Skip to main content

Course

Big Data Analytics for Business

Signal your interest
Course code
CEBD 1151
Duration
30 hours
Every day we have to take decisions based on limited resources. Limits on money, assets, technology, materials and specially time. In this course you will learn how companies, governments and organizations are taking data-driven decisions to better manage their resources and improve many aspects their business and our lives. Here you will learn how to identify the different challenges in Big Data and how to use Data Analytics to solve them. From regression, to classification, clustering, recommendation systems and natural language processing. You will see how businesses are leveraging analytics and machine learning to solve these problems and how you can apply in your own use cases.

Knowledge of Excel and/or SQL is highly recommended. If you do not have knowledge in these areas, we strongly recommend that you take Intro to Data Analysis with Excel (CEBD 1300) and Intro to SQL (CEWP 215).

Note that you will be required to do 5-10 hours of work per week outside of class time. Those with little to no prior knowledge will require more time to gain familiarity with the concepts.

Upcoming date(s)

There are no upcoming dates at this time.

Your takeaways

• Understand the challenges in big data analytics;
• Understand the big data analytics project life cycle;
• Identify business opportunities with data analytics and machine learning;
• Build a data driven solution on real world datasets.

Our approach

This course employs project-based learning that's focused on the acquisition of practical, real-world skills and not just theory. You'll be taught by an industry pro using state-of-the-art technologies and software. This course is designed for the students to meet regularly during live synchronous learning in an online virtual classroom (Zoom).

Who benefits the most?

Individuals who want to improve the performance of their organization by harnessing Big Data.
• Professionals who want to leverage data for better decision-making.
• Entrepreneurs with projects that could benefit from data analytics.
• Students in fields like geography, biology, psychology, humanities or any other field with big data.
• IT professionals who want to transition to Big Data from more traditional sectors.
Back to top

© Concordia University