Program overview
Admission Requirements
Intakes

Last updated on 2025-06-16

Program overview

Program Overview

The Post-Degree Diploma in Data Analytics at Langara College is a comprehensive program designed for individuals passionate about working with data. This program equips students with the necessary skills to analyze and interpret data, supporting technical and strategic business decisions. With a focus on real-world applications, students will engage in hands-on projects that prepare them for the demands of the data analytics field. The program culminates in a capstone project, allowing students to showcase their knowledge and skills before entering the workforce.

Program Structure

The Post-Degree Diploma in Data Analytics is a two-year full-time program that spans four consecutive terms, allowing students to complete their studies in as little as 16 months. The program is cohort-based, meaning students will progress through the curriculum together, fostering collaboration and teamwork. Key features of the program structure include:

  • Full-time delivery with no part-time option available.
  • Three intakes per year: January, May, and September.
  • A capstone project to apply learned skills in a practical setting.
  • Limited enrolment to ensure personalized attention and support.

Students are encouraged to have a personal computer that meets specific technical requirements to facilitate their learning experience.

Featured Experiences

  • Hands-on experience with industry-standard software applications.
  • Group projects that involve real-life data from various sectors, including telecommunications, finance, and healthcare.
  • Development of project management and team-building skills through collaborative work.
  • Capstone project that allows students to demonstrate their analytical skills in a real-world context.

Career Options

Graduates of the Post-Degree Diploma in Data Analytics can pursue a variety of career paths in Canada, including:

  • Data Analyst: Analyze data sets to identify trends and provide actionable insights for businesses.
  • Business Intelligence Analyst: Utilize data analysis tools to support decision-making processes and improve business strategies.
  • Data Scientist: Employ statistical methods and machine learning techniques to interpret complex data and solve business problems.
  • Market Research Analyst: Conduct research and analyze market conditions to understand potential sales of a product or service.
  • Data Engineer: Design and maintain the architecture that allows for the collection and processing of data, ensuring data quality and accessibility.

 

DISCLAIMER: The information above is subject to change. For the latest updates, please contact LOA Portal's advisors.

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