start

* [ZShell](https://zsh.sourceforge.io/Guide/)



## News



* [Dark Reading](https://www.darkreading.com/)

* [Engadget](https://www.engadget.com/)

* [Gizmodo](https://gizmodo.com/)

* [IEEE Spectrum](https://spectrum.ieee.org/)

* [Krebs on Security](https://krebsonsecurity.com/)

* [Light Reading](https://www.lightreading.com/)

* [Mac Rumors](https://www.macrumors.com/)

* [Techcrunch](https://techcrunch.com/)

* [Techmeme](https://www.techmeme.com/)

* [Tech Talks](https://bdtechtalks.com/)

* [Tom's Guide](https://www.tomsguide.com/)

* [ZDNet](https://www.zdnet.com/)

* [9to5Google](https://9to5google.com/)

* [9to5Mac](https://9to5mac.com/)



## Cool Papers



* [Twine](https://www.usenix.org/system/files/osdi20-tang.pdf)