Introduction to Machine Learning and AI with Python

Course Description

This course is designed to help you learn, understand, and practice big data analytics and machine learning approaches, which includes the study of modern computing big data technologies and scaling up machine learning techniques focusing on industry applications. We will learn about the functionality of the algorithm and theory without relying on complex math. In this way, you will master the fundamental theories in machine learning through theoretical study, understanding the latest developments, and learning to design algorithms for specific problems in their respective disciplines.

By the end of this class, you will:
• Understand basic AI concepts;
• Understand the applications and implications of data science in various disciplines;
• Use the essential machine learning techniques;
• Understanding machine learning algorithms without the knowledge of university-level math;
• Deploy appropriate algorithms for specific scientific research problems; and
• Have formulated a plan for starting a college career in data science.

Our classroom is a studio class, where sessions will involve a series of activities interwoven within lectures. In some instances, we will adopt a flipped-classroom approach where prior to the face-to-face session, you will gain exposure to new concepts and material by watching lecture videos, doing guided readings, and/or completing the required activities online. During class, we will do active work that calls for the analysis and/or application of the concepts and material learned prior to class. There will be classroom discussions, dialogues, and exercises led by the instructor. You are expected to actively participate in these discussions and to work on the particular exercises that allow you and your peers to learn by doing, to learn by observing the results of others, and to learn from one another while trying out new ideas. You will also learn through computer programming, by interacting with your professor and other students, and through the professor’s instruction and external media.


Math through algebra or pre-calculus would be very helpful. This course recommends a laptop for course-related programming, games/simulations, etc. Please note that some devices (e.g., Chromebooks) do not allow software downloads onto a desktop and so will not accommodate the specific needs of this course. If you have questions about this requirement please reach out to [email protected]


One Section Available to Choose From:

Online sections of Pre-College courses are offered in one of the following modalities: Asynchronous, Mostly asynchronous, or Blended. Please review full information regarding the experience here.

Dates: July 18, 2022 - August 05, 2022
Duration: 3 Weeks
Meeting Times: M-F 8:30A-11:20A
Status: Closed
Format: On-Campus
Instructor(s): Xiuquan Wang
Course Number: 10379