Artificial Intelligence

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Fundamentals of AI for STEM Learners

The Fundamentals of AI for STEM Learners package is made up of the three courses listed below. Click the register button to sign up for the 1-hour, 4-hour or 15-hour course.

If you’re interested in learning more about how to receive a micro-credential, click here.

This 15-hour course OR the 15-hour Fundamentals of AI course is required to micro-credential in AI

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Foundation

Fundamentals of AI for STEM Learners

There Are 3 Courses Available in This Package

1-hr
Course

Snapshot of AI for STEM Learners

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FREE Asynchronous

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.

4-hr
Course

Survey of AI for STEM Learners

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249 Asynchronous Course Completion Certificate 0.4 CEUs

This course is asynchronous, meaning you can sign up any time throughout the year.

Artificial intelligence (AI) is used to solve problems in research and industry. This course provides students with an introduction to the concepts and tools used to build and using AI systems. Students will obtain the skills and knowledge they need to understand how AI is used to solve real-world agricultural and life sciences problems.

After successfully completing this course, you will earn .4 CEU as well as a certificate of completion.

By the end of this course, students will be able to:

Use Google Colaboratory (Google Colab) and Jupyter Notebooks to build and train neural networks.

Demonstrate a basic understanding of modern AI and the history of AI development, using correct vocabulary to describe the characteristics of neural networks.

Implement neural networks in TensorFlow.

Identify important applications of phenotype prediction in agricultural and life sciences.

15-hr
Course

Fundamentals of AI for STEM Learners

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1095 HybridBadge Qualify for Micro-Credential 1.5 CEUs

This course is hybrid, meaning it will include a mixture of online work and live webinars.

This 15hr course OR the 15hr Fundamentals of AI course is required to micro-credential in AI

This is a 15-hour hybrid course. Learners will meet synchronously via Zoom and will have asynchronous activities. Learners will have eight weeks upon registration to complete the five modules which will require the students to complete at least three hours of work each week. At the end of the course, students will earn a badge for course completion. Learners will earn 1.5 continuing education units (CEUs).

By the end of this course, students will be able to:

Describe Statistical and Neural algorithms for AI, including

Multi-layer Perceptrons (MLPs)

Dimensionality Reduction

Support Vector Machines (SVMs)

Random Forests

Gibbs Samplers

Topic Models

Convolutional Neural Networks (CNNs)

Recursive Neural Networks (RNNs)

Autoencoders

Generative Adversarial Networks

Use Jupyter Notebook implementations of Statistical and Neural algorithms

Meet The Instructors

Instructor Headshot

Catia Silva, Ph.D.

1-hr, 4-hr and 15-hr Instructor
Instructor Headshot

Paul Gader, Ph.D.

15-hr Instructor

SHOWCASE MASTERY WITH A MICRO-CREDENTIAL.