Using computational resources to solve large-scale problems takes more than coding skills. It takes an understanding of computer systems that transcends code. The fundamental difference between programming and computer science has to do with the depth of knowledge. Programmers and computer scientists are both problem-solvers, but programmers work in a limited sphere (e.g., one language or framework) while computer scientists apply their skills broadly. They are comfortable with software architecture, analysis, and design across platforms and have the expertise required to build scalable, maintainable, and durable products.
Some make the leap through arduous self-study, but progressing from one role to the other is simpler and faster in a graduate program with an experiential computer science curriculum based on challenges, trends and innovations in tech. Case Western Reserve University’s part-time, 100% online Master of Science in Computer Science (MSCS) program attracts serious graduate students who see the value of strategically growing the technical skillsets where employer demand is highest.
Many applicants who meet the program admission requirements and enrollment prerequisites are experienced developers and analysts with working knowledge in data structures, algorithms, operating systems and specialty areas of computer science like machine learning, software development, artificial intelligence (AI) or cybersecurity. Some have bachelor’s degrees in computer science or other STEM fields. Regardless of background, all Case Western Reserve MSCS students share the drive to grow personally and professionally, refine their technical knowledge and advance their careers. They understand that long-term success in computer science is a product of both education and experience.
The online computer science master’s program offered by the Case School of Engineering computer science department covers a diversity of topics, explained in detail below. As a result, graduates emerge ready to rise through the ranks of accomplished computer scientists at top tech firms worldwide.
Case School of Engineering’s computer science master’s degree curriculum is comprehensive and rigorous. The 10-class, 30-credit hour program focuses on four key specialization areas of computer science—AI, databases and data mining, security and privacy and software engineering—taught in both live and independent online graduate courses. Students learn skills related to:
There are hundreds of programming languages—all of which can be categorized into upper-level programming paradigms such as imperative, object-oriented, functional and logical. Understanding these categorizations is critical because programming languages are tools, and some tools are better than others at tackling specific jobs. One crucial skill that sets senior software engineers and architects apart from junior programmers is understanding which paradigms best suit particular problems. Students in the computer science MS program learn this skill in “Programming Language Concepts,” a course exploring language syntax, semantics, names/scopes, types, expressions, assignment, subprograms, abstraction and inheritance.
Automation is the future of computing, and AI is the technology driving it. Research into the future economic impact of artificial intelligence conducted by the McKinsey Global Institute found that 70 percent of organizations plan to start using AI technology by 2030. Those technologies will generate $13 trillion of global economic activity in the same period. Today, the evolution of AI is already creating new computer science jobs, and demand for skills related to artificial intelligence is soaring. Online MSCS students at Case Western Reserve learn the concepts underlying intelligent systems, including problem-solving with search, constraint satisfaction, adversarial games, knowledge representation and reasoning, using propositional and first-order logic, reasoning under uncertainty, reinforcement learning and natural language processing.
Computer scientists can solve complex challenges that don’t have framework- or programming language-specific solutions because they understand how to create algorithms—sequences of well-defined, language-independent instructions used for solving specific classes of problems. They can also analyze solutions based on their underlying characteristics instead of comparing and contrasting programs, frameworks or hardware. Understanding algorithms is essential because there are numerous ways to approach problems, but some are faster and use fewer resources than others. Programmers who don’t study algorithms can only use certain approaches. Meanwhile, senior computer science professionals respond to challenges from different angles, which is especially useful in large-scale architecture and determining what will scale. MSCS candidates at Case Western Reserve study graduate-level topics such as amortized analysis, NP-completeness and reductions, dynamic programming, and advanced graph algorithms.
Demand for computer science professionals with networking skills is growing—and changing—as more data moves onto distributed systems and cloud-based computer networks. Understanding how networks and networked systems function and how code executes on remote devices over network links helps developers design and build more reliable, better-performing software. Case Western Reserve MSCS students explore HTTP, FTP, DNS, socket programming, UDP, TCP, reliable data transfer, IP, routing, NAT and Ethernets.
Most computational work involves databases somehow, but working with databases can be exceedingly complex in that it requires knowledge of operating systems, algorithms, data structures and network programming. Database systems are also often the slowest part of an application. Serious developers and software engineers know how to choose database systems that meet distinct real-world requirements strategically and tweak systems when performance issues arise. Demand for this kind of knowledge will rise as applications grow more robust and deal with increasing amounts of data. “Database Systems” coursework prepares students to adapt to this ever-evolving landscape by covering:
- Database design, integrity and security
- Object-oriented databases and query languages
- Physical data organization
- Query optimization
- Relational databases and query languages
Data mining is an often misunderstood subfield of computer science and data science that uses semi-automatic or automatic tools to identify unusual patterns—often clusters, anomalies or dependencies—in information. The use of the term mining calls to mind the extraction of data, but data mining has more to do with knowledge discovery (i.e., analysis) than the discovery of data itself. Companies across industries look to computer science professionals with data mining skills to leverage the large amounts of data stored in databases, data warehouses or other information repositories. Case Western Reserve MSCS students learn about data warehouse and OLAP technology, data preprocessing, data mining primitives, languages, system architectures, mining association rules, classification and prediction, cluster analysis and mining complex types of data.
The growing number of mobile applications with access to sensitive user data is cause for concern, and permission-based access-control mechanisms may not be enough to prevent smartphone security issues. Case Western Reserve’s research into smartphone security impacts the computer science master’s curriculum. Coursework currently explores a range of security issues and solutions concerning mobile platforms and information systems, including permission analysis, textual artifacts analysis, malware analysis, program analysis and UI analysis. Assistant Professor Xusheng Xiao’s award-winning work in context- and user-aware security frameworks are poised to become standard in smartphone security.
Demand for computer science professionals with data privacy skills will grow by more than 15% over the coming decade as privacy and security standards evolve. Educating developers and engineers at scale is a necessary part of preventing future large-scale data breaches. Case School of Engineering computer science master’s students gain a broader view of data privacy through coursework covering:
- Anonymous routing and TOR
- Cellular and Wi-Fi networks
- Cryptography-based solutions for privacy
- Genomic privacy
- Hiding data from database users and hiding access patterns from database owners
- Location privacy
- Privacy in online social networks, e-cash systems and e-voting
The book Software Engineering at Google states that software engineering is “not just the act of writing code, but all of the tools and processes an organization uses to build and maintain that code over time… Software engineering can be thought of as ‘programming integrated over time.'” Many people associate software engineering with application development. However, it’s a fundamental subdiscipline of computer science that deals with the design, implementation and maintenance of many different programs and systems. Understanding the logic that drives best practices is the key to writing flexible code. Case Western Reserve teaches software engineering through the study of lifecycle models; development team organization and project management; requirements analysis and specification techniques; software design techniques; programming practices; software validation techniques; software maintenance practices; and ethics.
The emerging field of machine perception encompasses computer vision, computer audition or machine hearing and other disciplines concerned with building systems that perceive the world more like humans do. Demand for computer science professionals with machine perception skills is growing as the applications of related technologies expand. Computer vision is already widely used in facial recognition systems and geographical modeling. Machine listening technology powers voice-activated devices and is increasingly used in audio compression and recording software and speech synthesis systems. The MSCS program introduces information processing and computational algorithms that underlie perception—not just vision and audition but also other senses involved in perceptual processing systems. As a result, students graduate prepared to advance in a world where computers can see, hear and even smell.
Surprisingly, part-time online MSCS programs typically don’t take longer to complete than full-time MSCS programs. Most students enrolled in the Case School of Engineering can work through the online master’s in computer science curriculum in five semesters when they take two courses per semester. That represents a commitment of just six to nine hours per week through a blend of self-paced core courses and live interaction plus study time. Program courses are not interdependent, so students can complete them in any order. Because CWRU runs three semesters annually (spring, summer and fall), MSCS students can finish graduate school in just two years.
The benefits of pursuing an online MSCS at Case Western Reserve extend beyond flexibility, however. Case Western Reserve’s student-centered online environment provides numerous opportunities to connect with fellow students, expert faculty members and Case School of Engineering alumni. The program builds exceptional support into the student experience, and the university’s learning management system is easy to navigate and engaging. Additionally, graduates benefit from Alumni Association initiatives designed to help online learners connect and access continuing education opportunities.
Ultimately, the value of a Case Western Reserve MS in Computer Science is substantial and the cost is competitive. The skills you develop in this graduate degree program will prepare you to advance in your career today—and become one of tomorrow’s innovators. Apply now or register for one of our upcoming webinars to learn more about MSCS careers, the application process, and more.