MS Computer Science in Software Engineering

Explore how to analyze and design computer algorithms and data structures. You’ll examine methods for evaluating algorithm efficiency and implementation of various data objects, programming styles, and performance expectations. Course topics include the key areas required to understand algorithmic design patterns, such as data concepts, arrays, stacks, queues, trees, and graphs. These concepts are applied to create effective programs and solve problems in coding design. You’ll also learn the importance of enhancing a program’s performance to ensure it is optimized and reusable for overall growth. 

Learn how to develop a new software program solution using the appropriate computer architectural design. Core topics focus on understanding the critical hardware and software functionality needed to ensure a solution can be designed that will meet the requirements for usability, performance, and support expectations of the program. You’ll also learn strategies for making architectural decisions critical for successful implementations.  

Develop an understanding of key security concepts, security issues and procedures in computer and mobile networks. You’ll explore various types of security such as LANs, WANs, databases, and network operating systems. You will also analyze threats to computer networks by exploring designs of network infrastructure, potential security flaws, risk assessment and mitigation, and security concepts that impact various communication networks. You’ll learn what network security capabilities are needed in architecture and how to apply them based on different situations. As a result, you’ll gain a comprehensive understanding of when to use network intrusion detection and forensics technologies, cryptographic and authentication systems, access control mechanisms, internet routing and other protocols. 

Examine the fundamentals of data warehousing and data mining and gain a deeper understanding of how data mining is used through hands-on experience in a variety of areas including:

• Big Data analysis
• prediction
• classification
• identification
• clustering
• association

You’ll also learn how data mining and databases work hand-in-hand from a user perspective in various data modelling, statistical analysis, designing schemas, querying databases, and manipulating databases. On completion, you’ll understand key strategies on how to apply data mining technology to real-world applications, evaluate trends, and optimal design solutions.

Examine the overall core aspects of operating systems design and implementation. You’ll explore key topics including developing knowledge of operating systems by reviewing different types of OS to understand system concepts (process and memory management, process coordination, device drivers, file systems, starvation/deadlock), functionalities of files system management (such as log-structured file systems, distributed file systems, memory-based file systems), user interface, programs and implementation approaches and steps. You’ll also use case studies to understand design approaches on how operating system types (batch, time-sharing/multitask, distributed, network, mobile, Microsoft windows, Apple iOS, Linux, etc.) may be used in a particular solution scenario and how they impact coding decisions.

Gain an introduction to the origins of programming languages and how they have evolved over the years. Learn about abstractions in programming languages, including both data type abstractions and control structure abstractions, and how different programming languages, like Java and Lisp, implement these abstractions and the programming paradigms to which they belong. Finally, develop your understanding of advanced features of programming languages, such as exceptions and polymorphism and their purpose.

Gain a foundation for assessing risk frameworks associated with inter-organizational and external breaches of security, setting up an IT security organization, system development considerations, and technical issues. You’ll cover a range of topics including: 

• strategy 
• business continuity 
• legal issues 
• risk management 
• disaster preparedness/recovery 
• training and awareness 
• policies and procedures 
• physical security 
• public key infrastructure and encryption 
• industrial espionage 
• privacy 
• software licensure compliance

Modern business is conducted by economic organizations in a highly competitive market environment. Managers often make decisions under severe time pressure without sufficient information. Ethical decision making in business cannot be considered apart from the complexity and uncertainty of actual situations. Therefore, the focus of the course is on ethical questions from the point of view of the practicing manager, with the aim of making ethical decisions that are consistent with effective corporate management.

Develop your understanding of theoretical and practical insights and developments in the fields of business ethics and sustainable business and learn the principles, practices, and ethical concerns/challenges organizations face in their daily operations. You will also gain an understanding of the theoretical basis of business ethics: stakeholder-theory, theories of responsibility and normative ethical theory, as well as intercultural ethics.

Gain foundation knowledge on the importance of machine learning in artificial intelligence and explore modern algorithms in machine learning, focusing on practical applications to understand how to structure data into models that can be created and utilized. A core emphasis is placed on understanding the components needed when using data and information to develop such as software libraries, regression, classification, mixture models, neural networks, deep learning, ensemble methods and reinforcement learning. You’ll also gain knowledge of machine learning techniques and how they can be applied in various processes and real-world solutions. 

Explore different approaches to software architecture to design supportable environments. You’ll review tools and techniques used in designing and structuring both simple and complex software solutions. You will gain knowledge of different architectural styles such as object-oriented architecture, data-centric architecture, client/server architecture, and layered architecture. Furthermore, you’ll develop a clear understanding of how to evaluate software architecture impacts, technology stacks, software processes and business needs by evaluating implementation decisions made in various business scenarios. 

Gain an introduction into software engineering concepts which includes activities performed at each stage of the software development life cycle. You’ll learn about the tasks and models a development team needs to understand to successfully complete a software project. You’ll enhance your knowledge of software analysis, requirement documentation, and technical and functional specifications. You’ll explore the best practices in writing appropriate documentation that details the full aspects of the project work to be performed throughout the SDLC process. The main goal is for you to understand what it takes to successfully engineer a software solution and meet the needs of business and customer stakeholders. Finally, you’ll also gain an understanding of topics including software project management (different methods/approaches such as Agile and Waterfall), project release planning, and software engineering ethics.  

Explore software testing principles, techniques, and best practices used in the development of high-quality software systems. The goal is for you to understand how to successfully create a test plan that encompasses the appropriate level of testing needed to validate a solution by resolving and preventing defects. You’ll learn about the different types of testing levels such as unit, system integration, and user acceptance testing as well as non-functional testing including load, performance or regression testing, and security testing. You’ll also explore the value of having quality checks through code reviews, requirements walk-throughs, and other process-related quality assurance concepts to ensure the result meets business and user requirements. 

Develop a comprehensive understanding of research in computer science. You’ll examine the concepts and theories underlying research, as well as the practice of research.  

The course has an applied focus. Your readings and assignments are designed to identify a feasible research topic and develop a research proposal for an academic project or dissertation. You will also examine how research problems and questions may be identified, and the process of achieving thoughtful, effective and efficient research design.  

Learn about the importance of the literature review and how it can be carried out for optimal effectiveness in research and gain an overview of research methodologies and methods as well as the techniques of the research process. You will study the philosophical and epistemological assumptions underpinning the research approaches and methodologies, as well as their role in determining the design and implementation of the research. Finally, you will  gain an understanding of the ethical aspects of research. 

A continuation of Research Methods for Computer Science I in which you’ll complete the project or dissertation presented in the first course.