Applied Computing (MAC)

Education on the cutting edge - The Master of Applied Computing (MAC) offers an advanced computing degree that adapts with the ever-changing technological landscape through a theoretical, practical and in-demand program focused on mobile, enterprise, data mining and machine learning. 

The MAC program will help you stand out in the job market and proves to employers that you have advanced technical knowledge and skills required to create technological solutions.

Starting in fall 2024, the MAC Coursework option will be located at the Brantford campus. The MAC Thesis and Co-op options will continue to be offered at the Waterloo campus.

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Program Highlights

  • Our faculty members offer research expertise in: algorithms, symbolic computation, embedded systems, networking, image processing, system-on-a-chip, security and quantum computing.
  • Flexible format - full-time or part-time program options to suit the busy schedules of working professionals. 

Program Details

Balancing Theory and Practice

Our philosophy is to create a “dream it, build it” environment where you apply the theory gained in the classroom and apply it to projects or in the field through a co-op placement. Employers note that people with traditional master's degrees in computing or computer science have a high level of technical knowledge but low levels of practical knowledge or experience. We equip you with both. Using case studies, project-based courses, and cooperative education opportunities, the MAC program will give you practical skills in ways that theory-focused degrees cannot.

Curriculum

All students in the MAC program must take Practical Algorithm Design. This course provides an essential background that allows students to move towards an area of specialization through additional coursework. These specialized course topics may include:

  • CP631: Advanced Parallel Programming 
  • CP685: Cyber Attack and Defense
  • CP670: Android Application Programming
  • CP640: Machine Learning
  • CP601: Seminar in Technology Entrepreneurship
  • CP610: Data Analysis
  • CP630: Enterprise Computing
  • CP669: Iphone Application Programming
  • CP650: User Interface Design and implementation

Program Options

The full-time Master of Applied Computing (MAC) program can be completed in four to five terms, depending on which option you choose (coursework, co-op or thesis option).

The part-time program (coursework option) allows you to take one to two courses per term and complete your degree in five to nine terms. Starting in fall 2024, the part-time option will also be offered online.

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“Choosing Laurier was one of the best decisions I’ve ever made. It’s a newer program and not as well known, but it’s a hidden gem.”

Tapas Vashi, current international student from India

Admissions

Take the first step in your graduate education and apply to one of our graduate programs. Follow our three-step admission process — we’ll walk you through how to apply and prepare for your first day as a graduate student.

Thesis and Co-op Program Stream

  • Start: Fall (September)
  • Format: Full-time
  • Application deadline:
    • Co-op option: The Fall 2024 Intake for the Co-op stream closed on January 26, 2024. Please watch this website for the next intake date. Applications are now being adjudicated. We appreciate your patience as we review a large volume of applications.
    • Thesis option: March 30 (international applicants), July 30 (domestic applicants).

Complete applications received by the first consideration date will be evaluated for early admission offers. We will continue to adjudicate applications until the application deadline or until the program is full. If you meet the requirements, please submit your application as early as possible. Only complete applications will be assessed for admissibility.

Coursework Program Stream

  • Start: Fall (September), Winter (January), Spring (beginning 2025)
  • Format: Full-time or part-time (in-person or online)
  • Application opens:  
    • January intake: Jan. 1
    • May intake (2025): May 1
    • September intake: Oct. 25, 2023
  • First consideration date: 
    • January intake: Feb. 28
    • May intake (2025): June 30
    • September intake: Dec. 30
  • Application deadline: 
    • January intake: April 30
    • May intake (2025): Aug. 30
    • September intake: March 30

Complete applications for Co-op, Thesis and Coursework Streams received by the first consideration date will be evaluated for early admission offers. We will continue to adjudicate applications until the application deadline or until the program is full. If you meet the requirements, please submit your application as early as possible. Only complete applications will be assessed for admissibility.

Your Next Steps

Questions? Contact the program via email at MACadvising@wlu.ca.

Waterloo and Brantford Campus

The Waterloo campus is home to more than 17,700 undergraduate and graduate students. You're steps away from classes, residence, and campus amenities on this close-knit campus.

On the other hand, the Brantford campus is woven into the downtown core of the City of Brantford and is home to more than 3,000 students. With classrooms and study spaces close to great restaurants, shopping and hiking trails, you get the best of both worlds.

There are many ways to tour both of our campuses to help make your decision. The choice of where you study is up to you!

Tuition and Funding

Regardless of the type of graduate degree program you intend to pursue, financial planning is important. At Laurier, we want to provide you with as much information as possible about a variety of scholarship and funding opportunities and equip you with the skills to manage your finances effectively in the years to come.

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Careers

This program can lead to careers such as:

  • data scientist
  • big data architect
  • mobile app developer
  • senior web developer
  • software developer
  • software project manager

Your Path to Post-Degree Success

ASPIRE is Laurier's professional skills development training program for graduate students. The program helps you craft an individualized, extracurricular learning plan tailored to your professional journey and entry to the workplace.

Faculty

Learn about the interests of our faculty members. If you are looking for more information about this program, have questions, or want to set up a meeting, contact a member of our team

Kathie Cameron
Professor

  • graph algorithms
  • polytime combinatorial optimization
  • graph theory

Hongbing Fan
Associate Professor

  • reconfigurable network computing platform with applications in grid/cloud computing
  • communication middlewere system for smart grid and sensor networks
  • circuit-switched/packet-switched reconfigurable interconnection on-chip networks

Angèle Foley
Professor

  • combinatorics
  • algorithms
  • optimization

Shohini Ghose
Professor
Director, Centre for Women in Science (WinS)

  • quantum computers/quantum teleportation
  • quantum and classical chaos
  • women in science

Ian Hamilton
Professor

  • quantum and classical mechanics
  • chemical bonding and reactivity
  • nanostructures, clusters and complexes

Chính Hoàng
Professor

  • theoretical computer science
  • graph theory
  • discrete mathematics
  • graph algorithms

Alexei Kaltchenko
Associate Professor

  • information theory
  • quantum information theory and quantum computing
  • data compression

Ilias Kotsireas
Professor
Director of the CARGO lab

  • symbolic computation
  • combinatorial designs
  • high-performance computing

Yang Liu
Associate Professor

  • machine learning 
  • data analysis 
  • deep learning 
  • recommender system 
Abdul-Rahman Mawlood-Yunis
Assistant Professor 
  • Android Mobile Application
  • Artificial Intelligence (Chatbots, NLP, Ontology, Semantic Web, Knowledge Representation, Software Agent)
  • Software Engineering
  • Distributed Systems and Algorithm Design
  • P2P Networking and Fault-tolerance

Roderick Melnik
Professor
Tier I Canada Research Chair in Mathematical Modelling
Director, MS2Discovery Interdisciplinary Research Institute

  • coupled multiscale phenomena, processes and systems
  • machine learning / deep learning algorithms for biomedicine and
    materials science
  • human interactions with complex systems, including human-computer
    interactions, human intelligence and human errors.

Shaowen Song
Professor

  • computer networks
  • system-on-chip design
  • video/audio compression
  • FPGA based circuit design
  • N-nary logics and optical computing

Marek Wartak
Professor

  • simulations of photonic devices
  • computational photonics
  • plasmonics

Li Wei
Professor

  • Computational/experimental photonic devices
  • Computational/experimental plasmonics

Jessie Zhao
Assistant Professor 

  • machine learning
  • information Retrieval
  • recommendation Systems
  • natural Language Processing
  • bioinformatics

Eugene Zima
Associate Professor

  • computer algebra
  • program optimization and fast computational schemes
  • algorithms
  • closed form summation