In an increasingly competitive consumer marketplace, decisions around adding new products and services are more important to a company’s success than ever. Students in the Marketing program at McMaster University’s Centre for Continuing Education will research and prepare a report for your company that recommends a new product or service and/or plans its launch.

This course covers advanced-level topics in the areas of data science, machine learning, and technical/software applications. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. They will practice their knowledge of using various technologies as part of the course, such as real-time analytics tools (e.g., Kafka and HBase), NoSQL databases, and cloud technologies. Students will apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization, with support from faculty mentors, who will work with students.

This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. The students learn how to perform exploration of data in order to discover meaningful information to solve problems, and will allow for the application of analytics life cycle in the context of planning to solve a business problem. Emphasis is placed on framing the problem, proposing an analytics solution, communicating with stakeholders, and establishing an analytics-focused project plan. Common data visualization tools and techniques are explored and used as students learn best practices for the presentation and communication of analytical solutions and insights.

This course is part of the Data Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course explores the importance of managing data as an enterprise asset and the processes and components required in terms of the acquisition, storage, sharing, validation and accessibility of data for addressing business problems. An examination of Database Management Systems, database architectures (structured and non-structured) the differences between OLTP (Online transaction processing) OLAP (online analytical processing) as well as the administrative processes (Data Governance) that guide the data lifecycle will be a focus.