Description: Students play with an AI that can react to their movement, and choreograph something that uses this tool. They can show off their choreography to the rest of the class
Skills/knowledge you'll gain: Movement, collaboration
Length: 1-4 hours

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards

Description: AI can create realistic-looking images and videos that were never actually filmed or taken as a photo. These images and videos are called deepfakes. This is a quick lesson requiring no background where students learn about deepfakes, as well as ways to verify information that they see
Skills/knowledge you'll gain: Critical thinking
Length: 1 hour

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards

Description: A quick and fun way to become familiar with some core ideas of modern AI while playing with Google Quick, Draw
Skills/knowledge you'll gain: Understanding of what AI is, privacy and bias concerns
Length: 1 hour

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards

Description: Learn how conservationists use AI image recognition to save time identifying how and where to protect endangered species. Build your own species-identifying AI system
Skills/knowledge you'll gain: Conservation
Length: 1-2 hours

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards

Second course in a two-course sequence. Introduces and applies technical skills around beginning and managing a small business, including spreadsheets and the use of charts and graphs. Includes reflection and discussion of the application of concepts to a real-world example. Requires teamwork and collaboration to be exercised in completing a group project. Covers application of financial, legal, and administrative procedures in running a business.
Upon successful completion of this course, students will be able to:
Represent business models in spreadsheets including preparation of charts and graphs. Apply key business activities and the primary concepts and terms associated with these activities. Manage a business interacting with the external environment (through a simulation) and describe how this interaction impacts both business and the external environment. Implement the financial, legal, and administrative procedures involved in starting new business ventures. Identify ethical issues facing businesses. Effectively collaborate with team members and communicate professionally.

A short course for students to increase their proficiency in analyzing and interpreting data visualizations. By completing this short course students will be able to explain the importance of data literacy, identify data visualization issues in order to improve their own skills in data story-telling. The intended outcome of this course is to help students become more discerning and critical users of data, graphs, charts and infographics.

Are you ready to leave the sandbox and go for the real deal? Have you followed Data Analysis: Take It to the MAX() and Data Analysis: Visualization and Dashboard Design and are ready to carry out more robust data analysis?

In this project-based course you will engage in a real data analysis project that simulates the complexity and challenges of data analysts at work. Testing, data wrangling, Pivot Tables, sparklines? Now that you have mastered them you are ready to apply them all and carry out an independent data analysis.

For your project, you will pick one raw dataset out of several options, which you will turn into a dashboard. You will begin with a business question that is related to the dataset that you choose. The datasets will touch upon different business domains, such as revenue management, call-center management, investment, etc.

The Data Notebook is an online suite of open interactive resources that provides instructional materials for introductory data analytics and data visualization approaches relevant to a wide range of subjects and disciplines. Specifically, this book focuses on principles related to data storytelling, and provides tangible research steps and include case studies, mini-lessons, and interactive instructional components.

Data talks are short 5-10 minute classroom discussions to help students develop data literacy. This pedagogical strategy is similar in structure to a number talk, but instead of numbers students are shown a data visual and asked what interests them

A LibGuide that covers topics related to Data Visualization, including planning visualizations, tools and resources, assessment, and accessibility

Data Viz Project started out as an internal tool box, where we simply stuck data visualizations up on our wall as visual inspiration. Of course, there are a lot of books, websites, libraries, and tools that include a lot of visualization types, but not as comprehensive and logical as we liked. So instead of continuing to stick these visualizations on our wall, we thought we might as well just put it online, so you and others can use it as a tool and inspiration.

Background: How Neural Networks Work
Pairs with: AI & The Environment, AI & Dance, AI & Facial Recognition
Length: 2-4 hours

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards

Description: GANs are often used when machines create new images or video content. This lesson explores how each work
Pairs with: AI & Deepfakes
Length: 2-4 hours

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards

Description: An introductory hands-on deep dive into the technical details about how machines hold the information that they’ve learned. In the end, students will teach others what they have learned
Pairs with: Everything
Length: 2-4 hours

Curriculum aligns to:
- NGSS Engineering standards
- ISTE standards
- Common Core ELA/Literacy standards
- Also maps to CSTA standards

Social data analysis enables you, as a researcher, to organize the facts you collect during your research. Your data may have come from a questionnaire survey, a set of interviews, or observations. They may be data that have been made available to you from some organization, national or international agency or other researchers. Whatever their source, social data can be daunting to put together in a way that makes sense to you and others.

When we come across a graph, a chart, or an infographic, how do we know if it is telling the truth? Often, numbers and data convey an authority that is hard to dispute, especially when they are arranged visually in a compelling way. Yet, data, in the ways it is gathered and shared, can be misrepresented and portray a slanted reality rather than a more accurate depiction.

This workshop introduces the concept of data literacy, or the ability to comprehend and interpret data, as a method of cultivating a critical mindset towards representations of information. Participants will learn how to discern misleading data visualizations and collaborate with others in developing strategies for analyzing data that is more accurate and useful. All consumers of information, especially undergraduate students, are encouraged to attend.

By the end of this workshop, participants will be able to:

* Understand what data is and how it is used for rhetorical, commercial, and political purposes

* Identify errors and discrepancies in how data is produced and represented

* Engage with data visualizations in multiple contexts with a healthy degree of skepticism

* Communicate their interpretations of data with their peers