Computer Science

Where to Start
--------------------------------------------

Friedman, The Little Schemer
K&R, The C Programming Languaage
Graham, ANSI Common Lisp
SICP
Bloch, Effective Java
Sedgewick, Algorithms

=============================================
What languages people learn first

Traditional Route:
C -> Java -> Other (Clojure, Go/Rust, C#, D)

Used to be
C -> C++, but Java replaced C++ because C++
gained too much complexity

MIT Route:
LISP -> Java -> C

Modern Route:
Python -> Java / C#

=============================================

Ideal CS Ciriculum
--------------------------------------------

~~~Fall 1~~~
Calculus I
Intro to Proofs and Abstract Mathematics
Physics I
Intro to Programming
Technical Writing

~~~Spring 1~~~
Calculus II
Matrix Algebra
Physics II
Digital Logic and Automata
Data Structures

~~~Fall 2~~~
Vector Calculus
Physics III
Electrical Engineering Fundamentals
Computer Architecture
Algorithm I

~~~Spring 2~~~
Ordinary Differential Equations
Probability and Statistics
Parallel, Distributed, and GPU Programming
Operating Systems
Algorithm II

~~~Fall 3~~~
Numerical Analysis I
Combinatorics and Graph Theory I
Mathematical Logic
Digital Signal Processing
Programming Languages and Compilers I

~~~Spring 3~~~
Numerical Analysis II
Combinatorics and Graph Theory II
College Geometry
Computability and Complexity Theory
Compilers II
Database Theory (Seminar)

~~~Fall 4~~~
Abstract Algebra
Classical Number Theory
Computer Graphics and Vision
Artificial Intelligence and Machine Learning
Internet, Networks and Communication Systems
Professionalism, Ethics, and Conduct (Seminar)

~~~Spring 4~~~
Linear Programming and Optimization
Computer Security and Cryptography
FPGAs, Microcontrollers and Driver Development
Software Engineering Essentials
Principles of Economics
Personal Grooming and Hygiene (Seminar)

Alternative
--------------------------------------------

1st semester
>Unix Introduction
>C Introduction
>Essential Data Structures: Linked Lists, Binary Trees, and Hash Tables in C
>Essential Algorithms: Sorting and Searching
>Project Management and Maintenance
>textbooks: The UNIX Programming Environment, Programming in C; The Practice of Programming

2nd semester
>Scheme Introduction
>SICP
>textbook: Structure and Interpretation of Computer Programs

3rd semester
>Concurrent Programming in Go
>Network Programming in Go
>Graphs and Why You'd Want Them
>Using yacc
>Parsing and Interpreting Non-Metacircularly




Computer Engineering

    Algorithm Design and Analysis: Either
        Algorithms by Dasgupta et al,
        Algorithm Design by Kleinberg and Tardos,
        Introduction to Algorithms by Cormen et al,
        Introduction to Algorithms: A Creative Approach by Manber.
    Artificial Intelligence: Either
        Artificial Intelligence, a Modern Approach by Russell and Norvig,
        Paradigms of Artificial Intelligence Programming by Norvig.
    Automata Theory: Either
        Applied Combinatorics on Words by Lothaire,
        Automata Theory, Languages, and Computation by Hopcroft et al,
        Formal Language: A Practical Introduction by Webber,
        Introduction to the Theory of Computation by Sipser,
        Languages and Machines: An Introduction to the Theory of Computer Science by Sudkamp.
    Category Theory: Either
        Abstract and Concrete Categories: The Joy of Cats by Adamek et al,
        Category Theory by Awodey,
        Category Theory for Computer Scientists by Pierce.
    Compilers: Either
        Compilers: Principles, Techniques and Tools by Aho et al,
        Engineering a Compiler by Cooper and Torczon,
        Modern Compiler Implementation by Appel.
    Computability Theory: Either
        Computability and Logic by Boolos and Jeffrey,
        Introduction to the Theory of Computation by Sipser.
    Computational Geometry: Computational Geometry: Algorithms and Applications by de Berg et al.
    Computer Architecture: Either
        Computer Architecture - A Quantitative Approach by Patterson and Hennessy.
        Computer Organization by Hamacher et al,
        Computer Systems - A Programmer's Perspective by Bryant and O'Hallaran,
        Structured Computer Organization by Tanenbaum.
    Computer Graphics: Either
        Computer Graphics: Principles and Practice by Foley et al,
        Fundamentals of Computer Graphics by Shirley and Marschner,
        Real-Time Rendering by Akenine-Moller et al.
    Computer Vision: Either
        Computer Vision: Algorithms and Applications by Szeliski,
        Computer Vision - A Modern Approach by Forsyth,
        Machine Vision: Theory, Algorithms, Practicalities by Davies.
    Cryptography: Either
        Cryptography Engineering by Schneier et al,
        Modern Cryptography by Katz and Lindell.
    Database Theory: Either
        Database Management Systems by Ramakrishnan and Gehrke,
        Database Systems: The Complete Book by Garcia-Molina et al.
    Distributed Programming: Either
        Distributed Systems: Concepts and Design by Dollimore et al,
        Introduction to Reliable Distributed Programming by Guerraoui and Rodrigues,
        Principles of Concurrent and Distributed Programming" by Ben-Ari.
    Functional Programming: Either
        Introduction to Functional Programming using Haskell by Bird and Wadler,
        Learn You a Haskell for Great Good by Lipovaca,
        The Little Schemer and The Seasoned Schemer by Friedman and Felleisen,
        ML for the Working Programmer by Paulson,
        Structure and Interpretation of Computer Programs by Abelson et al.
    General Logic: Either
        Logic for Computer Science: Modelling and Reasoning About Systems by Huth and Ryan,
        Mathematical Logic for Computer Scientists by Ben-Ari.
    Human-Computer Interaction: Designing the User Interface: Strategies for Effective Human-Computer Interaction by Shneiderman.
    Information Theory: Either
        Information Theory by Cover and Thomas,
        Information Theory and Reliable Communication by Gallager.
        Information Theory, Inference, and Learning Algorithms by MacKay.
    Intractability: Either
        Computational Complexity by Papadimitriou,
        Computational Complexity: A Modern Approach by Arora and Barak,
        Introduction to the Theory of Computation by Sipser.
    Lambda Calculus: Lambda Calculi: A Guide for Computer Scientists by Hankin.
    Logic Programming: Either
        Prolog Programming for Artificial Intelligence by Bratko,
        The Art of Prolog: Advanced Programming Techniques by Shapiro.
    Machine Learning: Either
        Bayesian Reasoning and Machine Learning by Barber,
        Data Mining: Practical Machine Learning Tools and Techniques, by Witten and Frank,
        The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Hastie et al,
        Introduction to Machine Learning by Alpaydin,
        Machine Learning by Mitchell,
        Mining of Massive Datasets by Ullman and Rajamaran,
        Pattern Recognition and Machine Learning by Bishop and Pattern Classification by Duda and Hart.
    Natural Language Processing: Either
        Foundations of Statistical Natural Language Processing by Manning and Schutze,
        Speech and Language Processing by Jurafsky and Martin.
    Networks: Either
        Computer Networking by Kurose and Ross,
        Computer Networks by Tanenbaum and Wetherall.
    Numerical Methods: Numerical Recipes in C: The Art of Scientific Computing by Press et al.
    OO Program Design: Design Patterns, Elements of Reusable Object-Oriented Software by Gamma et al.
    Operating Systems: Operating System Design and Implementation by Tanenbaum.
    Operations Research: Either
        Convex Optimization by Boyd and Vandenberghe,
        Linear Programming and Network Flows by Bazaraa et al.
    Pi Calculus: Communicating and Mobile Processes: The Pi Calculus by Milner.
    Program Analysis: Principles of Program Analysis by Nielson et al.
    Programming Language Concepts and Design: Either
        Concepts, Techniques and Models of Computer Programming by Van Roy and Haridi,
        Essentials of Programming Languages by Friedman et al,
        Modern Programming Languages: A Practical Introduction by Webber,
        Programming Languages: Application and Interpretation by Krishnamurthi.
        Programming Language Pragmatics by Scott.
    Programming Language Semantics: Either
        Formal Semantics of Programming Languages by Winskel,
        Foundations for Programming Languages by Mitchell,
        Semantics Engineering with PLT Redex by Felleisen,
        Semantics of Programming Languages: Structures and Techniques by Gunter.
    Quantum Computation: Quantum Computation and Quantum Information by Nielson and Chuang.
    Randomized Algorithm Design and Analysis: Either
        Randomized Algorithms by Motwani and Raghavan,
        Probability and Computing, Randomized Algorithms and Probabilistic Analysis by Mitzenmacher and Upfal.
    Security Engineering: Security Engineering by Anderson.
    Software Engineering: Software Engineering by Sommerville.
    Term Rewriting: Term Rewriting and All That by Baader and Nipkow.
    Type Theory: Either
        Foundations for Programming Languages by Mitchell,
        Types and Programming Languages by Pierce.

General useful reference works for programmers on the art, science and methodology of engineering programs:

    Code Complete: A Practical Handbook of Software Construction by McConnell,
    Crystal Clear: A Human Powered Methodology for Small Teams by Cockburn,
    How to Design Programs by Felleisen et al,
    The Mythical Man Month by Brooks,
    The Pragmatic Programmer by Hunt and Thomas,
    Refactoring: Improving the Design of Existing Code by Fowler et al,
    Why Programs Fail: A Guide to Systematic Debugging by Zeller.