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McGill SCS Graduate Certificate in Data Analysis for Complex Systems

 

The Graduate Certificate in Data Analysis for Complex Systems is designed to equip learners who do not have a technical background with the fundamentals of complex systems. The program focuses on applying data analysis techniques to better understand different phenomena in fields such as financial technology, organizational management, or digital marketing.

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Type:   Graduate Certificate
Courses:   5
Credits:   15
Time:   Weekday evenings
Delivery:   Online
Unit:   Technology and Innovation
Questions?   info.conted [at] mcgill.ca

 


 


Message From the Academic Program Coordinator
 

So, you are a professional in a non-technical field. A head librarian, maybe, or a manager in public transportation. You might manage an orchestra or own a convenience store. You could be an administrator of an educational institution or in charge of a non-profit. You are surrounded by interesting sources of information. You feel like you should be making proper use of all the data that ticks away around your organization.

You have looked around for options that would allow you to grasp the realm of what is possible and learn to get things done. At times you fiddle with "Computers for Dummies" books at your favourite bookstore, but they do not feel right since you are an intelligent, educated individual.

The books with interesting titles about harnessing the power of data get way too technical before getting to the matters that interest you. You want to do things better and surely there must be something out there to help you achieve that, no?

You are right. There is. This program. Data analysis for complex systems is the heart of what we specialize in. It has been my personal passion for decades. My esteemed colleagues Alejandro Gutiérrez (also into complex networks) and Nabil Beitinjaneh are experts as well, complementing my scientific background with in-depth industrial experience in data analysis and information visualization. Yes, the three of us are geeks. But we have the ability to vulgarise the power of data and computational tools to non-experts from diverse backgrounds.

Together with an experienced team of course lecturers, we deliver a set of courses that gradually empower you to identify what data you have within your reach, how you can begin to gather and store that data, and what you can do with it to gain insights into how things work.

In this program, we will discuss technical terms on a need-to-know basis and offer you asynchronous learning modules to revisit things in depth should you feel the need.

Every course in this program consists of modules covering diverse application areas and fields of science, each initiating with an enticing story – a real-world case study or a carefully crafted hypothetical scenario designed to lead you to discover novel concepts and tools. Through interactive exercises and discussions with classmates, you gain a conceptual understanding of the assumptions, steps, possibilities, and limitations of useful tools and techniques as well as hands-on experience in building and using computational models and tools to solve various types of problems.

This program is not about getting a piece of paper with a fancy seal on it. Yes, it is nice. Yes, you can frame it. But what you will be most proud of showing off are your new skills and ideas on how to get things done.  

Elisa Schaeffer
Academic Program Coordinator


Key Features
 
  • Improve your understanding of systems, organizations, processes, and situations by identifying, gathering, and processing data with the proper tools.
  • Learn how to gather data and apply computational tools to process, analyze, and represent data to gain actionable insights that open opportunities for new and improved processes.

Who Should Apply
 

This program is a good fit for you if you are:

  • In a non-technical role and seek to harness the power of data available in the context of your work.
  • An early and mid-career professional with an undergraduate degree in any discipline who strives to side-skill by complementing your existing expertise to become a "knowledge worker" in a specialized field such as financial technology, organizational management, or digital marketing

Learning Outcomes
 

This program will enable you to:

  • Model real-life systems, phenomena, and organizations, their elements, and interactions with mathematical concepts
  • Implement mathematical models of real-life systems, phenomena, and organizations clearly, efficiently, and modularly with open-source computational tools
  • Select mathematical and computational concepts to adequately represent a complex system to gain insight into its structure and function

Courses
 

Required Courses

CCCS 610 Digital Thinking for Data Analysis (3 credits)
CCCS 620 Data Analysis and Modelling (3 credits)
CCCS 630 Complex Systems (3 credits)

Complementary Courses

6 credits from:
CCCS 670 Information Visualization (3 credits)
CCCS 680 Scalable Data Analysis (3 credits)
CCCS 690 Applied Computational Research (3 credits)

OR
another 600-level course offered by the School of Continuing Studies and approved by the academic unit.

Admission Requirements

 

  1. Applicants must hold a bachelor’s degree from an approved university with a minimum CGPA of 3.0/4.0 or 3.2/4.0 in the last two years of full-time academic studies.
     
  2. If your CGPA is lower than the above requirement, please submit the following for consideration with your application:

    a) Letter of Intent: 1 to 2 pages in length, single-spaced, written in English or French, addressing the following:
    • your knowledge that would be pertinent to the program
    • your interest in the field of study and the reasons for applying
    • plans for integrating the training into your current or future career
    • description of your professional experience and its relevance, if applicable, to the program
    • awards received or other contributions
    • any additional information relevant to your application

    b) Curriculum Vitae

    c) Two letters of reference, signed and on letterhead. At least one should be from a current or former employer.

    d) GMAT and/or GRE test score results (optional)
     
  3. Applicants must provide proof of English Language proficiency.

Career Spotlight
 

The Graduate Certificate in Data Analysis for Complex Systems focuses on the core competencies required for learners from technical and non-technical backgrounds to side-skill and incorporate data analysis into their work.


News & Articles

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Be sure to review all the necessary instructions and guidelines to help make your application process smooth and easy.

How to Apply

Application Deadlines

Language Requirements

Financial Aid

Tuition and Fees

International Students

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Need help applying?

Contact us at info.conted [at] mcgill.ca
or call 514-398-6200


Questions about your admission?

Contact us at admissions.scs [at] mcgill.ca
or call 514-398-6200

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