Artificial Intelligence and Machine Learning

Upgrade your data science skills and develop an understanding of Python

Artificial Intelligence and Machine Learning

At a Glance

Type
Professional Education
Enrollment
Open Enrollment
Duration
Eight weeks Open Enrollment
Format
Online
Cost
$2,500

Discover how artificial intelligence (AI) and machine learning are revolutionizing how society operates and learn how to incorporate them into your business—today.

The University of Chicago’s eight-week Artificial Intelligence and Machine Learning course guides participants through the mathematical and theoretical background necessary to take advantage of the machine learning at use in today’s business world.

Designed For

Designed for those who already have previous knowledge working with Python and have a solid understanding of linear algebra.

Learning Objectives

Learn how to make full use of AI to benefit your customers. Throughout this course, you will discover how foundational data science models are leveraged to obtain increased technological power: more computing power, more complex layers, and different sampling techniques that will refine the accuracy of predictions.

After completing the course you will be able to:

  • Interpret big data-related solutions
  • Understand the basic concepts of predictive analytics and machine learning
  • Use the scripting programming languages including Python to process, visualize, and analyze large data sets and implement machine learning solutions

Program Format

  • Eight weeks in length
  • Weekly, self-paced interactive learning modules and assignments are time-sensitive and should be completed by the set deadlines
  • Synchronous sessions and live question and answer sessions 
  • Mentors will provide continuous support and encourage a dynamic and positive learning environment

You will learn to:

  • Design classification and regression models for prediction and reasoning
  • Develop a comprehensive understanding of model interpretation and evaluation
  • Perform unsupervised and supervised machine learning on large-scale, unstructured/structured datasets
  • Understand important pattern discovery concepts, methods, and applications

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