PhD Business Management, Applied Computer Science

The Phd in Business management & applied computer science degree program is offered in collaboration of the school of business management and school of computer science at Queensville University. Students get to learn courses form leading faculty members of both the schools and are able to do major development work after they graduate. Graduates are in a position to hold faculty appointments and do development and research work at the forefront of this quickly changing and expanding field.

Doctorate in Business Administration-Applied Computer Science consists of courses in algorithms, programming languages, compilers, artificial intelligence, database systems, and operating systems. Advanced courses are offered in many areas such as natural language processing, the theory of computation, computer vision, software engineering, compiler optimization techniques, multimedia, networks, cryptography and security, Adjunct faculty, drawn from outside academia, teaches special topics courses in their areas of expertise.


WHAT YOU'LL LEARN

As a result of completing this program, students should be able to:

  • Develop professional-level understanding of advanced topics in computer science for those in the field looking to enhance their skills for career advancement, as well as individuals interested in moving into the field.
  • Engage the development, and analysis of algorithms, which are instructions (or software) that tell a computer how to solve particular problems correctly and efficiently.
  • Develop research and development experience by gaining specialized knowledge in the areas of computer science.
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Information Research Strategies

2

Introduction to information research including electronic resources. This course is designed to help researchers locate, evaluate, and use information. It includes exploration of the research process, search strategies, locating resources, source documentation, and organization of research.

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Statistical Modeling and Analysis for Complex Data Problems

2

Reviews some of today's more complex problems, and reflects some of the important research directions in the field. Twenty-nine authors – largely from Montreal's GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and shastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.

Optimal Experimental Design

2

Introduces the philosophy of experimental design, provides an easy process for constructing experimental designs, calculating necessary sample size using R programs and teaches by example using a custom made R program package: OPDOE introduces experimenters to the philosophy of experimentation, experimental design, and data collection.

Mathematical Modeling

2

Complete range of basic modeling techniques: it provides a consistent transition from simple algebraic analysis methods to simulation methods used for research. Such an overview of the spectrum of modeling techniques is very helpful for the understanding of how a research problem considered can be appropriately addressed.

Research Methods and Design

2

Learners gain a thorough understanding of statistical tests appropriate to their dissertation topic and design, how to interpret the results of the tests and how to conduct follow-up analyses, as appropriate. This course includes guidelines and "best practices" for collecting data. Power analysis, what it is, why do it, and how to use available software is covered. Data preparation, use of software to analyze data, and understanding the calculated results are covered.

Dissertation Planning, Writing, and Defending

2

step-by-step through the dissertation process, with checklists, illustrations, sample forms, and updated coverage of ethics, technology, and the literature review.

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Business Process Management

2

Applications and case studies focusing on contemporary issues in operations and quality management to include lean manufacturing practices, ERP, quality and environmental management systems/standards, Six Sigma, statistical process control, and other current topics.

Operations Strategy

2

Application and case studies are used to address issues in operations management, quality, research and development, capacity planning, budgeting, marketing, supply chain, and technology to provide an interdisciplinary, quantitative focus on decision making and strategic planning for operations.

Project Management

2

Focuses on project definition, selection, planning, scheduling, implementation, performance monitoring, evaluation and control. Emphasis will be on product, service and process development and emerging concepts related to development on the internet.

Business and Corporate Strategies

2

Introduces students to a repertoire of strategies that have been found useful in the creation of competitive advantage: cost leadership, business model differentiation, vertical integration, diversification, globalization, mergers and acquisitions, tacit collusion, alliance, and flexibility-agility-adaptability strategies.

Managing Change

2

This course focuses on theory, research, and practice of both 'planned' and 'unplanned' change. The course considers the dynamics of change in complex organizations, variables which facilitate or impede change, and how to lead change and motivate others to change.

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Decision Support and Expert Systems

3

Explains fundamentals of artificial intelligence and expert systems that manipulate data and arrive at decisions through a programming process that resembles the human thinking process.

E-Commerce Concepts

3

Electronic commerce touches each of us daily. As consumers we are continually offered products and services via the Internet. In our jobs, no matter what profession we are in, electronic commerce is being used more and more to conduct business, for training purposes and daily communications. This course examines the principles of electronic commerce and business transactions on the Internet.

Concepts of Database Management

3

Focuses on data as a valuable organizational resource that must be managed, distributed, and maintained in a secure manner.

Integrated Business Processes with ERP Systems

3

Covers the key processes supported by modern ERP systems and examines in depth the core concepts applicable to all ERP environments, and it explains how those concepts can be utilized to implement business processes in SAP systems.

Monitoring Web-Based Applications and Infrastructure

3

Provides Learners with the skills to build powerful Web-based applications for the electronic commerce environment.

Managerial Electronic Commerce

3

Provides a thorough explanation of what EC is how it's being conducted and managed, and how to assess its opportunities, limitations, issues, and risks— all from a managerial perspective.

Electronic Payment Systems

3

Examines in detail the transformation of the VISA system from a collection of non-integrated, localized, paper-based bank credit card programs into the cooperative, global, electronic value exchange network it is today.

Network Defense: Security and Vulnerability Assessment

3

Covers the fundamental skills in evaluating internal and external threats to network security and design, how to enforce network level security policies, and how to ultimately protect an organization's information. I also covers a broad range of topics from secure network fundamentals, protocols & analysis, standards and policy, hardening infrastructure, to configuring IPS, IDS, firewalls, bastion host and honey pots.

Data Mining Concepts and Techniques

3

Provides an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each lesson is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data.

Computer Networking

3

Focuses on different computer network topologies and methods as well as setting up and management with methods of access control and troubleshooting

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Concept Paper

2

Ethical issues in research are studied and the Learner evaluates the research plan developed in modules RSH8951-RSH8953 against accepted ethical principles and practices in the field. The material developed in the modules is integrated into a summarizing document called the Dissertation Research Proposal. The proposal is comprised of Chapter I (Introduction), Chapter II (Literature Review), and Chapter III (Methodology).

Doctoral Comprehensive Examination

2

Assures that the Learner has mastered knowledge of his or her discipline, specialization, and can demonstrate applications of that knowledge before formal candidacy status is granted and research in support of the dissertation is initiated. Satisfactory/Unsatisfactory grade only.

Doctoral Dissertation Research l

2

The draft of the Dissertation Research Proposal is finalized and approved by the Learner's Dissertation Committee and the University's Ethics Committee. All steps necessary to begin data collection, including any necessary pilot testing, are completed. Candidates for the Ph.D. must maintain continuous enrollment. Satisfactory/Unsatisfactory grade only.

Doctoral Dissertation Research ll

2

Dissertation data are collected and analyzed. Candidates for the Ph.D. must maintain continuous enrollment. Satisfactory/Unsatisfactory grade only.