Why Continuing Education Is Important for Computer Scientists

For professionals in the computer industry, continuing education is vital for adding key skills to their repertoire as well as sharpening the skills they already have. Computer professionals know that almost as soon as a new technology is made available, there is already something more advanced in development waiting to take its place. Continuing education classes help computer professionals stay on the cutting edge in their profession. Some of the continuing education courses developed for computer scientists might include software design, software testing, network security and other foundations of computer science theory and their applications. Taking a few continuing education courses can also boost your resume and demonstrate to your employer that you are committed to being a lifelong learner.

The Advantage of Taking Online Classes

Computer scientists immerse themselves every day in computer technology, so taking classes online, rather than in a traditional classroom, should not come as a surprise to them as a learning platform. In fact, this may be the best way for them learn the subject matter. Working computer scientists will not need to put their jobs on hold to take continuing education classes online, as the programs are flexible and allow them to access their courses 24/7 while eliminating the commute to a college campus. Computer scientists can take advantage of the high quality of courses and instructors, all from the comfort of their homes or any other Internet hotspot.

How Free Online Classes Can Supplement Your Career

Many of the nation’s most respected universities are posting a limited number of courses in or related to computer science online for free to all takers. These courses are not credit-bearing, as there is no professor to guide the course, but they still serve as a great refresher in areas where you may have gotten rusty or an excellent resource for independent study in an area in which you may not be familiar. Some of the top universities offering these free online classes include MIT, Princeton, Harvard, UC—Berkeley and the University of Washington. A few of the course offerings have included: Machine Structures; Artificial Intelligence; Algorithms and Computational Complexity; the History of Computing; and Programming Languages.

• Computers in Our World: This course includes lecture notes, problem sets, lab resources and solutions for studying Javascript and more. [Princeton]
• Introduction to Artificial Intelligence: Take this course if you want to learn about artificial intelligence topics like machine translation, decision trees and logic. [University of Washington]
• Machine Structures: Lessons in this course include number representations and MIPS. [UC Berkeley]
• Introduction to Computer Science and Programming: Discover how computer science and computing is used in problem solving. [MIT]
• Introduction to Computers: Here is another introductory-level computer science course that covers computers and culture, the Internet and social networking. [UC Berkeley]
• The History of Computing: Study past uses of the computer for scientific purposes. [MIT]
• Understanding Computers and the Internet: Explore the inner workings of your computer when you take this course. [Harvard]
• Representing and manipulating data in computers: Study positive integers, negative integers, weight representation, and input and output here. [The Open University]
• Introduction to Computer Science and Programming: Even if you have no programming experience, you can take this course to learn the basic principles of CS. [MIT]
• Introduction to Algorithms: CS students get an introduction to programming through this course. [MIT]
• Algorithms and Computational Complexity: Continue your study of algorithms with this course. [University of Washington]
• Introduction to Computer Science I: This is another introduction course to teach you how computers work. [Harvard]
• The Anthropology of Computing: In this class, you’ll consider computers as social instruments. [MIT]
• Artificial Intelligence: Here is another course that will teach you about heruistics, game trees, Markov Decision Processes, and more. [UC Berkeley]
• Data and process in computing: Explore the types of data found in software systems. [The Open University]
• Representing and manipulating data in computers: Positive integers, denary and binary numbers, and encoding integers are all covered here. [The Open University]
• Freshman Computer Seminar: This is a good class for beginners or for those wanting to brush up on CS basics. [UCLA]
• Computer System Architecture: Take this class if you want to learn more about micro-architecture, memory organization, sharing, set design, and more. [MIT]
• Computers and Computer Systems: This intermediate class covers processors, memory, switches and representing data. [The Open University]
• How Computers Work: Learn digital logical design, processor design and assembly design here. [ADUni]
• Principles of Computer Systems: In order to understand how to build computers and computer systems, you’ll learn about their fundamental properties in this course. [MIT]
• Machine Learning: Machine Learning will teach you about classification, clustering and more. [UC Irvine]
• Theory of Computation: Learn about the hierarchies and variations of finite state machines, context free grammars and more. [ADUni]
• Database Systems: Familiarize yourself with different types of database systems and components here. [MIT]
• Transmission of Information: Study the quantitative theory of information here. [MIT]
• Systems: In Systems, you’ll continue to study computer software engineering and hardware engineering. [ADUni]
• Cultural History of Technology: Study the cultural history of technology from the ancient Greeks until now. [MIT]
• Social and Political Implications of Technology: Discover how technology influences culture. [MIT]
• Programming languages: Learn about different types of programming languages and memory management systems here. [University of Washington]
• Simply Scheme: Higher order functions, Lamda, input and output, trees, fractals and functions are all covered here. [UC Berkeley]
• Kernel-based Learning: Get an overview of Kernel methods here. [UC Irvine]
• Machien Learning: This machine learning course covers statistical patterns and more. [Stanford]
• XML Foundations>: Get an introduction to XML with these slides and course materials. [UCB]
• Multithreaded Parallelism: Learn about coding, optimization and organization for languages and compilers of multithreaded parallelism. [MIT]
• AJAX Programming: Find AJAX tutorials and learning resources here. [Google Code University]
• Object-Oriented Programming in C++: Familiarize yourself with C++ basics here. [University of Southern Queensland]
• Networking Basics: After this course, you’ll be able to identify networks, connect to the Internet, use appropriate terminology, and explain how networks work. [3com]
• Technology and Global Development: Discover how computers and other technology systems are changing the world. [Delft]
• Distributed Computer Systems Engineering: Learn how to design distributed computer systems here. [MIT]
• Computer Vision: Find lecture notes and slides about computer vision here. [Oxford]
• Mathematics for Computer Science: This math class covers discrete mathematics, including probability theory and modular arithmetic. [MIT]
• Introduction to Computers – Interdepartmental Studies: Lessons here include Basic Application Software II and Privacy and Security. [UC Berkeley]
• Discrete Mathematics: This is another course covering discrete mathematics for CS. [ADUni]
• Computer Communication and Networks: Learn routing, TCP congestion, practical networking, routing, HTTP and more. [University of Washington]
• Computer Language Engineering: Study high-level programming languages and potential problems here. [MIT]
• Software Engineering: Learn about Java, Javascript, Ruby on Rails and more. [University of Washington]
• PHP: Learn PHP fundamentals from this course. [University of the Western Cape]
• Great Ideas in Theoretical Computer Science: Consider the role that computers play in decoding complex problems. [MIT]
• Introduction to Formal Models in Computer Science: You’ll learn concepts like recursive definitions, graphs, relations and basic set theory when you take this course. [University of Washington]