Get ready to delve into the core concepts and implementation of machine learning. What does that mean exactly? Well, based on practical examples from well-known systems like Netflix, YouTube, or Twitter, your instructor will describe some fascinating big data problems, introduce the standard algorithms used to address them, and present libraries used to implement those algorithms.

You'll cover topics like mining frequent item sets, clustering, stream analysis, similarity search, machine learning, and recommendation systems.

Knowledge of Excel, SQL, Python, and/or R, as well as statistics and probability, is crucial for you to be successful in this course. If you do not have knowledge in these areas, we strongly recommend that you take Intro to Data Analysis with Excel (CEBD 1300), Intro to SQL (CEWP 215), Intro to R (CEBD 1200), and/or Intro to Python (CEBD 1100).

Your Takeaways

This course is a great way to help you:

• Understand the broad classes of methods used to address big data challenges;

• Learn the main algorithms to implement those methods.

• Apply those algorithms to realistic problems using existing software libraries.