Merge pull request #2 from Flomza/restructure

Restructure The Borr Project

Author: pulkitkrishna00

docs/computer-science/advanced-cs/electives/index.md

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+---
+sidebar_position: 6
+---
+
+# Electives
+
+*Timeline: varies per student*
+
+After completing **every required course** in Core CS, students should choose a subset of courses from Advanced CS based on interest.
+Not every course from a subcategory needs to be taken.
+But students should take *every* course that is relevant to the field they intend to go into.
+
+#### Advanced programming
+
+**Topics covered**:
+`debugging theory and practice`
+`goal-oriented programming`
+`parallel computing`
+`object-oriented analysis and design`
+`UML`
+`large-scale software architecture and design`
+`and more`
+
+Courses | Duration | Effort | Prerequisites
+:-- | :--: | :--: | :--:
+[Parallel Programming](https://www.coursera.org/learn/scala-parallel-programming)| 4 weeks | 6-8 hours/week | Scala programming
+[Compilers](https://www.edx.org/learn/computer-science/stanford-university-compilers) | 9 weeks | 6-8 hours/week | none
+[Introduction to Haskell](https://www.seas.upenn.edu/~cis194/fall16/)| 14 weeks | - | -
+[Learn Prolog Now!](https://www.let.rug.nl/bos/lpn//lpnpage.php?pageid=online) ([alternative](https://github.com/ossu/computer-science/files/6085884/lpn.pdf))*| 12 weeks | - | -
+[Software Debugging](https://www.youtube.com/playlist?list=PLAwxTw4SYaPkxK63TiT88oEe-AIBhr96A)| 8 weeks | 6 hours/week | Python, object-oriented programming
+[Software Testing](https://www.youtube.com/playlist?list=PLAwxTw4SYaPkWVHeC_8aSIbSxE_NXI76g) | 4 weeks | 6 hours/week | Python, programming experience
+
+(*) book by Blackburn, Bos, Striegnitz (compiled from [source](https://github.com/LearnPrologNow/lpn), redistributed under [CC license](https://creativecommons.org/licenses/by-sa/4.0/))
+
+#### Advanced systems
+
+**Topics covered**:
+`digital signaling`
+`combinational logic`
+`CMOS technologies`
+`sequential logic`
+`finite state machines`
+`processor instruction sets`
+`caches`
+`pipelining`
+`virtualization`
+`parallel processing`
+`virtual memory`
+`synchronization primitives`
+`system call interface`
+`and more`
+
+Courses | Duration | Effort | Prerequisites | Notes
+:-- | :--: | :--: | :--: | :--:
+[Computation Structures 1: Digital Circuits](https://learning.edx.org/course/course-v1:MITx+6.004.1x_3+3T2016) [alternative 1](https://ocw.mit.edu/courses/6-004-computation-structures-spring-2017/) [alternative 2](https://ocw.mit.edu/courses/6-004-computation-structures-spring-2009/) | 10 weeks | 6 hours/week | [Nand2Tetris II](https://www.coursera.org/learn/nand2tetris2) | Alternate links contain all 3 courses.
+[Computation Structures 2: Computer Architecture](https://learning.edx.org/course/course-v1:MITx+6.004.2x+3T2015) | 10 weeks | 6 hours/week | Computation Structures 1 | - 
+[Computation Structures 3: Computer Organization](https://learning.edx.org/course/course-v1:MITx+6.004.3x_2+1T2017) | 10 weeks | 6 hours/week | Computation Structures 2 | -
+
+#### Advanced theory
+
+**Topics covered**:
+`formal languages`
+`Turing machines`
+`computability`
+`event-driven concurrency`
+`automata`
+`distributed shared memory`
+`consensus algorithms`
+`state machine replication`
+`computational geometry theory`
+`propositional logic`
+`relational logic`
+`Herbrand logic`
+`game trees`
+`and more`
+
+Courses | Duration | Effort | Prerequisites
+:-- | :--: | :--: | :--:
+[Theory of Computation](https://ocw.mit.edu/courses/18-404j-theory-of-computation-fall-2020/) ([alternative](https://www.youtube.com/playlist?list=PLEE7DF8F5E0203A56)) | 13 weeks | 10 hours/week | [Mathematics for Computer Science](https://openlearninglibrary.mit.edu/courses/course-v1:OCW+6.042J+2T2019/about), logic, algorithms
+[Computational Geometry](https://www.edx.org/learn/geometry/tsinghua-university-ji-suan-ji-he-computational-geometry) | 16 weeks | 8 hours/week | algorithms, C++
+[Game Theory](https://www.coursera.org/learn/game-theory-1) | 8 weeks | 3 hours/week | mathematical thinking, probability, calculus
+
+#### Advanced Information Security
+
+Courses | Duration | Effort | Prerequisites
+:-- | :--: | :--: | :--:
+[Web Security Fundamentals](https://www.edx.org/learn/computer-security/ku-leuven-web-security-fundamentals) | 5 weeks | 4-6 hours/week | understanding basic web technologies
+[Security Governance & Compliance](https://www.coursera.org/learn/security-governance-compliance) | 3 weeks | 3 hours/week | -
+[Digital Forensics Concepts](https://www.coursera.org/learn/digital-forensics-concepts) | 3 weeks | 2-3 hours/week | Core Security
+[Secure Software Development: Requirements, Design, and Reuse](https://www.edx.org/learn/software-development/the-linux-foundation-secure-software-development-requirements-design-and-reuse) | 7 weeks | 1-2 hours/week | Core Programming and Core Security
+[Secure Software Development: Implementation](https://www.edx.org/learn/software-development/the-linux-foundation-secure-software-development-implementation) | 7 weeks | 1-2 hours/week | Secure Software Development: Requirements, Design, and Reuse
+[Secure Software Development: Verification and More Specialized Topics](https://www.edx.org/learn/software-engineering/the-linux-foundation-secure-software-development-verification-and-more-specialized-topics) | 7 weeks | 1-2 hours/week | Secure Software Development: Implementation
+
+#### Advanced math
+
+Courses | Duration | Effort | Prerequisites
+:-- | :--: | :--: | :--:
+[Essence of Linear Algebra](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab) | - | - | [high school math](/precollege-math/index.md)
+[Linear Algebra](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/) | 14 weeks | 12 hours/week | corequisite: Essence of Linear Algebra
+[Introduction to Numerical Methods](https://ocw.mit.edu/courses/mathematics/18-335j-introduction-to-numerical-methods-spring-2019/index.htm)| 14 weeks | 12 hours/week | [Linear Algebra](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/)
+[Introduction to Formal Logic](https://forallx.openlogicproject.org/) | 10 weeks | 4-8 hours/week | [Set Theory](https://www.youtube.com/playlist?list=PL5KkMZvBpo5AH_5GpxMiryJT6Dkj32H6N)
+[Probability](https://stat110.hsites.harvard.edu/) | 15 weeks | 5-10 hours/week | [Differentiation and Integration](https://www.edx.org/course/calculus-1b-integration)
+

docs/computer-science/advanced-cs/final-project/index.md

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+---
+sidebar_position: 6
+---
+
+# Final Project
+*Timeline: varies per student*
+
+### Final project
+
+Part of learning is doing.
+The assignments and exams for each course are to prepare you to use your knowledge to solve real-world problems.
+
+After you've completed Core CS and the parts of Advanced CS relevant to you,
+you should identify a problem that you can solve using the knowledge you've acquired.
+You can create something entirely new, or you can improve some tool/program that you use and wish were better.
+
+Students who would like more guidance in creating a project may choose to use a series of project oriented courses.
+Here is a sample of options
+(many more are available, at this point you should be capable of identifying a series that is interesting and relevant to you):
+
+Courses | Duration | Effort | Prerequisites
+:-- | :--: | :--: | :--:
+[Fullstack Open](https://fullstackopen.com/en/) | 12 weeks | 15 hours/week | programming
+[Modern Robotics (Specialization)](https://www.coursera.org/specializations/modernrobotics) | 26 weeks | 2-5 hours/week | freshman-level physics, linear algebra, calculus, [linear ordinary differential equations](https://www.khanacademy.org/math/differential-equations)
+[Data Mining (Specialization)](https://www.coursera.org/specializations/data-mining) | 30 weeks | 2-5 hours/week | machine learning
+[Big Data (Specialization)](https://www.coursera.org/specializations/big-data) | 30 weeks | 3-5 hours/week | none
+[Internet of Things (Specialization)](https://www.coursera.org/specializations/internet-of-things) | 30 weeks | 1-5 hours/week | strong programming
+[Cloud Computing (Specialization)](https://www.coursera.org/specializations/cloud-computing) | 30 weeks | 2-6 hours/week | C++ programming
+[Data Science (Specialization)](https://www.coursera.org/specializations/jhu-data-science) | 43 weeks | 1-6 hours/week | none
+[Functional Programming in Scala (Specialization)](https://www.coursera.org/specializations/scala) | 29 weeks | 4-5 hours/week | One year programming experience
+[Game Design and Development with Unity 2020 (Specialization)](https://www.coursera.org/specializations/game-design-and-development) | 6 months | 5 hours/week | programming, interactive design
+

docs/computer-science/advanced-cs/index.md

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+---
+sidebar_position: 10
+---
+
+# Advanced CS
+*Timeline: varies per student*
+
+import DocCardList from '@theme/DocCardList';
+
+<DocCardList />

docs/computer-science/applications/computer-graphics/index.md

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+---
+sidebar_position: 3
+---
+
+# Computer graphics
+*Timeline: 72 hours*
+
+Learn to create images of 3D scenes in both real-time and with realistic ray tracing in this introductory computer graphics course.
+- [Computer Graphics](https://www.edx.org/learn/computer-graphics/the-university-of-california-san-diego-computer-graphics)
+
+Alternative course:
+- [CSE 167: Computer Graphics](https://cseweb.ucsd.edu/~viscomp/classes/cse167/wi22/schedule.html)

docs/computer-science/applications/databases/index.md

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+---
+sidebar_position: 1
+---
+
+# Databases
+*Timeline: 60 hours*
+
+These courses will give the student a basic understanding of databases, specifically with SQL:
+- [Relational Databases & SQL](https://www.edx.org/learn/relational-databases/stanford-university-databases-relational-databases-and-sql), 20 hrs
+- [Modeling & Theory](https://www.edx.org/learn/databases/stanford-university-databases-modeling-and-theory), 20 hrs
+- [Semistructured Data](https://www.edx.org/learn/relational-databases/stanford-university-databases-semistructured-data), 20 hrs

docs/computer-science/applications/index.md

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+---
+sidebar_position: 9
+---
+
+# Applications
+*Timeline: 279 - 291 hours*
+
+import DocCardList from '@theme/DocCardList';
+
+<DocCardList />

docs/computer-science/applications/machine-learning/index.md

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+---
+sidebar_position: 2
+---
+
+# Machine Learning
+*Timeline: 99 hours*
+
+These courses provide a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.)
+
+- [Supervised Machine Learning: Regression and Classification](https://www.coursera.org/learn/machine-learning), 33 hrs
+
+- [Advanced Learning Algorithms](https://www.coursera.org/learn/advanced-learning-algorithms), 34 hrs
+
+- [Unsupervised Learning, Recommenders, Reinforcement Learning](https://www.coursera.org/learn/unsupervised-learning-recommenders-reinforcement-learning), 27 hrs

docs/computer-science/applications/software-engineering/index.md

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+---
+sidebar_position: 4
+---
+
+# Software Engineering
+*Timeline: 48 - 60 hours*
+
+This course introduces how teams design, build, and test multi-version software systems.
+
+You will learn software engineering principles that are applicable to the breadth of large-scale software systems. The course explores topics such as agile development, REST and Async programming, software specification, design, refactoring, information security, and more.
+
+By the end of this course, learners will work in teams, applying an agile software development process to specify, design, and test multiple versions of complex software systems.
+- [Software Engineering: Introduction](https://www.edx.org/learn/software-engineering/university-of-british-columbia-software-engineering-introduction)
+
+Alternative:
+- [UBC CPSC - Software Engineering Resources](https://github.com/ubccpsc/310/blob/main/resources/README.md)

docs/computer-science/ethics-security/cyber-fundamentals/index.md

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+---
+sidebar_position: 2
+---
+
+# Cybersecurity
+*Timeline: 80 - 96 hours*
+
+Learn cybersecurity fundamentals, including how to detect threats, protect systems and networks, and anticipate potential cyber attacks.
+- [Cybersecurity Fundamentals](https://www.edx.org/learn/cybersecurity/rochester-institute-of-technology-cybersecurity-fundamentals)
+
+Extra resources:
+- [Professor Messer SY0-701 Security+ Training Course](https://www.youtube.com/playlist?list=PLG49S3nxzAnl4QDVqK-hOnoqcSKEIDDuv)

docs/computer-science/ethics-security/ethics/index.md

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+---
+sidebar_position: 1
+---
+
+# Ethics
+*Timeline: 35 hours*
+
+This course provides an introduction to ethics in engineering and technology.
+- [Ethics, Technology & Engineering](https://www.coursera.org/learn/ethics-technology-engineering), 18 hrs
+
+This course will introduce the various types of U.S. intellectual property: patents, which cover inventions and process innovations; copyright, which protects original works of authorship; and trademarks, which protect a business’ commercial identity as the source of valuable goods and services. You will then explore case studies of how global businesses have used intellectual property law to generate enormous value from these intangible assets.
+- [Introduction to Intelectual Property](https://www.coursera.org/learn/introduction-intellectual-property), 8 hrs
+
+This course is designed to introduce data privacy to a wide audience and help each participant see how data privacy has evolved as a compelling concern to public and private organizations as well as individuals. In this course, you will hear from legal and technical experts and practitioners who encounter data privacy issues daily. This course will review theories of data privacy as well as data privacy in the context of social media and artificial intelligence. It will also explore data privacy issues in journalism, surveillance, new technologies like facial recognition and biometrics.
+- [Data Privacy Fundamentals](https://www.coursera.org/learn/northeastern-data-privacy), 9 hrs