Data Analytics, Big Data, and Predictive Analytics

Data analytics is critical in almost all industries, from business and finance to government and healthcare. This is driving the need for people who can analyze and integrate data into business decision-making.

Not only does this certificate equip you with that skill set, it also meets the requirements for you to become a Certified Analytics Professional (CAP®). Toronto Metropolitan University is recognized by an industry-leading association, The Institute for Operations Research and Management Sciences (INFORMS).

Career-Ready Support Offered

While enrolled in the Certificate in Data Analytics, Big Data, and Predictive Analytics (or Certificate in Practical Data Science and Machine Learning), you will receive a variety of support, including:

• Educator support: instructors, teaching assistants, and data analytics tutors provide support for your hands-on practice with virtual data analytics lab activities.

• Synchronous weekly online sessions: in these Zoom sessions, the teaching team, with practitioner-expert, credentialed data scientists as instructors and teaching assistants, addresses learners’ questions and strengthens their hands-on data analytics skills and working knowledge for future jobs in the field.

• Discussion forums: the teaching team will monitor discussion forums where learners ask questions on data analytics applied to lab activities, readings, video lectures, assignments, and projects.

• Virtual tutor services: the virtual mentor is offered at no cost upon request to certificate registrants taking courses for one-on-one Zoom meetings and for consultations by email about the coursework, assignments, final projects, and career advising.

• Career support: data science job search and career advice will be offered during the final capstone course, CIND 820: Big Data Analytics Project.

• Alumni networking support: participating alumni will receive informal career and networking support through LinkedIn for certificate candidates and graduates.

Industry and Careers

This certificate can lead to a career in various roles. Here are some examples:

• Business analyst

• Data analyst

• Data scientist

• Financial data analyst

Who Should Get This Certificate?

• Recent graduates or individuals who 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

• Professionals looking to build their skill set in technically applied data analysis , machine learning, predictive analytics, and data organization and management to advance in their career or change their career to data analytics

• Data analysts who want to advance their skills

• Managers and business leaders who work with data, manage data analytics projects, or lead teams of data analysts

What will you learn?

After completing this certificate, you will be able to do the following:

• Provide a well-refined hands-on education that covers essential skills and knowledge to excel in the data analytics domain, such as understanding data types and structures, data manipulation and cleaning, statistical analysis, data visualization, machine learning techniques, programming languages for querying data, and understanding the business context to provide insights and recommendations effectively.

• Gain insight into the next steps for your entry-level or mid-level data analytics career and 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.

Tools in use include the following:

• R

• SAS

• Python

• Tableau

• XPath and XQuery

• Structured Query Language (SQL)

• Hadoop (MapReduce)

Data Collection and Storage Tools

• MySQL

• MongoDB

Analytics Tools

• Python Libraries for Data Analysis

• R Packages for Data Analysis 

Integrated Development Environment (IDE)

• MySQL Workbench

• RStudio

• MS-VSCode

• Robo3T