Program Overview

The Technical Data Analytics post-graduate program will provide you with a solid foundational skill set related to data analysis and its supporting IT technologies. You’ll explore database and data warehouse design for business intelligence systems, big data security and governance, machine learning and AI in big data, and data analysis techniques and technologies.
international only
No
PGWP
No

Program Details

Program Code
TDA2
Credential:
Ontario College Graduate Certificate
Duration
30 Weeks

Canadian Students

Start Dates
Locations
Availability

Full Time Offerings

2025 May
London
Open
2025 September
London
Open
2026 January
London
Open
2026 May
London
Open

Your Learning Experience

TDA2 is available for domestic students only. International students can enrol in TDA1.

Become a Data Scientist with our Graduate Certificate program

The Technical Data Analytics graduate certificate program will provide students with the skills needed to dive into data using various technologies to discover trends and find solutions to business problems. Students will also gain insights into machine learning fundamentals, big data technologies and database management.

What you can expect to learn from in our data analytics graduate certificate program:

  • Foundations of data analytics 
  • Data modelling and schema design 
  • Statistical analysis
  • ETL processes and data integration 
  • Data warehousing
  • Big data systems
  • Data mining and predictive modelling
  • Big data analytics 
  • Text and social media analytics 
  • Machine learning fundamentals 
  • Data technology and business

Students will graduate from this data analytics graduate certificate program with confidence that their data analytics skills will help their future employers mitigate risk, improve processes and productivity, and make better decisions with the use of data and the actionable insights gained from it.

Laptop and technical requirements

Please note, this program requires a laptop. It is recommended that students use a PC laptop vs. a Mac laptop, as Windows is required to be able to load program-specific software. For more information on specific requirements, visit the Laptop Requirements page on the Fanshawe CONNECTED website.

Career Information

Fanshawe’s Technical Data Analytics program will prepare graduates to take advantage of the growing opportunities in the field of information technology. Graduates can expect to be hired as the following:

  • Data Scientist - uses advanced analytics technologies to support the identification of trends, scrape information from unstructured data sources and provide automated recommendations
  • Data Analyst - designs, develops and administers data management solutions, develops and implements data administration policies, standards and models
  • Business Intelligence Analyst - gathers, cleans and analyzes data like sales revenue, market information and consumer engagement metrics of a business
Related Programs

Academic School

School of Information Technology
 
International Admission Equivalencies
Admission equivalencies for Fanshawe depends on your country of study. Please enter your location to see the requirements for your country below.

Courses

Level 1
Take all of the following Mandatory Courses:
COOP-1020Co-operative Education Employment Prep1
This workshop will provide an overview of the Co-operative Education consultants and students' roles and responsibilities as well as the Co-operative Education Policy. It will provide students with employment preparatory skills specifically related to co-operative education work assignments and will prepare students for their work term.
INFO-6174Intro to Data Analytics3
This course is designed to acquaint students with the fundamental principles and techniques of data analytics. The course explores the processes involved in collecting, processing, and interpreting data to extract meaningful insights and support decision-making. Students will learn the basics of data manipulation, visualization, and statistical analysis using popular tools and programming languages such as Python or R.
INFO-6185Data Modeling and Schema Design4
This course delves into the principles and practices of structuring data for efficient storage, retrieval, and analysis. The course focuses on teaching students how to design effective database schemas, emphasizing the importance of logical and physical data modeling.
INFO-6175Statistical Analysis 13
This course introduces students to the principles of statistical reasoning and analysis. The course covers essential topics in descriptive and inferential statistics, providing students with the tools to make sense of data and draw meaningful conclusions. Students will learn how to summarize and visualize data, calculate measures of central tendency and dispersion, and understand probability distributions.
INFO-6176ETL Processes and Data Integration4
This course focuses on Extract, Transform, Load (ETL) processes-a crucial component of data warehousing and business intelligence. This course is designed to familiarize students with the principles, techniques, and tools involved in collecting, transforming, and integrating data from various sources into a unified and accessible format. The course includes hands-on exercises using popular ETL tools and languages
INFO-6177Introduction to Data Warehousing3
This course is designed to provide students with a comprehensive understanding of the fundamental concepts and principles of data warehousing. The course focuses on the architecture, design, and implementation of data warehouses and Data Lakes. Practical aspects of the course may involve hands-on exercises in designing and building a simple data warehouse, understanding the role of star and snowflake schemas, and using tools commonly employed in the field.
INFO-6184Data Technology and the Business4
This course explores the intersection of data and business strategies, focusing on how technology is leveraged to drive decision-making and innovation within organizations. Students will learn about the role of data in business decision-making, the technologies that enable efficient data management, and the integration of data-driven insights into business strategies. Key topics will include data governance ethical considerations, privacy concerns, and regulatory aspects related to the use of data in business contexts.
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Contact/Questions