McGill MSBA Program: Complete Overview

Table of Content


This blog aims to provide you with insightful information and an overview of the McGill MSBA Program. We will explore what sets this program apart and why it may be an excellent fit for managerial and executive aspirants. Furthermore, we will explore the course structure, specific courses offered, admission requirements, and other essential program elements. The McGill MSBA Program has received one of the highest ratings among MSBA programs in Canada, and we will showcase what makes it stand out from other business education programs worldwide. Ultimately, this blog offers an insider’s perspective on the McGill MSBA Program to empower prospective students to make informed decisions about their future.

The McGill MSBA program is a one-year pre-experience focused program in the rapidly evolving field of business analytics that places a significant emphasis on experiential learning. The MSBA program is intended to meet the increased demand from companies (for profit, non-profit, and government) for data-driven decision making that incorporates both commercial acumen and technological skills. In order to prepare for meaningful careers in analytics across a number of businesses and managerial situations, students learn managerial problem-solving utilizing cutting-edge data analytics techniques.

Program Overview

Program Structure and Duration

McGill MSBA program is designed for individuals who want to advance their knowledge of business analytics, ranging from fresh graduates with demonstrated quantitative skills to more seasoned professionals wishing to transition to a new industry. McGill students come from a variety of backgrounds, skill sets, and experience levels, but they all have a strong interest in studying analytics from a business or management standpoint. 

Students benefit from unique access to leaders from a number of industries thanks to the class patron/matron, the dedicated members of the MSBA Industry Advisory Board, and the large network of professional guest lecturers/partners. For students interested in getting more professional experience before graduation, the McGill MSBA program provides a 1.5-year program that includes an internship.

McGill MSBA Class Profile

The Desautels Faculty of Management chooses their students for the MSBA program carefully and consists of a pool of students of 571 applications. There are 23 countries represented in the incoming MMA class of 84 (42 female, 42 male).

Their academic backgrounds are equally broad, with students from colleges all over the world holding degrees in business, arts, accounting, physics, economics, commerce, computer science, engineering, and math, to mention a few.

The average age of the cohort is 24, with an average work experience of 2 years. As an McGill MSBA student, you will have the opportunity to be a part of this vibrant and diverse community, embarking on a transformative journey of personal and professional growth.

McGill Rankings and Reputation

McGill University is a prestigious Canadian institution with a strong global reputation. It consistently ranks among the top universities in the world. In various international rankings, such as the QS World University Rankings and the Times Higher Education World University Rankings, McGill often places within the top 50 universities globally.

The McGill MSBA program was ranked 10th worldwide by the QS World University Rankings. The university is renowned for its research excellence, academic programs, and diverse student community. It has a long history of producing successful graduates who have made significant contributions to various fields.

McGill’s reputation in various fields, including medicine, engineering, law, and arts, has attracted top-tier faculty and students from around the globe. The university’s diverse and vibrant community fosters an intellectually stimulating environment for students to thrive and excel.

Mcgill Msba Rankings - McGill MSBA Program: Complete Overview - - Class Profile, Tuition Fees and Employment Details - McGill MSBA Program - McGill MSBA Program


A one-year, pre-experience specialized Program with a heavy focus on experiential learning, the McGill MSBA degree is in the developing subject of business analytics. The MSBA Program is created to meet the growing demand for data-driven decision making that combines business acumen and technical abilities among organizations (profit, non-profit, and governmental).

As part of their preparation for fulfilling jobs in analytics across a number of industries and managerial settings, students gain knowledge of managerial problem-solving utilizing cutting-edge data analytics techniques.

The McGill MSBA is a rigorous, full-time, one-year Program that emphasizes experiential learning heavily. To give students a wide range of practical skills and views, the McGill MSBA curriculum maintains a balance between advanced statistics, technology, and business strategy.

In the curriculum, there is a 1.5-year alternative including an internship for students who want to obtain more work experience before they graduate.

Core Module (21 credits)

The core module’s objectives are to improve your statistical problem-solving skills and provide knowledge of the technical foundations of Team Management, Leadership, Data Analytics, and Decision Analytics.

Complementary Course Module (15 credits)

The MSBA Program is regarded as being industry-neutral. In order to expose students to a variety of themes, such as marketing, retailing, supply chain, healthcare, security, pricing, talent, and network analytics, complementing courses are created.

Introduction to Artificial Intelligence, Deep Learning, Cloud-based Enterprise Analytics, Social Media Analytics, Healthcare Analytics, Epidemiology Analytics, Pricing Analytics, and Revenue Management are a few examples of sample courses.

Experiential Module (9 credits)

The purpose of the experiential module is to give students the opportunity to use the principles they have learned in class in real-world situations and to interact with practitioners from top analytics companies.

  • Capstone Management Analytics Project (10 months)
  • Internship Option
  • Community Analytics Project Option

Required Courses (27 credits)

Students either need to take one of the following combined courses. Rest of the courses are mandatory.

  • BUSA 693 D1 and BUSA 693 D2.
  • BUSA 693 N1 and BUSA 693 N2.

BUSA 693D1: Analytics & Solution Consulting Practice (3 Credits)

In order to address data/analytics difficulties, data science teams collaborate with a specific client and provide an automated, technically sound solution.

BUSA 693D2: Analytics & Solution Consulting Practice (3 Credits)

In order to address data/analytics difficulties, data science teams collaborate with a specific client and provide an automated, technically sound solution.

BUSA 693N1: Analytics & Solution Consulting Practice (3 Credits)

Data science teams collaborating with a committed client to address data and analytics difficulties, including developing an automated and technically sound solution.

BUSA 693N2: Analytics & Solution Consulting Practice (3 Credits)

Data science teams collaborating with a committed client to address data and analytics difficulties, including developing an automated and technically sound solution.

INSY 660: Coding Foundations for Analytics (3 Credits)

The basics of computer programming, code for data collecting and processing, and particular operational concerns linked to “big data” analytics are just a few of the topics that students will be introduced to. Additionally, data security, ethics, and privacy will be covered in the course materials.

INSY 661: Data & Dist System for Analytics (3 Credits)

The student will learn several important database technology-related topics in this course, as well as how databases are used to manage enormous datasets and how to put these principles into practice.

The concepts of database management systems (DBMS), database architecture, entity-relationship modeling (ER) database design, data storage, file organization, the SQL language, normalization, data integrity, database security, data warehousing, and big data-related technologies like NoSQL, Hadoop, MapReduce, Pic, and Hive will all be covered in this course.

INSY 662: Data Mining and Visualization (3 Credits)

R, a tool that data analysts frequently utilize, will be used in the course to give students hands-on experience with the data mining techniques that will be presented. Instead of covering the theory and math behind the models, the course concentrates on applying the tools and strategies. The fundamentals of data manipulation and coding covered in INSY 660 are expanded upon and covered in considerably greater detail in this course.

In order to gain practical experience with using data mining and predictive analytics to make business decisions, students will be exposed to real-world datasets and examples. They will also be asked to contribute R code to implement the predictive models they have learnt in class. By the end of the course, students will feel confident utilizing R to independently address business challenges using a variety of data mining techniques.

MGSC 660: Math & Stat Foundations for Analytics (3 Credits)

There are two sections to this course. The course’s first half focuses on the statistical and probabilistic underpinnings of data analytics. Students will have mathematical understanding of the following subjects by the end of this section: Bayes’ Rule, Correlation, Sampling, Central Limit Theorem, Prior and Posterior Distributions, Random Variables, and Probabilities.

The mathematical underpinnings of decision analytics are the main topic of the course’s second half. The following mathematical concepts will be covered by the pupils by the end of this section: Convexity, Separating Hyperplanes, Unconstrained and Constrained Optimization, Lagrange Multipliers, Calculus of Several Variables, and Linear Algebra are some of the concepts covered.

MGSC 661: Multivariate Statistical Analysis (3 Credits)

The course will start with the basic linear regressions and move on to factor analysis, principal component analysis, selection models, dynamic and nonlinear multivariate data approaches, and multivariable regression models. By performing their own statistical studies, students will be introduced to a wide range of business analytics methods and applications.

MGSC 662: Decision Analytics (3 Credits)

In this course, students will learn quantitative techniques for commercial decision-making. Topics covered include Simulation, Optimisation Models, and Optimisation under Uncertainty. The commercial applications of these methods are highlighted. Through computer analysis of practical issues, students in this course will gain experience in quantitative methodologies for decision making.

ORGB 660: Managing Data Analytics Teams (1.5 Credits)

Students will develop a collaboration style and learn about themselves as team members and leaders in this course, including their strengths and areas for improvement. They will also learn how to jointly develop a vision and superordinate goal. They will also develop skills in team communication, using the “power of framing,” as well as how to work effectively with a variety of people and groups.

ORGB 661: Ethical Leadership & Leading Change (1.5 Credits)

In this course, students will learn how to excel at distributed and shared leadership which is essential to modern business; develop a collaboration style and learn about themselves as leaders – their strengths, their areas for improvement; learn how to jointly develop a vision and superior goal; establish guidelines, protocols, and criteria for leading change and for the respectful and ethical collection, storage, and use of data derived from others; develop the skills necessary to lead change; and, finally, learn how to create and implement change.

Complementary Courses (18 credits)

Students need to earn 3 credits from the following:

  • BUSA 600: Analytics Internship (3 Credits)

A work placement under the supervision of a professor in a business or organization. This course’s learning goals are to give students the chance to apply concepts they’ve studied throughout the Program and to get official job experience.

  • BUSA 649: Community Analytics Project (3 Credits)

A small- or medium-sized business analytics initiative that focuses on applying the principles of practical analytics challenges faced by businesses with limited budgets.

Students need to earn 15 credits from the following:

  • ACCT 626: Data Analytics in Accounting (1.5 Credits)

Through practical application learning, it is investigated how financial and non-financial variables might be related to corporate performance. Examining financial statement analysis, return predictability, required and optional company disclosure, and fraud detection.

  • ACCT 696: Advanced Topics in Accounting Analytics (1.5 Credits)

Current and developing accounting analytics issues. Each term’s course material will be unique.

  • BUSA 611: In-depth Studies in Analytics 1 (1.5 Credits)

Acquiring actual data to carry out a data-centric analysis for a company or research facility. Students will concentrate on one of the following project deliverables under the guidance of the instructors: data management, value proposition, analytic formulation, solution development, or user application.

  • BUSA 613: In-depth Studies in Analytics 2 (3 Credits)

Actual data acquisition in order to carry out a data-centric analysis for a company or research facility. The following project deliverables will be the main emphasis of each student’s work, as directed by the instructors: data management, value proposition, analytic formulation, solution development, and user application.

  • BUSA 684: Analytics Study Trip (3 Credits)

Site (company) visits, guest lectures from senior executives, and daily student reflections will all be used to conduct the course. Additionally, it might be coupled with a nearby analytics-related conference. Students must thoroughly research these procedures, finish a project centered on organizational practice excellence in analytics, and compose a reflection report.

  • FINE 675: FinL Val Analytics for Startups (1.5 Credits)

An introduction to finance with a focus on analytics, emphasizing how the combination of finance and analytics plays a crucial role for businesses and the choice to accelerate growth.

  • FINE 695: Advanced Topics in Financial Analytics 1 (1.5 Credits)

The course will talk about advanced financial analytics subjects. Each term’s content will be unique.

  • FINE 696: Advanced Topics in Financial Analytics 2 (1.5 Credits)

The course will talk about advanced financial analytics subjects. Each term’s content will be unique.

  • INSY 669: Text Analytics (1.5 Credits)

An introduction to the fundamentals of text mining and text-based predictions, covering the categorization and classification of a range of documents, and the use of popular scripts, packages, and libraries like SentiStrength (for sentiment analysis). The use of text analytics to address current business issues.

  • INSY 670: Social Media Analytics (1.5 Credits)

Methods and tools for utilizing the power of social media, with a focus on a range of issues relating to businesses’ social media initiatives, including metrics to record pertinent results and predictive analytics to connect social media chatter to business performance.

  • INSY 671: Analytics and Open Innovation (1.5 Credits)

The use of data analytics in the context of open innovation is thoroughly introduced in this course. Students will rely on prior knowledge from Masters Program courses as well as discover new tools and strategies that may be used to address open innovation-related challenges in the real world.

  • INSY 672: Healthcare Analytics (1.5 Credits)

Students will gain practical experience working with real-world datasets to investigate how data analytics can be used to forecast and understand disease outbreaks, how analytics can be used to enhance hospital operations, and how analytics can be used as decision support for doctors to diagnose and treat patients.

Students should be able to understand the changes occurring in the delivery of healthcare services as a result of analytics by the end of the course, as well as the role and opportunities for analytics to lower costs and enhance the quality of healthcare in local communities.

  • INSY 673: Security Analytics (1.5 Credits)

A thorough introduction to data analytics within the context of information security is provided in this course. The ability to use data analytics to aid in the visualization, detection, and analysis of information security data will be understood by the students. The tools and methods that can be used to analyze real-world datasets will be introduced to the students.

  • INSY 695: Advanced Topics in Information System (1.5 Credits)

Current and developing information systems topics. Each term’s course material will be unique.

  • MGPO 695: Advanced Topics in Strategy Analytics (1.5 Credits)

Present-day strategy analytics topics. Each term’s course material will be unique.

  • MGSC 670: Revenue Management (1.5 Credits)

Students will learn about revenue management (RM) strategies used in the following industries: air travel, hospitality (hotels, cruises, theme parks, and casinos), car rental, broadcasting, media, natural gas storage and transmission, electricity generation and transmission, and show business (concerts, theaters, and sporting events).

The majority of applications are recent and have been made available by improvements in technology, data, and decision analytics. Forcing customers to pay different prices for essentially the same goods raises legal questions as well as consumer outrage. Additionally, these topics will be covered in the course. The subjects covered include discount pricing, customized pricing, overbooking, capacity allocation, and network management.

  • MGSC 672: Ops and Supply Chain Analytics (1.5 Credits)

Analytical models are covered throughout the course that investigate the main problems with supply chain design and management. The majority of the course is focused on data-driven decision models that explicitly address uncertainty. Supply network design, inventory centralization, the value of information, and contracts are some of the subjects covered.

  • MGSC 673: Introduction to AI & Deep Learning (1.5 Credits)

Neura networks are used as an introduction to deep learning, which uses data and tasks like classification, forecasting, and data production to learn from it. the origins of deep learning and the most recent research’s applications. using deep learning in a real-world setting and utilizing tools like Keras, hyperparameter tuning, image classification approaches, back propagation, LSTMs, and autoencoders.

  • MGSC 695: Advanced Topics in Management Science (1.5 Credits)

Current and upcoming operations management topics. Each term’s course material will be unique.

  • MRKT 671: Advanced Marketing Analytics (1.5 Credits)

The course will give students practical experience utilizing these methods with real datasets and introduce them to sophisticated marketing analytic approaches available to managers. Lectures with step-by-step explanations of analytical approaches using real data will be the primary teaching tool. Then, data analysis-related examples will be added to these. Customer and product analytics techniques are among the subjects discussed.

  • MRKT 672: Internet Marketing Analytics (1.5 Credits)

What distinguishes internet marketing? Introduction to search engine optimization in online marketing. Search advertising and privacy issues with inbound marketing. Privacy concerns and online tracking.

  • MRKT 673: Pricing Analytics (1.5 Credits)

Introduction to fundamentals of pricing optimization and price-response functions. Models of demand are estimated using data. Personalization, consumer values, and value-based pricing. Pricing differentiation strategies. Pricing in light of a limited supply. Consultation on a team project.

  • MRKT 674: Retail Analytics (1.5 Credits)

The following subjects will be covered in this course: market basket analysis, assortment planning and category management, store placement and trade area analysis, forecasting, and purchasing decisions.

  • MRKT 696: Advanced Topics in Marketing Analytics (1.5 Credits)

Recent and developing topics in marketing analytics. Each term’s course material will be unique.

  • ORGB 671: Talent Analytics (1.5 Credits)

Learning goals include gaining experience in gathering and integrating performance and personnel outcome data, developing and practicing analytical skills for these types of data, cultivating knowledge and understanding of the potential and limitations of talent analytics, and being able to apply what is learned in class to future organizational settings.

  • ORGB 672: Organizational Network Analysis (1.5 Credits)

Learning goals include gaining experience in gathering and representing organizational network data, developing and practicing the skills necessary to analyze network data, cultivating knowledge and understanding of how social networks are related to significant organizational outcomes, and developing the ability to apply what is learned in class to future organizational settings.

  • ORGB 695: Advanced Topics in Organizational Behavior (1.5 Credits)

Organizational behavior’s newest emerging topics. Every term, the curriculum will change.

Admission Requirements

The McGill MSBA program has specific admission requirements that applicants need to fulfill. Here is an overview of the requirements:

  • Education:

You must include each university-level institution you have attended to date on your application and attach a comprehensive record of study for each. All courses and grades for each year of attendance must be included on transcripts. Transcripts are also required for any courses taken at other universities, such as transfer credits, exchanges, or unfinished degrees.

Transcripts from McGill do not need to be uploaded. They demand a copy of the actual diploma to be provided in addition to the transcripts for universities where a degree was received but the year is not specified on the transcript.

Transcripts in languages other than English or French must be accompanied by a certified translation into English or French. Only approved applicants will be asked to present an official transcript from each school attended. All admitted students will be sent further mailing instructions detailing where to send these papers.

  • Work Experience:

At the time of application, a minimum of 2 years of full-time work experience after completing the Bachelor’s degree is required.


Except for individuals with a graduate or undergraduate degree from a Canadian or US university, all applicants must take the GMAT or GRE. There will be no exceptions or exemptions.

When registering for a test, request that the testing agency send the results electronically to McGill University. Please keep in mind that it may take 10-20 business days for your GMAT/GRE scores to appear in your application portal after they have been submitted.

  • English Proficiency:

The TOEFL or IELTS is required for candidates whose home tongue is not English and who have not finished a degree in an English-speaking nation. At-home tests are not accepted for admission; only examinations done at Test Centers are allowed.

  • Letter of recommendations:

You must include the names and institutional email addresses of two referees who may evaluate your talents on the application form. Following the submission of your application, McGill will contact these referees and request that they upload their references.

Your referees should be people who have had direct experience judging your performance and potential. They might be professional or academic, but at least one academic reference letter should be included. You can either email this recommendation form to referees for completion, or they can write their own reference letters.

You are excused from taking a proficiency test if you have finished an undergraduate or graduate degree at a recognized institution where English is the language of instruction but not in an English-speaking country. 

Meeting these admission requirements is essential to be considered for the McGill MSBA program.

McGill Campus and Location

Location and Regional Benefits

McGill University benefits from its strategic location in Montreal, Quebec, Canada. Here are the key advantages:

  1. Cultural Hub: Montreal is a vibrant multicultural city with a rich history and diverse population, providing students with a unique cultural experience and exposure to various perspectives.
  2. Language Opportunities: Being in Quebec, where French is widely spoken, students have the chance to immerse themselves in a bilingual environment, enhancing their language skills and cultural understanding.
  3. Networking Opportunities: The city serves as a major economic hub in Canada, offering students access to a wide range of industries and networking opportunities with potential employers.
  4. Research Collaborations: McGill’s location in Montreal fosters collaboration with other top-notch research institutions, facilitating cutting-edge research projects and academic partnerships.
  5. Arts and Entertainment: Montreal is renowned for its vibrant arts and entertainment scene, providing students with numerous opportunities to explore music, theater, festivals, and other cultural events.
  6. Outdoor Activities: The city offers beautiful parks, scenic landscapes, and outdoor recreational activities, allowing students to balance their academic pursuits with nature and leisure.
  7. Internship Possibilities: Montreal hosts a variety of international organizations and companies, presenting students with valuable internship prospects to gain real-world experience.
  8. Access to Government Institutions: Being in the heart of Quebec’s political landscape, students can engage in discussions and internships with various government institutions, fostering a deeper understanding of public policy and governance.

These factors make McGill University an attractive and enriching academic destination for students seeking a well-rounded and culturally diverse education.

Resources Available to McGill Students

McGill University offers a wide range of resources and support to enhance the student experience and facilitate personal and professional development. Here are some notable resources available to students:

  1. McGill Library: Access to extensive physical and digital collections, research support, and study spaces.
  2. Student Wellness Hub: Provides counseling services, health care, and wellness programs to support students’ mental and physical well-being.
  3. Career Planning Service: Assists students with career exploration, job search strategies, and networking opportunities.
  4. Teaching and Learning Services: Offers academic support, workshops, and resources to enhance students’ learning experience.
  5. Athletics and Recreation: Provides sports facilities, fitness classes, and recreational activities to promote a healthy lifestyle.
  6. International Student Services: Supports international students with immigration advice, cultural adaptation, and social events.
  7. Tutoring Services: Offers peer tutoring and academic assistance in various subjects.
  8. Financial Aid and Scholarships: Provides information and assistance on financial aid options and scholarships to eligible students.

In a nutshell, McGill University offers a comprehensive range of resources for its students. These resources contribute to a well-rounded and supportive environment for students’ personal, academic, and leadership development.

Program Costs and Financial Aid

Tuition and fees

The tuition fees for the McGill MSBA program amount to $57,600. Additionally, there is an estimated living cost of $19,800. It’s important to note that tuition fees are subject to change, so it’s advisable to visit the McGill MSBA tuition fee page as well.

Scholarships and financial aid options

Pursuing an MSBA is a significant investment in your future and a crucial decision. McGill understands the importance of supporting exceptional candidates in realizing their aspirations. That’s why they offer a range of grants and merit-based scholarships to deserving individuals.

Upon acceptance, all MSBA students at the Desautels Faculty of Management are considered for merit-based entrance scholarships. You may be given one if you are one of our most excellent candidates. There is no extra application required to be considered for this award. Selected applicants will get additional information on the scholarship award procedure along with their admission offer. 

This reward is disbursed to the student’s fee account in two payments, the first in September and the second in January. Please keep in mind that the amount of the admission scholarship varies.

Recap of Key Points

  1. Education: Applicants must include each university-level institution they have attended to date on their application and attach a comprehensive record of study for each. All courses and grades for each year of attendance must be included on transcripts. Transcripts are also required for any courses taken at other universities, such as transfer credits, exchanges, or unfinished degrees.
  2. Work Experience: A minimum of 2 years of full-time work experience is required.
  3. GMAT/GRE: All applicants must take the GMAT or GRE. There will be no exceptions or exemptions.
  4. TOEFL/IELTS: Valid TOEFL or IELTS scores are required if the medium of instruction was not entirely in English.
  5. Campus Location: McGill’s Montreal location offers cultural diversity, language opportunities, networking, research collaborations, arts, outdoor activities, internships, and government access.
  6. Regional Benefits: McGill’s strategic location in Montreal, Quebec, Canada offers regional advantages like cultural exposure, language immersion, economic networking, research collaborations, arts scene, outdoor activities, internships, and government engagement.
  7. Resources Available: Students at McGill University have access to a wide variety of resources. These tools enhance the development of students’ leadership, academic, and personal skills in a well-rounded and encouraging atmosphere.
  8. Program Costs: Tuition fees for the McGill MSBA program amount to $57,600, with an estimated living cost of $19,800.
  9. Financial Aid: McGill offers grants and merit-based scholarships for exceptional candidates. Applicants can also explore other funding options to support their MSBA journey.
  10. Reminder: Visit the official McGill website for detailed and updated information on the McGill MSBA program, including admission requirements, financial aid options, and any recent changes.

Call to action or next steps for interested readers

If you found this blog post on the McGill MSBA program insightful and are considering pursuing an MSBA at McGill, I encourage you to stay tuned for our upcoming blog on “How to Get into the McGill MSBA Program.” This blog will delve into crafting a robust application, including writing compelling essays, securing solid letters of recommendation, and presenting yourself effectively during interviews. We will also cover essential deadlines and offer valuable tips to enhance your chances of admission.

Whether you’re a prospective full-time or part-time student, this upcoming blog will serve as a valuable resource to navigate the application process successfully. It will equip you with the knowledge and insights to present your skills, experiences, and aspirations in the best possible light.

Getting into the McGill MSBA program is an exciting journey, and we are here to support you every step of the way. Stay tuned for our comprehensive guide on “How to Get into the McGill MSBA Program” and take the first step towards realizing your academic and career goals.

Remember, preparation and a thorough understanding of the application process can make a significant difference. We look forward to helping you navigate the path to your dream MSBA program at McGill.

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