Organizations and data professionals have tremendous opportunities to analyze Big Data whether that data exists internally within the organization or externally. This course will examine the basic technical concepts and challenges of Big Data. Participants will learn how to use data analytics tools such as Hadoop, Hive or Spark. A capstone project will be included where participants will problem-solve a real-world Big Data scenario using the tools taught in the course.
Professionals working with data from various sectors in healthcare, finance, insurance and marketing, data science and data analytics professionals.
Upon successful completion of the course, students will be able to:
- Describe the basic technical concepts and challenges of Big Data.
- Explain and apply data cleaning and feature extraction methods to Big Data.
- Investigate machine learning and statistical learning algorithms for processing Big Data.
- Demonstrate the use of data analytics tools such as Hadoop and Hive.
- Review parallel processing tools for Big Data such as MapReduce and Spark.
- Discover how to draw conclusions from analytics through real-world case studies.
- Complete a capstone project that draws on skills gained from the course to address a real-world problem in small teams.
Admission to the program requires an Undergraduate degree or College Diploma plus the completion of a Basic Statistics course.
Applies Towards the Following Certificates
- Data Science Certificate : Required Courses
*Course details are subject to change.