Diploma in Data Analytics Co-op Toronto School of Management

This one-year Co-op diploma in Data Analytics will position you at the forefront of a competitive job market, in which you will develop highly sought-after and employable skills and knowledge to thrive in a data-driven world. Learn how to analyze data using cutting-edge technology or traditional methods to drive proactive decision-making and optimize business performance. With the ability to interpret and transform large sets of data into actionable insights, students can increase business efficiencies.

Our data analytics program is powered by AWS Educate, Perlego, and Tableau.

It integrates classroom learning with possible supervised practical work experience that is directly related to your academic and career goals. Start online, and finish on campus.

Learning Partners

This program is powered by Amazon Web Service Educate (AWS) and Tableau. You will receive access to AWS, where you can test various tools in the platform to earn micro-credentials. You will also develop data visualization skills using software such as Tableau to facilitate the understanding of data findings.

This program is powered by Perlego. It is a digital online library focusing on the delivery of academic, professional, and non-fiction eBooks. It is a subscription-based service that offers users unlimited access to over 2,000 academic publishers and offers an impressive 600,000+ professional and academic titles across 900+ different topics and subtopics for the duration of the subscription.

Why study Diploma in Data Analytics Co-op at TSoM?

	Unbeatable Location: Study in the heart of downtown Toronto, Canada’s business and financial capital.
	Learning Partner: This program is powered by Perlego, Amazon Web Service Educate (AWS), and Tableau. You will be granted access to AWS, where you will be able to test various tools in the platform to earn micro-credentials. You will also develop data visualization skills using software such as Tableau to facilitate the understanding of data findings.
	Student Diversity: Diverse student body from over 100 countries.
	Co-op partners: Extensive network of 100+ co-op partners across a wide range of industries.
	Career Prospect: Graduates can work as a Data Analyst, Database Analyst, Data Mining Analyst, and Data Warehouse Analyst.
	Work Opportunities in Toronto: As a full-time international student, you can work up to 20 hours during your studies and full time during scheduled breaks.

Program Modules

You will have 600 hours of guided learning followed by 240 hours of practical experience in an established business.

The work placement will help you apply the theories you have learned in real business situations. We will help you secure your work placement by sending you for interviews.

1. Data Design

This module is designed to provide you with the skills to enhance the quality and usefulness of data analytics by starting with the intended outcomes.

The module will enable you to consider the information an organization wants to gain from data analytics. This will give you the skills to select the most appropriate data collection method, design deployment approaches, implement data collection techniques and revise instruments and systems to be developed.

This module incorporates automated data collection as well as traditional methods to enable the development of methodologically-sound approaches. Throughout the module, you will be given access to the Amazon Web Services (AWS) virtual environment where you will be able to complete additional assignments and earn micro-credentials.

2. Data Handling and Decision Making

This module is designed to introduce the theoretical concepts and practical applications of data auditing, handling, and decision-making. It will equip you with the skills needed to identify what the findings from data analysis mean and how they can be applied.

You will learn approaches that can be used to audit existing data within an organization to identify gaps, analyze data and generate recommendations from your findings.

As part of your studies, you will be able to learn how to utilize R as it is rapidly becoming the leading language in data science and statistics. Today, R is the preferred programming language for data science professionals in every industry and field.

3. Working with Data using SAS and SQL

This module gives you an opportunity to gain practical experience in handling data using analysis software. The module will also cover theoretical concepts from data design and handling while teaching techniques for working with Structured Query Language (SQL) and SAS.

The module is designed in two parts; part one focuses on learning the fundamentals of SQL with multiple exercises, which is essential for working with databases. You’ll get hands-on experience accessing and manipulating data in order to gain useful insights. In part two, you will learn how to use SAS software for data handling and analysis.

4. Data Visualization and Interpretation

This module is partnered with the data handling and decision-making module and enables you to develop your skills in data presentation to facilitate the understanding of findings, so you can make informed decisions. Data visualizations are a powerful method of making data accessible and understandable to non-specialists.

Through this module, you will learn the appropriate use of graphs and charts as well as the use of specialist data visualization packages and tools such as Tableau, Qlik Sense, and D3 to visualize data and impact the decision-making process.

5. Work Placement

At the conclusion of the program, you are required to complete 240 hours of work placement in a suitable business environment. Appropriate business sectors for placement include marketing, retail, finance and accounting, not-for-profit, customer care, and administration.

Activities performed will vary depending on the work placement site, however, key responsibilities include being supervised by a placement host at all times, observing all workplace and school safety and security procedures, dressing appropriately, interacting with other staff respectfully, courteously, and enthusiastically, learning about the work environment and participating in the daily routine as required.

• Use the skills gained to enhance the quality and usefulness of data analytics by drawing from both the cutting-edge technology of automated data collection as well as traditional methods to enable the development of methodologically-sound approaches.
• Enhance your knowledge of theoretical concepts and practical applications of data auditing, handling, and collecting as well as the accurate tools for this and for effective decision-making.
• Gain practical experience in handling and analyzing data to gain informative and useful insights using analysis software such as Structured Query Language (SQL) and SAS while continuously learning the theoretical concepts in handling and designing data.
• Learn to use specialist data visualization packages and tools such as Tableau, Qlik Sense, and D3 to visualize data.
• Acquire knowledge to use R, the leading programming language in data science and statistics.
• Understand the concepts of, and recognize the importance of professional conduct, and develop and implement strategies to promote professional competence.

Graduates of this diploma can consider career opportunities under NOC 2172 which includes positions such as:

• Data analyst
• Database analyst
• Data mining analyst
• Data warehouse analyst