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Mercy College International Graduate Pathway - Computer Science (STEM)

The Computer Science Master of Science degree equips students with cutting edge knowledge and tools to solve data science and software development problems. The program starts by providing fundamental computer science theories that make skilled practice possible.

MSc Computer Science

The MSc Computer Science degree equips students with cutting-edge knowledge and tools to solve data science and software development problems.​

The program starts by providing fundamental computer science theories that make skilled practice possible.​
Choose from concentrations in data science or software development to pursue a career that best fits your interests. Data scientists and software developers receive comparable salaries.

Students can pursue careers in:

  • Data scientist: Analyze data and solve problems using the scientific method.
  • Software developers: Create user-focused apps, games, and more.

English Language Requirements

Course English Language Requirement
MCI Graduate Pathway (3 semester) IELTS 4.5 with no less than 4.0 in each component
MCI Graduate Pathway (2 semester) IELTS 5.0 with no less than 4.5 in each component
MCI Graduate Pathway (2 semester) IELTS 5.5 with no less than 5.5 in each component

What will you study?

As a graduate pathway student you will study English
Language, as well as academic courses tailored towards
your final degree. Each course is 3 credits and will count
towards your final degree.

Course Information

Object-Oriented Programming and Analysis of Algorithms (IELTS 4.5 only)

This course uses Java to cover object-oriented programming. Representation and implementation of major data structures, essential algorithms such as searching, sorting, hashing, and graphs, and analysis of the efficiency of algorithms are considered.

Theoretical Concepts in Computer Science

This course is an introduction to the theoretical concepts in Computer Science. Concepts include logic, proofs, relations, functions, counting, probability, regular, context-free, and computable (recursive) languages with finite state machines, pushdown automata, and Turing machines, along with basic concepts of computability theory and NP-theory.

Database Management Systems

Students learn the fundamentals of database management systems, including data representation, conceptual data modeling, entity relationship diagrams, the relational model, normalization, and database design and implementation. Concepts of data integrity, security, privacy, and concurrence control are introduced. Students design and implement a major database application project.

This is one of the three courses you can choose from in your final semester.

Software Design and Development (for Software Development specialization)

Students will learn the principles of software design and development, and software engineering. Topics to be covered include software design and processes, requirements and specifications, software validation and testing strategies, software evolution, project management, documentation, and quality assurance. Upon completion of the course, students should have a fundamental understanding of the software life cycle and the processes involved in the design, development, implementation and maintenance of complex software systems, and the associated documentation of design, program and training materials, as well as an understanding and development of the interpersonal and communication skills required for a career in computer science.

This is one of the three courses you can choose from in your final semester.

Mathematical Methods for Data Analysis (for Data Science specialization)

This course prepares the student for data analysis. Topics discussed include probability axioms, counting methods, random variables, probability distributions and densities, expected value, variance, correlation, conditional distributions (mean and variance), special probability models, law of large numbers, central limit theorem, statistical estimation, unbiasedness, consistency, efficiency, hypothesis testing, p-value, confidence intervals, nonparametric methods, ANOVA, and least squares. Applications for data science problems are discussed.

This is one of the three courses you can choose from in your final semester.

Key Information


Start Dates

January 2024September 2023


Pathway Tuition Fee

$12,814.00 – $18,414.00