Program Overview

Program Overview

The Applied Modelling and Quantitative Methods program at Trent University offers a unique opportunity for students to earn an M.A. or M.Sc. in a cutting-edge, data-driven field. This interdisciplinary program is designed to set students up for career success, with four dynamic streams to choose from: Thesis, Data Science and Analytics, Big Data Analytics, and Big Data Financial Analytics.

Program Description

The Thesis stream is a research-based option that allows students to collaborate with faculty members from a wide range of disciplines, including Anthropology, Biology, Business Administration, Chemistry, Computer Science, Economics, Geography, Humanities, Mathematics, Physics & Astronomy, Philosophy, and Psychology. This stream is ideal for students who wish to pursue a Ph.D. program in the future.

The course-based streams, on the other hand, are designed to provide students with practical skills and knowledge in their chosen field. The Data Science and Analytics stream is a 12-month program that covers a wide array of data science topics, including data mining, visualization, and machine learning. The Big Data Analytics stream is a 16-month program that equips students with the tools and techniques required to analyze complex data sets, with an emphasis on practical skills in visualization, data mining, and parallel programming. The Big Data Financial Analytics stream is also a 16-month program that prepares students for careers in the financial sector, including equity analysis, financial forecasting, and investment banking.

Program Details

• Location: Peterborough
• Degrees offered: Master of Arts (M.A.), Master of Science (M.Sc.)
• Program options: Course-based, Thesis
• Program length:
  • Thesis stream: 24 months
  • Data Science and Analytics stream: 12 months
  • Big Data Analytics stream: 16 months
  • Financial Analytics stream: 16 months
• Start dates: Fall, Winter, Spring/Summer
• Application deadlines:
  • Fall intake: February 1st
  • Winter intake: June 1st
  • Spring intake: October 1st

Admissions

To be eligible for the program, students must have:

• An Honours bachelor's degree (a four-year undergraduate bachelor's degree) in a traditional discipline
• A minimum B+ (77%) or equivalent in the last two years of full-time study, or last ten full academic credits
• A university course in differential and integral calculus, and one in probability and statistics or equivalent
• Some familiarity with linear algebra, and capabilities in programming at an elementary level in at least one computational language
• A course in either differential equations or advanced statistics is required, depending on whether the student's area of research will be mathematics or statistics based
• Proof of English Proficiency (for international students)

Eligibility Requirements

All applicants must submit the following documents to complete their application:

• Transcripts: Unofficial copies of all post-secondary transcripts
• 2 letters of reference: Academic references are preferred; however, professional references will be accepted
• Plan of Study/Personal Statement: 1-2 pages outlining your objectives in a graduate program
• Detailed Resume or Curriculum Vitae (course-based streams only)
• Proof of Citizenship (e.g., copy of passport or birth certificate)
• Supervisor (thesis-stream only): A potential supervisor must be chosen as an admission requirement for this program

Financial Matters

• Thesis stream: Eligible full-time students are offered minimum funding packages during their funded period of $18,000 annually, which includes a Graduate Teaching Assistantship employment offer valued at approximately $13,000 annually
• Course-based streams: Top scholar applicants may be awarded a Graduate Distinguished Entrance Scholarship of up to $3,000, based on academic excellence

Meet the Faculty

The program is led by world-class professors and researchers, including Dr. James D. A. Parker, AMOD Director and Professor of Psychology, and Dr. Jie Zhang, Associate Professor of Finance in the Trent School of Business.