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Course

AI Academy - Level 1

CSE-902.23

AI Academy Level 1 is a multi-module course that prepares students for further study or work in Natural Language Processing through the use of Machine Learning, Data Science and Artificial Intelligence technologies. 

To work effectively in this field, the Machine Learning Engineer and Data Scientist must be fluent in the requisite mathematics and programming topics, and this course provides a focused introduction to both, as well as offering options to analyze AI ethics and the fundamentals of data science. After enrollment, students complete one module and may enroll in the course in subsequent academic terms to complete additional subject modules.

Course may be repeated for credit.

What you'll learn

Module Options

  • Python and Mathematics for Machine Learning
    • This course will provide a general working knowledge of the math concepts and Python programming skills needed to implement and analyze standard and advanced Machine Learning algorithms.
  • Machine Learning Algorithms
    • Students completing this course will have a general working knowledge of standard Machine Learning algorithms used in supervised and unsupervised learning models.
  • AI Ethics
    • AI Ethics provides high school students with an introduction to the ethical considerations, societal impacts, and responsible development practices for working with artificial intelligence systems. The curriculum covers fundamental topics including bias and fairness, privacy and security, and transparency. Using Python, students implement ethical analysis techniques, explore fairness-performance tradeoffs, and learn to apply privacy-preserving techniques like differential privacy.
  • Data Science Fundamentals
    • Data Science Fundamentals provides students with the skills to develop end-to-end data pipelines used in AI and Machine Learning. Students collect real-world data via web scraping and live APIs, preprocess it using Pandas, store and query it in SQLite, and analyze it through Exploratory Data Analysis (EDA). Each unit includes a hands-on coding project that culminates in a capstone connecting data acquisition to machine learning, and preparing students for more advanced Machine Learning courses.

Course Information

3.00 units
$500.00
Notes: This course is not A-G approved.

Get more information

Course sessions

Closed

Section ID:

EL00010410

Class type:

Not Applicable

Textbooks:

For students choosing one of these modules: - Python and Mathematics for Machine Learning - Machine Learning Algorithms The following textbook is required: Python and Math Essentials for Machine Learning - a Beginner’s Guide 1st by Mauro, Anthony ISBN / ASIN: 9798350948486

Policies:

Schedule:

No information available at this time.
Closed