This course is part of the Big Data Programming and Analytics certificate program. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. This course examines developing solutions for extracting and analyzing big data sets using various technologies. Students will learn Scala and Java, which are the fundamental part of Spark, Kafka, and HBase. The focus will be on Apache Spark and its different aspects. Students will explore real-time analytics tools such as Kafka and HBase. NoSQL will be covered in this course. Course activities will include instructor presentations, required readings and experiential learning activities (i.e. case studies, group discussions, projects, etc.).

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.

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 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.