MS Computer Science in Artificial Intelligence and Machine Learning

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.  

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. 

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. 

Develop your understanding of the fundamentals of artificial intelligence, usability, and how these are impacting everyday lives and businesses. You’ll analyze the concepts of AI usage such as speech and face recognition, autonomous driving, automatic scheduling, machine learning, deep learning, and other areas. You’ll also examine how mathematical tools are used to create applications and how to use these tools to solve AI problems in the real world. Finally, you will explore various AI ethical questions and concepts which impact people and businesses. 

Gain an understanding of computer vision when building artificial intelligent systems that process and perceive visual data through deep learning algorithms such as neural networks. You’ll explore the fundamentals of image formation and camera imaging processing including types of features such as: 

• stereo image 
• filtering 
• feature extraction 
• edge detection 
• alignment 
• object recognition appearance 
• audio 
• language  

 

You’ll research situations where imagery enhances artificial intelligence to capture the intended audience’s eye such as for gaming systems, self-driving cars, medical imaging, scientific applications, and other advancements in technology. As a result, you’ll gain an understanding of how visual representations can be structured to make images more accurate depictions through computer vision tasks. 

In this course, you will learn about modern natural language processing (NLP) concepts, tools and applications. More specifically, you will learn about and understand how morphological, syntactic and semantic analysis of text are carried out in natural language processing (NLP) applications. Further, you will also be introduced to the different methods and tools that can be used to implement NLP systems for applications such as sentiment analysis, question answering and machine translation. This course will also cover how NLP fits in machine learning by touching upon areas such as classifications, artificial neural networks, and model training.

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.