Students enrolled in the master’s program in computer science at the University of Ottawa may be eligible to fast-track directly into the doctoral program without writing a master’s thesis. For additional information, please consult the “Admission Requirements” section of the PhD program The Master’s program in Computer Science offers a unique choice of courses that covers all aspects of the discipline, ranging from advanced digital technologies to distributed information systems and security. It also includes emerging disciplines such as biocomputing and service science Computer Science Master’s Curriculum. Regardless of how you complete the computer science master’s degree (on-campus or online), the program consists of one core course, three cluster courses, four electives, and a thesis or project. The program prepares for academic and research careers in computer science or related disciplines
Master of Science in Computer Science < Georgia Tech
The MSCS provides the skills necessary for challenging jobs as software developers, information security analysts, network administrators, database developers, data analysts, IT project managers, and health informatics professionals. Bureau of Labor Statistics Occupation Outlook Handbook. Because of the specialized nature of the work, competition for talent is fierce.
Boston University has been designated a Center of Academic Excellence CAE in Cyber Defense and Research by the National Security Agency and Department of Homeland Security. Our information security programs are certified by the Committee on National Security Systems CNSS.
The professors have a good mix of both academic and industry experience, making it a very well-rounded program. Use the Career Insights tool to explore jobs that are the right fit for you.
Filter by career area and job title or by industry sector to explore employment demand and average salaries. Our faculty consists of academic leaders who are engaged in innovative research computer science master thesis proposal skilled industry experts with firsthand experience in data analytics, machine learning, AI, computer networks, cybersecurity, IT project management, and software development.
To computer science master thesis proposal eligible for the degree, you must apply for admission and be accepted into the degree program. Connect with a graduate admissions advisor at csadmissions bu. edu to learn more about this option.
A minimum passing grade for a course in the graduate program is a C 2. Topics include sorting, searching, dynamic programming, greedy algorithms, advanced data structures, graph algorithms shortest path, spanning trees, tree traversalsmatrix operations, string matching, NP completeness.
Prereq: MET CS and either MET CS or MET CS Or METCS and METCS Or instructor's consent. Overview of operating system characteristics, design objectives, and structures. Topics include concurrent processes, coordination of asynchronous events, file systems, resource sharing, memory management, security, scheduling and deadlock problems. Prereq: MET CS, and MET CS or MET CS, or instructor's consent. Theory of finite automata and regular expressions and properties of regular sets.
Context- free grammars, context-free languages, and pushdown automata. Turing machines, undecidability problems, and the Chomsky hierarchy. Introduction to computational complexity theory and the study of NP-complete problems. Prerequisite: MET CS or instructor's consent. Overview of techniques and tools to develop high quality software. Topics include software development life cycle such as Agile and DevOps, requirements analysis, software design, programming techniques, refactoring, testing, as well as software management issues.
This course features a semester-long group project where students will design and develop a real world software system in groups using Agile methodology and various SE tools, including UML tools, project management tools, programming frameworks, unit and system testing toolsintegration tools and version control tools, computer science master thesis proposal.
Prereq: At least two level or above programming intensive courses. Students should be familiar with object oriented design concepts and proficient in at least one high level programming language before taking this class.
This course provides a robust understanding of networking. It teaches the fundamentals of networking systems, their architecture, function and operation and how those fundamentals are reflected in current network technologies. Students will learn the principles that underlie all networks and the application of those computer science master thesis proposal or not to current network protocols and systems. The course explains how layers of different scope are combined to computer science master thesis proposal a network.
There will be a basic introduction to Physical Media, the functions that make up protocols, such as error detection, delimiting, lost and duplicate detection; and the synchronization required for the feedback mechanisms: flow computer science master thesis proposal retransmission control, etc.
Prereq: MET CS and MET CS or MET CS or MET CS Restrictions: This course may not be taken in conjunction with MET CS or MET CS undergraduate. Only one of these courses can be counted towards degree requirements. This course provides a theoretical yet modern presentation of database topics ranging from Data and Object Modeling, relational algebra and computer science master thesis proposal to advanced topics such as how to develop Web-based database applications.
Other topics covered - relational data model, SQL and manipulating relational data; applications programming for relational databases; physical characteristics of databases; achieving performance and reliability with database systems; object- oriented database systems.
Prereq: MET CS or MET CS ; or instructor's consent. Restrictions: This course may not be taken in conjunction with MET CS undergraduate or MET CS Refer to your Department for further details. Students who have completed courses on core curriculum subjects as part of their undergraduate degree program or have relevant work-related experience may request permission from the Department of Computer Science to replace the corresponding core courses with graduate-level computer science electives.
Please refer to the MET CS Academic Policies Manual for further details. Students who are not choosing a concentration must select five General Electives. At least three courses must be at the level or above. When choosing electives, students should make sure that they have all prerequisites required by the selected course. MET CS Computer Graphics This course is primarily the study of design of graphic algorithms.
At the end of the course you can expect to be able to write programs to model, transform and display 3- dimensional objects on a 2-dimensional display. The course starts with a brief survey of graphics devices and graphics software. Attributes of the primitives are studied as well as filtering and aliasing.
Geometric transformations in 2 dimensions are introduced in homogeneous coordinates, followed by the viewing pipeline, which includes clipping of lines, polygons and text.
Hierarchical graphics modeling is briefly studied. The graphics user interface is introduced and various input functions and interaction modes are examined. This is followed by 3-d transformations and the 3-d viewing pipeline. The course ends with a study of algorithms to detect the visible surfaces of a 3-d object in both the object space and the image space. Laboratory Course.
Prereq: MET CS and MET CS or MET CS The goal of this course is to provide students with the mathematical and practical background required in computer science master thesis proposal field of data analytics, computer science master thesis proposal.
Probability and statistics concepts will be reviewed as well as the R tool for statistical computing and graphics. Different types of data are investigated along with data summarization techniques and plotting.
Data populations using discrete, continuous, and multivariate distributions are explored. Errors during measurements and computations are analyzed in the course. Confidence intervals and hypothesis testing topics are also examined. The concepts covered in the course are demonstrated using R. Prereq: MET CS and MET CS or MET CSor equivalent knowledge, or instructor's consent.
This course provides an overview of the statistical tools most commonly used to process, analyze, and visualize data. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis.
These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results, are discussed. Concepts are presented in context of real world examples. Recommended Prerequisite: MET CS or equivalent knowledge, computer science master thesis proposal, or instructor's consent.
This course presents financial algorithms used in applications of computer science in financial decision analysis, risk management, data mining and market analysis, and other modern business processes.
The course covers theoretical background on probabilistic methods used for financial decision making and their application in number of fields such as financial modeling, venture capital decision making, operational risk measurement and investment science. Number of financial applications and algorithms are being presented for portfolio risk analysis, modeling real options, venture capital decision making, etc.
The course concludes with algorithms for financial risk assessment and presents the security concepts and challenges of financial information systems. This course is designed for IT professionals, and those training to be IT professionals, who are preparing for careers in healthcare-related IT Computer science master thesis proposal Informatics, computer science master thesis proposal. This course provides a high-level introduction into basic concepts of biomedicine and familiarizes students with the structure and organization of American healthcare system and the roles played by IT in that system.
The course introduces medical terminology, computer science master thesis proposal, human anatomy and physiology, disease processes, diagnostic modalities, and treatments associated with common disease processes. IT case studies demonstrate the key roles of health informatics and how IT tools and resources help medical professionals integrate multiple sources of information to make diagnostic and therapeutic decisions.
This course presents the technological fundamentals and integrated clinical applications of modern Biomedical IT. The first part of the course covers the technological fundamentals and the scientific concepts behind modern medical technologies, computer science master thesis proposal, such as digital radiography, CT, nuclear medicine, ultrasound imaging, etc.
It also presents various medical data and patient records, and focuses on various techniques for processing medical images. This part also covers medical computer networks and systems and data security and protection.
The second part of the course focuses on actual medical applications that are used in health care and biomedical research. Health Information Systems are comprehensive application systems that automate the activities of healthcare delivery including clinical care using electronic health records EHRs computer science master thesis proposal, coordination of care across providers, telehealth, management of the business of healthcare such as revenue cycle management, and population health management.
The course covers the functionality of these systems, the underlying information technology they require and their successful operations. It addresses challenges in this rapidly changing field such as complex data, security, interoperability, mobile technology and distributed users. The course emphasizes applied use of health information systems through case studies, current articles, and exercises.
In this course we will study the fundamental and design applications of various biometric systems based on fingerprints, computer science master thesis proposal, voice, face, hand geometry, palm print, iris, retina, computer science master thesis proposal, and other modalities.
Multimodal biometric systems that use two or more of the above characteristics will be discussed. Biometric system performance and issues related to the security and privacy aspects of these systems will also be addressed. This course focuses on building core competencies in web design and development. It begins with a complete immersion into HTML essentially XHTML and Dynamic HTML DHTML.
Students are exposed to Cascading Style Sheets CSSas well as Dynamic CSS. The fundamentals of JavaScript language including object-oriented JavaScript is covered comprehensively. AJAX with XML and JSON are covered, as they are the primary means to transfer data from client and server. Prereq: MET CSMET CSMET CS computer science master thesis proposal MET CS
Master's Thesis Proposal Presentation - Student: Tran Le Anh
, time: 13:17USC Viterbi | Department of Computer Science
The Master’s program in Computer Science offers a unique choice of courses that covers all aspects of the discipline, ranging from advanced digital technologies to distributed information systems and security. It also includes emerging disciplines such as biocomputing and service science Students enrolled in the master’s program in computer science at the University of Ottawa may be eligible to fast-track directly into the doctoral program without writing a master’s thesis. For additional information, please consult the “Admission Requirements” section of the PhD program Computer Science Master’s Curriculum. Regardless of how you complete the computer science master’s degree (on-campus or online), the program consists of one core course, three cluster courses, four electives, and a thesis or project. The program prepares for academic and research careers in computer science or related disciplines
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