Computer Science MSc

Program Overview

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Course overview

The School has a proven record of successful research, consultancy and enterprise projects in the field of computer science, giving our staff the relevant real-world case studies to draw upon in their teaching. Having worked in the sector, many of our academic staff have forged strong working relationships with colleagues in industry.

The programming strand gives you the expertise and transferable skills in event-driven programming, patterns, design, development and deployment using industry-standard tools. The AI strand investigates computer models, simulations and techniques for observing and predicting behaviours in large-scale systems. The project management module underpins the practical and theoretical skills with techniques for strategic management of projects so that you are prepared for the full project life cycle. The individual computer science project and Advanced Practice (Internship) module provides you with the opportunity to apply both your practical and theoretical skills in your chosen specialism and to gain real-world experience in industry or research.There are three routes you can choose from to gain an MSc Computer Science:

full-time - 2 years with advanced practice (September and January start)

full-time - 1 year (September start) or 16 months (January start)

part-time - up to 3 years (can be completed in 2 years if preferred).

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Program Outline

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Computer Science MSc at Teesside University: Detailed Information

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Degree Overview:

The MSc in Computer Science at Teesside University provides a comprehensive understanding of two key areas: programming and artificial intelligence (AI). Additionally, the program focuses on project management and research methods, equipping students with the necessary academic rigor and practical skills required for postgraduate studies and industry entry.

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Objectives:

• Develop expertise in programming and AI fundamentals.
• Master project management and research methodologies.
• Gain practical experience through an internship or individual research project.
• Prepare for a career in the thriving data science sector.

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Program Description:

The program features two distinct strands:

• Programming: Develop expertise in event-driven programming, patterns, design, development, and deployment using industry-standard tools.
• Artificial Intelligence: Investigate computer models, simulations, and techniques for observing and predicting behavior in large-scale systems.
The program also emphasizes project management, equipping students with the knowledge and skills required for the strategic management of projects. Additionally, the program culminates in an individual project or internship, allowing students to apply their theoretical and practical skills in their chosen field and gain real-world experience.

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Outline:

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Program Content:

• Core modules covering AI foundations, big data and business intelligence, object-oriented programming, and research methods.
• Elective modules offering specialization in areas such as machine learning, mobile app development, and advanced practice (internship).
• Individual project or internship to apply theoretical knowledge and gain practical experience.

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Structure:

• Available as a full-time program with two years of duration or a part-time program with a variable duration of up to three years.
• Full-time program offers both standard and advanced practice options, with the latter including a professional internship.
• Modules are offered throughout the year, allowing for flexible scheduling and completion.

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Course Schedule:

• Specific course schedules are not provided in the context.
• Students can contact the university directly for detailed information on course schedules.

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Individual Modules:

• Artificial Intelligence Foundations: Introduces logic-based knowledge representation, reasoning, problem solving, algorithms, and AI applications.
• Big Data and Business Intelligence: Develops skills in designing and implementing database, big data, and analytics applications.
• Computing Masters Project: Individual research focusing on a specific area of computer science, culminating in a major deliverable such as a software package, design, or research findings.
• Machine Learning: Explores statistical and probabilistic techniques for making predictions based on observed data.
• Mobile App Development: Develops Android apps for smartphones and tablets to a professional standard using industry-standard tools and processes.
• Object Oriented Programming: Intensive introduction to programming principles and event-driven GUI development using Java language.
• Research Methods: Develops research skills and knowledge necessary for undertaking the master's project, focusing on evaluating academic research, generating evidence, and applying research methodologies.

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Other Modules:

• Advanced Practice (Internship): Vocational or research-based internship opportunities for professional development and real-world experience.

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Assessment:

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Assessment Methods:

• Individual assignments, coursework, projects, presentations, exams, and research reports.
• Emphasis on critical thinking, problem solving, and effective communication.
• Varies depending on the specific module and assessment criteria.

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Assessment Criteria:

• Knowledge and understanding of subject matter.
• Ability to apply theoretical concepts to practical problems.
• Critical thinking and problem-solving skills.
• Effective communication skills, both written and oral.
• Project management and research skills.

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Teaching:

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Teaching Methods:

• Interactive lectures with case studies and examples.
• Tutorials and practical sessions.
• Guest lectures from industry professionals.
• Emphasis on active learning and student engagement.
• Individualized support and guidance from experienced faculty.

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Faculty:

• Experienced and qualified professors with expertise in computer science, AI, and related fields.
• Strong connections to industry and research communities.
• Committed to providing students with a stimulating and supportive learning environment.

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Unique Approaches:

• Focus on project-based learning and critical thinking.
• Access to state-of-the-art computing facilities and software.
• Opportunities for industry engagement and professional development.
• Commitment to inclusivity and diversity in the classroom.

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Careers:

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Career Opportunities:

• Graduates can pursue careers in various sectors including data science, AI, software development, research, and academia.
• The program prepares students for job roles such as data scientist, AI engineer, software developer, researcher, and lecturer.
• High demand for data science professionals in industries like defense, finance, telecommunications, and healthcare.

• The program is accredited by the Chartered Institute for IT (CIIT).
• Graduates acquire transferable skills valuable in various careers, including problem-solving, critical thinking, communication, and teamwork.
• The university offers career support services to assist students in their job search and professional development.

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Tuition Fees and Payment Information:

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Full-time:

• UK applicants:
• £7,365 per year
• £4,770 per year with advanced practice
• International applicants:
• £17,000 per year
• £10,000 per year with advanced practice

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Part-time:

• UK applicants:
• £820 for each 20 credits

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Payment information:

• More details about the fees can be found on the university's website.
• You can apply online for the full-time or part-time program.
• You can also apply online for the fast-track program if you are a current student.

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Currency:

• The fees are listed in British Pounds (GBP).

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Additional Information:

• The length of the program is:
• Within 1 year (September start)
• 16 months (January start)
• 2 years with advanced practice (September or January start)
• The start date is September or January.

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Please note:

• The information provided is based on the 2024/25 entry year.
• Fees and payment information may be subject to change.
• It is recommended to consult the university's website for the most up-to-date information.