Gain the Data Analytics Expertise Employers Are Looking For
Today’s organizations rely on professionals who can do more than query big data for outputs – they need data experts who can interpret data accurately, deliver responsible insights, communicate recommendations and maintain them efficiently, and make explainable, traceable decisions. The Chang School’s Certificate in Data Analytics, Big Data, and Predictive Analytics equips you with the technical and analytical skills to interpret data in context, think critically, and expand your capabilities with AI.
You’ll gain hands-on experience with predictive analytics, machine learning, and tools that drive industry – SQL, Python, Power BI, Tableau, and Excel – along with data visualization and data-storytelling skills that help you present your evidence-based analyses and acumen with confidence. Through a real-world capstone project, you’ll apply these capabilities to complex analytical challenges while practicing responsible, explainable use of AI.
Delivered fully online, this comprehensive, degree-credit program can be completed in as little as two terms and offers the depth and credibility that set you apart from short, non-credit crash courses focused only on tools. It’s recognized by the Institute for Operations Research and the Management Sciences (INFORMS) and meets requirements for the Certificated Analytics Professional (CAP) designation – giving you an academic credential and an industry-recognized edge.
Be ready for the next stage of your data career. Get started today.
Who should take this certificate?
This program is designed for professionals who want to advance into high-responsibility roles in data analytics and decision-making. It’s ideal if you:
- Work with data and want to deepen your technical expertise and analytical acumen to progress to senior roles.
- Lead or collaborate with analytics teams and want to strengthen your hands-on practice with data science tools, visualizations and storytelling, to drive better business outcomes.
- Want to apply AI responsibly – using Machine Learning (ML) to extend analysis and produce explainable, traceable recommendations.
- Seek a degree credit, university-recognized credential that builds both analytical mastery and professional credibility.
- Need the flexibility of online learning without compromising academic rigour or quality.
- Want a real-world capstone project that demonstrates end-to-end analytical work – from framing a problem to building models and communicating insights.
What will you learn while taking this certificate?
Build the technical depth, contextual understanding, and critical thinking employers trust for high-responsibility data roles. This certificate goes beyond tools to develop your analytical judgment, clear communication, and confident, explainable decision-making – the capabilities that set senior professionals apart.
You’ll learn how to:
- Frame business problems and put data in context so analyses answer the right questions and drive measurable outcomes.
- Apply advanced data analytics and machine learning techniques (classification, regression, clustering, forecasting) to interpret complex datasets and deliver actionable insights.
- Use AI responsibly: leveraging AI-assisted coding and model-building for efficiency while ensuring explainability, transparency, and reproducibility.
- Master key industry tools – SQL, Python, Power BI, Tableau, and Excel – to collect, clean, model, visualize and communicate data effectively.
- Design and manage data structures and pipelines in relational and NoSQL systems (e.g., MySQL, MongoDB) while practicing governance, privacy, and ethics.
- Strengthen statistical foundations through inference, feature engineering, predictive analytics, and model validation.
- Tell the story through your real-world capstone project, building executive-ready dashboards and narratives that translate findings into clear, traceable recommendations.
Hands-on practice
- AI-assisted development in modern IDEs (e.g., VS Code, RStudio, MySQL Workbench) to improve accuracy, efficiency, and collaboration.
- A professional portfolio featuring applied projects and a real-world capstone, showcasing technical expertise and readiness for senior analytics roles.
Industry-standard tools & environments
- Programming languages: Python, R
- Database management systems: MySQL, MongoDB
- Data visualization tools: Power BI, Tableau, SAS
- Libraries for data analysis: pandas, NumPy, SciPy, Matplotlib, dplyr, ggplot2
- Integrated development environments (IDEs): MS VS Code, RStudio, MySQL Workbench, Robo 3T, and AI-Assisted Coding
What career support is available to you?
You’ll have access to a network of instructors, mentors, and alumni who are active in the analytics field. Career development resources include:
- Virtual mentorship and networking opportunities with data professionals.
- Career discussion forums focused on advancement pathways in analytics
- Weekly live online sessions and instructor support to deepen learning and engagement
- Access to tutoring and advising to help you plan your progression through the program and beyond.
Career Options
This certificate prepares professionals to advance into high-responsibility data and analytics roles across industries, including:
- Data Analyst or Business Intelligence Analyst
- Data Scientist or Machine Learning Strategist
- Predictive or Risk Analytics Consultant
- Data Architect or Solutions Analyst
- Data Strategy or Analytics Manager
- Business Transformation Analyst
- Business Data Strategist
- Data Governance Manager
Certificate Requirements
- 6 required courses
- Cumulative grade point average (GPA) 1.67+
Admission Criteria
Recommended:
- Ontario Secondary School Diploma (OSSD) or equivalent
- With 6 Grade 12 U credits, including English, Mathematics (Advanced Functions and one of either Calculus and Vectors or Data Management), and Science (Biology or Chemistry or Physics)
OR
M credits with a minimum average of 70 percent or equivalent academic status
- With 6 Grade 12 U credits, including English, Mathematics (Advanced Functions and one of either Calculus and Vectors or Data Management), and Science (Biology or Chemistry or Physics)
OR
- Mature student status with 4 years of relevant professional experience
Frequently Asked Questions
Can I take more than one course while working full-time?
Yes. The program’s flexible online delivery allows learners to balance multiple courses alongside full-time work. Most professionals complete the certificate within two to four terms, depending on schedule and workload.
If you’re only able to take two or three courses in Term 1, those courses should be CIND 123, CIND 830, and CIND 119.
In the event that you’re unable to take more than one course in Term 1, start with CIND 123, followed in Term 2 by CIND 830, CIND 119, and CIND 110.
You are encouraged to take CMTH 642 and CIND 110 in the same term (most learners choose to take these two courses together). In Term 4, you’d take CIND 820.
Once you complete the first four courses, you may request to take CMTH642 and CIND820 (the last two courses) in your final term by emailing ce@torontomu.ca.
Can any of the data science course requirements be substituted or transferred?
Because the program’s courses are specialized and updated for industry-adopted currency frequently, substitutions or transfer credits are rarely granted. Each course builds distinct analytical and technical competencies essential for professional high-trust job roles.
Are there any company affiliations or career placements?
While the program does not include formal co-op placements, employers regularly share analytics job postings with the program director, which are circulated to learners in the final course: CIND 820 – Big Data Analytics Project and recent graduates. Participants also have access to career development resources through The Chang School, including portfolio and job search guidance and résumé support.
What programming languages are used?
Learners build applied proficiency in using Python and SQL, the most in-demand languages for data analytics, and gain experience with tools such as Power BI, Tableau, and Excel.
What prerequisites or professional experiences are recommended for this certificate?
No prior coding experience is required. However, due to the program’s rigour and technical depth, applicants should feel comfortable with quantitative concepts and be ready to engage in a challenging, rewarding learning experience. Our team can help assess readiness if you’re unsure about fit at ce@torontomu.ca.
Are there any specific technical requirements for coursework?
Yes.
The minimum required RAM on a learner's computer must be 8 GB, but 16 GB is highly recommended for efficient processing for training and testing heavy machine-learning algorithms, AI-Assisted Coding tools, and using Python libraries.
For the processor, Apple's M2 Chip, Intel Core i5 or i7 or higher is preferable.
The storage unit of the learner's computer must be a solid-state drive model and must be a minimum 256 GB.
A PC or Mac computer can be used to operate the technical tools in the data-science courses.
What laptop or setup is required for the capstone course?
Learners completing the capstone course will receive access to a virtual desktop containing all required software, including Python, MySQL, Power BI, R, Tableau, and Apache Spark. Access remains active through the end of the term to ensure a seamless project experience.
Questions?
Contact Client Services ce@torontomu.ca
