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Course Description

Snapshot of AI for STEM Learners 1 Hour Course Description & Objectives:

  •  This course is asynchronous, meaning you can sign up any time throughout the year.
  •  This course provides the framework for identifying and applying AI systems for real world applications. By the end of the course, you will have a basic understanding of all the components of an AI system.
    •  By the end of this course, students will be able to:
      •  Identify different types of learning in Machine Learning.
      •  Identify different types of intelligence in Artificial Intelligence.
      •  Identify different components of an AI system.

Survey of AI for STEM Learners 4 Hour Course Description & Objectives:

  •  This course is asynchronous, meaning you can sign up any time throughout the year.
  •  Upon completion 0.4 CEUs are awarded.
  •  This course will equip you with the basic knowledge and skills to reason with and develop Artificial Intelligence systems.
    •  By the end of this course, students will be able to:
      •  Apply different types of data encoding techniques.
      •  Explain different types of feature selection.
      •  Explain the role of the curse of dimensionality in machine learning.
      •  Create and maintain Python virtual environment.
      •  Explain different strategies of experimentation.
      •  List the steps for carrying Machine Learning experiments.
      •  Understand and utilize resampling methods for cross-validation.
      •  Identify strategies to avoid overfitting.
      •  Select appropriate evaluation metrics.
      •  Write code with the scikit-learn library for Python.

Notes

A badge or certificate is not awarded for the 1 hour course. 
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Enroll Now - Select a section to enroll in
Section Title
Snapshot of AI for STEM Learners- 1 hour
Type
self-paced
Dates
Start Now, you have 60 days to complete this course once enrolled.
Course Fee(s)
1 hour non-credit $0.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
Description & Objectives
  •  This course is asynchronous, meaning you can sign up any time throughout the year.
  •  This course provides the framework for identifying and applying AI systems for real world applications. By the end of the course, you will have a basic understanding of all the components of an AI system.
    •  By the end of this course, students will be able to:
      •  Identify different types of learning in Machine Learning.
      •  Identify different types of intelligence in Artificial Intelligence.
      •  Identify different components of an AI system.
Section Title
Survey of AI for STEM Learners- 4 hour
Type
self-paced
Dates
Start Now, you have 60 days to complete this course once enrolled.
Course Fee(s)
Registration fee non-credit $149.00
Drop Request Deadline
TBD
Transfer Request Deadline
TBD
Section Notes
Description & Objectives
  •  This course is asynchronous, meaning you can sign up any time throughout the year.
  •  This course will equip you with the basic knowledge and skills to reason with and develop Artificial Intelligence systems.
    •  By the end of this course, students will be able to:
      •  Apply different types of data encoding techniques.
      •  Explain different types of feature selection.
      •  Explain the role of the curse of dimensionality in machine learning.
      •  Create and maintain Python virtual environment.
      •  Explain different strategies of experimentation.
      •  List the steps for carrying Machine Learning experiments.
      •  Understand and utilize resampling methods for cross-validation.
      •  Identify strategies to avoid overfitting.
      •  Select appropriate evaluation metrics.
      •  Write code with the scikit-learn library for Python.
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