Office of Applied Research and Innovation
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Data Analytics Internship

Closed
Toronto School of Management
Toronto School of Management
Toronto, Ontario, Canada
Irene Lasker
Irene Lasker
Career Services Manager
(1)
3
Experience
17/20 project matches
Dates set by projects
Preferred companies
Anywhere
Any
Any industries

Experience scope

Categories
Data visualization Data analysis Data modelling Market research Project management
Skills
business analytics data analysis research competitive analysis project planning
Learner goals and capabilities

Looking to elevate your business, and bring it to the next level?

Bring on students from the Toronto School of Management' Data-Analytics program to be your virtual interns, in a project-based experience.

Students in this program are poised to succeed in the integrated work areas of big data, business analytics, marketing analytics, data mining analytics.

Students are required to complete 240 hours of placement within 12 weeks

These students are looking for both paid and unpaid internships with a preference for paid experiences. Please indicate in your project submission which you are able to offer.

Due to COVID-19 restrictions, student placements will only occur virtually.

Learners

Learners
Diploma
Any level
34 learners
Project
240 hours per learner
Learners apply to projects
Expected outcomes and deliverables

Deliverables will vary depending on the scope of the internship. However, these deliverables must be discussed and agreed upon prior to the start of the internship.

Project Examples

Requirements

Project examples that students can complete may include, but are not limited to:

  • Using 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
  • Enhancing their 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
  • Gaining 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
  • Learning to use specialist data visualization packages and tools such as Tableau, Qlik Sense and D3 to visualize datas
  • Acquiring knowledge to use R, the leading programming language in data science and statistics

Additional company criteria

Companies must answer the following questions to submit a match request to this experience:

  • Q - Checkbox
  • Q - Checkbox
  • Q - Checkbox