Technical Data Analytics (Co-op)
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Program Overview
The Technical Data Analytics post-graduate program emphasizes foundational and advanced technical skills for data analysis focusing on IT infrastructure, high-performance computing and enterprise-level data management. You’ll gain proficiency in programming languages such as Python, R, and SQL and advanced database design concepts tailored for large-scale data operations. You'll also explore big data technologies, machine learning and AI applications with hands-on training in a unique, high-end dedicated server environment that supports large-scale data processing, predictive modelling, statistical analysis and data visualization.
Program Details
Program Code
TDA2
Credential:
Ontario College Graduate Certificate
Duration
30 Weeks
Canadian Students
Start Dates
Locations
Availability
Full Time Offerings
2026 January
London
Open
2026 May
London
Open
2026 September
London
Open
2027 January
London
Open
2027 May
London
Open
Your Learning Experience
Become a Data Scientist with our Graduate Certificate program
TDA2 is only available to domestic students. A version for international students can be found at TDA1.
This Technical Data Analytics graduate certificate program will provide students with the skills to dive into data using various technologies to discover trends and solve business problems. The program emphasizes enterprise-grade data warehousing and data lake architectures, enabling students to work with structured and unstructured data in real-time and batch-processing scenarios. Students will develop a comprehensive understanding of ETL (Extract, Transform, Load) pipelines and database design. Machine learning, AI applications, and statistical analysis are integrated into the coursework to ensure graduates are prepared for mission-critical IT and data analysis roles. This program also includes a paid co-op work term for valuable hands-on learning experience.
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 (Extract, Transform, Load) processes and data integration
- Data warehousing
- Big data systems
- Data mining and predictive modelling
- Big data analytics
- Text and social media analytics
- Technical machine learning applications
- Data technology and business
- Programming for data manipulation and analytics
By the end of the program, graduates will be equipped to navigate the complexities of modern data ecosystems, making them well-suited for careers in data engineering, IT infrastructure management, and advanced analytics within high-performance computing environments.
Laptop and technical requirements
Please note that 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
Admission Requirements
Ontario College Diploma, Ontario College Advanced Diploma,
Degree or equivalent in computer
science/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.
English Language Requirements
English Language Requirements
TOEFL iBT 88
IELTS Academic Overall score of 6.5 with no score less than
6.0 in any of the four bands
CAEL Overall score of 70 with no score less than 60 in any of
the four bands
PTE Academic 59
Cambridge English Overall score of 176 with no language skill
less than 169
ESL4/GAP5 Minimum grade of 80% in Level 9, 75% in Level
10
Duolingo Overall score of 120, with no score lower than
105
Recommended Academic Preparation
Recommended Academic Preparation
Prospective students should possess a solid foundation in Mathematics, Statistics or Actuarial Sciences.Applicant Selection Criteria
Applicant Selection Criteria
Where the number of eligible applicants exceeds the available
spaces in the program, the Applicant Selection Criteria will
be:
Preference for Permanent Residents of Ontario
1. Receipt of Application by February 1st (After this date,
Fanshawe College will consider applicants on a first-come,
first-served basis until the program is full)
2. Achievement in the Admission Requirements
Courses
| Level 1 | ||||
| Take all of the following Mandatory Courses: | ||||
| COOP-1020 | Co-operative Education Employment Prep | 1 | ||
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-6174 | Intro to Data Analytics | 3 | ||
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-6185 | Data Modeling and Schema Design | 4 | ||
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-6175 | Statistical Analysis 1 | 3 | ||
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-6176 | ETL Processes and Data Integration | 4 | ||
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-6177 | Introduction to Data Warehousing | 3 | ||
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-6184 | Data Technology and the Business | 4 | ||
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. | ||||
Tuition Summary
London
[1] Total program costs are approximate and subject to change. They do not include additional fees such as the health and dental plan, bus pass, or general expenses. Learn more about ancillary and additional fees.