computer-science/extras/courses.md

Computer Science - Great Courses

This is a list of high-quality courses that, for one reason or another, didn't make it into the curriculum. The most common reasons are that the course isn't available often enough, or that there was an alternative that fit better into the curriculum.

Programming

Courses	Duration	Effort
Introduction to Computer Science and Programming Using Python	9 weeks	15 hours/week
Introduction to Computer Science (Udacity)	7 weeks	10-20 hours/week
An Introduction to Interactive Programming in Python (Part 1)	5 weeks	-
An Introduction to Interactive Programming in Python (Part 2)	-	-
Introduction to Computational Thinking and Data Science	10 weeks	15 hours/week
Introduction to Programming with Java Part 1: Starting to Code with Java	5 weeks	5-7 hours/week
Introduction to Programming with Java Part 2: Writing Good Code	5 weeks	5-7 hours/week
CS For All: Introduction to Computer Science and Python Programming	14 weeks	5-7 hours/week
Programming Basics	9 weeks	8 hours/week
Introduction to Programming with MATLAB	-	-
Principles of Reactive Programming	7 weeks	5-7 hours/week
Object-Oriented Programming	4 weeks	8 hours/week
Introduction to Functional Programming	7 weeks	4-6 hours/week

Math

Courses	Duration	Effort
Pre-Calculus	10 weeks	10-12 hours/week
Multivariable Calculus	6 weeks	5-7 hours/week
Introduction to Probability and Data	-	-

Systems

Courses	Duration	Effort
Operating System Engineering	-	-
Introduction to Linux	8 weeks	5-8 hours/week
CompTIA Linux+	-	5.25 hours
Introduction to Operating Systems	8 weeks	5-8 hours/week
Advanced Operating Systems	5 weeks	5-8 hours/week
Advanced Operating Systems: Structures And Implementation	10 weeks	2-3 hours/week
Introduction to Computer Networking	-	5-10 hours/week
CompTIA Network+	-	32 hours
Cisco CCNA	-	15.5 hours
Networking for Web Developers	-	12 hours
Computer Networking	12 weeks	5-8 hours/week

Theory

Courses	Duration	Effort
Algorithms, Part I	6 weeks	6-12 hours/week
Algorithms, Part II	6 weeks	6-12 hours/week
Analysis of Algorithms (Skiena)	15 weeks	6-8 hours/week
Analysis of Algorithms (Sedgewick)	6 weeks	6-8 hours/week
Programming Challenges (Skiena)	14 weeks	6-8 hours/week
Mathematical Logic and Algorithms Theory	7 weeks	3-4 hours/week
Algorithmic Toolbox	5 weeks	4-8 hours/week
Algorithms on Graphs and Trees	-	-
Algorithms on Strings	-	-
Advanced Algorithms and Complexity	-	-
Algorithmic Thinking (Part 1)	-	-
Algorithmic Thinking (Part 2)	-	-
Statistical Mechanics: Algorithms and Computations	-	-
Approximation Algorithms Part I	-	-
Approximation Algorithms Part II	-	-
Algorithms: Design and Analysis, Part 1	6 weeks	5-7 hours/week
Algorithms: Design and Analysis, Part 2	6 weeks	6-10 hours/week

Applications

Courses	Duration	Effort
Web Application Architectures	6 weeks	6-9 hours/week
Agile Development Using Ruby on Rails - Basics	9 weeks	12 hours/week
Agile Development Using Ruby on Rails - Advanced	8 weeks	12 hours/week
Startup Engineering	12 weeks	2-20 hours/week
Using Databases with Python	5 weeks	2-3 hours/week
Database Systems	-	27 hours
Database Management Essentials	7 weeks	4-6 hours/week
Intro to Artificial Intelligence	16 weeks	6-10 hours/week
Intro to Machine Learning	10 weeks	6-10 hours/week
Machine Learning for Data Science and Analytics	5 weeks	7-10 hours/week
Big Data for Smart Cities	4 weeks	3-5 hours/week
Processing Big Data with Azure HDInsight	5 weeks	3-4 hours/week
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center	7 weeks	4-5 hours/week
Mining Massive Datasets	7 weeks	8-10 hours/week
Text Retrieval and Search Engines	-	-
Text Mining and Analytics	-	-
Cluster Analysis in Data Mining	-	-