Power up your data career with a Data Analytics, Big Data, and Predictive Analytics certificate
Today, most business decisions are powered by data, making data science professionals highly in-demand. Want to start working as a data analyst in this lucrative field, or give your data science career a boost? The Chang School offers a Certificate in Data Analytics, Big Data, and Predictive Analytics that will set you up for success in this fast-paced field.
Our data science courses emphasize hands-on experience with data analysis tools and techniques, providing you with practical big-data skills that are directly applicable in the job market – and to a wide range of industries and roles. We also offer a capstone project course, so you can apply your newfound data science training to real-world problems.
You can finish all our data science courses online in as little as two terms. We offer a ton of career support to our learners – something that isn’t commonly found in other data science programs.
Our data science certificate is also recognized by an international, industry-leading association, The Institute for Operations Research and the Management Sciences (INFORMS), and meets the requirements for you to become a Certificated Analytics Professional (CAP®), giving our learners the opportunity for data science certification – and a competitive edge in the data analytics, big data, and predictive analytics job market.
Ready to embark on an exciting career in data science? Let’s get started.
Who should take this Data Analytics, Big Data, and Predictive Analytics certificate?
- You’re a professional looking to build your skill set in technically applied data analysis, machine learning, and predictive analytics, together with data organization and management, to advance in your career or change your career to data analytics
- You’re a analyst who wants to advance their skills in big data analytics
- You’re a manager or business leader who works with data, manages data analytics projects or leads teams of data analysts
- You want a data analyst or data scientist career and wish to gain the hands-on experience in analytics, coding, tools, and statistics needed to prepare and analyze data to make business decisions
What will you learn while taking the Data Analytics, Big Data, and Predictive Analytics certificate?
You’ll learn how to:
- Excel in the data analytics domain, understanding data types and structures, data manipulation and cleaning, statistical analysis, data visualization, machine learning techniques, and programming languages for querying data, along with the business context to provide insights and recommendations effectively
- Enhance your practical experience in data analytics and machine learning, as well as your knowledge of AI, to progress to senior roles within the data-science domain
- Understand the different types of databases and how to manage and organize them
- Use statistics and machine-learning techniques to prepare, model, and analyze data
- Use programming languages like R and Python to turn data into insights that can help a business
- Complete data analytics assignments and final projects that you can include in your portfolio when applying for jobs
You’ll also learn how to use these tools:
- Programming languages: R, Python
- Database management systems: MySQL, MongoDB
- Data collection and query tools: XPath, XQuery
- Data visualization tools: Tableau
- Libraries for data analysis: Python Libraries (pandas, NumPy, SciPy, Matplotlib), R Packages (dplyr, ggplot2)
- Integrated development environments (IDEs): RStudio, MS-VSCode, MySQL Workbench, Robo3T
What career support is available to you?
During your certificate, we offer extensive career help, including:
- Virtual mentor services
- Alumni networking
- Synchronous weekly online sessions
- Educator support
- Tutoring services
- Career discussion forums
Career Options
This certificate can prepare you for jobs like:
- Data analyst, including marketing data analyst and financial data analyst
- Data scientist, including machine learning scientist and AI research scientist
- Business intelligence analyst, including business intelligence consultant and business intelligence developer
- Business analyst, including IT business analyst and financial business analyst
- Predictive analyst including risk analyst and customer insight analyst
- Data architect, including data warehouse architect and data integration architect
- Database analyst, including database developer and data administrator
- Big data analyst, including big data consultant and big data solutions analyst
- Chief data officer, including head of data governance and director of data strategy
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
- And permission of the academic coordinator
Frequently Asked Questions
Can I take more than one analytics course in the evening and still hold my full-time job?
Yes. It is possible to take more than one analytics course in one term and still hold your full-time job. 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 may opt to take CMTH 642 and CIND 110 in Term 3 (most learners choose to take these two courses together). In Term 4, you’d take CIND 820.
Can any of the data science course requirements be fulfilled by substitution or transfer credit?
The unique and specialized nature of these courses mean that very few, if any, equivalents exist elsewhere. Learners should not depend on using prior learning or study elsewhere to meet certificate requirements.
Are there any company affiliations or career placements available as part of this certificate program?
There are no direct corporate associations or career placements available. However, companies and organizations seeking data analysts and data scientists do contact the Program Director with job postings and the postings are emailed out to all learners in the sixth and final course, CIND 820 - Big Data Analytics Project. They’re also sent out to recent certificate graduates. The Chang School can provide career advisement support upon request, such as resumé preparation and one generalized letter of reference for applying to all job positions.
What programming languages are used to teach this data science certificate?
The certificate is taught using R-language and Python.
What prerequisites or professional experiences are recommended for this certificate?
This is an open admissions program. No previous background is required. However, due to the rigorous nature of this certificate, applicants wondering if they’re a good match should send a current resumé to Client Services at ce@torontomu.ca.
Are there any specific technical requirements for course work?
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, loading R packages, and using Python libraries.
For the processor, Apple's M1 Chip, Intel Core i5 or i7 is preferable.
The storage unit of the learner's computer must be a solid-state drive model and needs to 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 tower PC configuration should I have to complete the capstone course?
This checklist will ensure you have the necessary computer and software requirements to complete this course:
- I have access to a reliable computer with the minimum recommended requirements (dual-core 1.6 GHz or faster processor, 200GB of disk, 8GB of RAM) to use the software in this course (e.g., Python).
- I have internet access and an adequate data allowance.
- I can access Google Meet or Zoom and know how to use it.
Each learner will be granted access to a virtual desktop equipped with all the tools to complete their project. These virtual desktops will be available until the end of the enrolled term and will be archived by then. Here is a list of tools that will be included in these virtual desktops:
- Programming tools: R, SAS, Python, XPath, and XQuery
- Data collection and storage tools: MySQL, MongoDB
- Visualization tools: Tableau
- Advanced analytics tools: Apache Spark, Weka
- File system: Hadoop Distributed File System
- Extract, transform, and load Tools: Apache Hive, Sqoop>
- IDEs: Colab/Jupyter notebooks, MS-VSCode, RStudio, MySQL Workbench
Questions?
Contact Client Services ce@torontomu.ca
