The virtual industry immersive occurs at the midpoint of the program and enables you to collaborate with your cohort and network with each other as well as industry professionals. It consists of a mix of workshops, keynotes, and hands-on activities. This two-day experience surveys concepts, tools, and techniques that promote innovation. Students engage in exercises designed to apply and test creative techniques. At the conclusion of the virtual industry immersive, students will have knowledge of and practice with a number of approaches that can be applied through the second half of the program and into their careers.

We live in a world surrounded by ever-increasing amounts of information in the form of data. Converting this raw data into a visual form that communicates effectively involves data analytics and information visualization. To use data to communicate effectively requires advanced information and visualization literacy. By the end of this course, you will have working knowledge of historical, cultural, social, economic, political, and ethical contexts of data analytics and visualizations. You will explore perspectives and research from the fields of art/design history, theory, and visual culture. Additionally, you will study the way visualization has been used historically, and is currently being used, in a variety of industries to tell compelling narratives.

To ensure your success in the program, students will meet virtually for a 1-day orientation where they will meet administrative staff, learn more about student services and success initiatives, and engage in community building with their cohort. In addition, students will complete an asynchronous orientation course in Canvas as a means to introduce them to the navigation of MICA’s administrative tools as well as inform them of academic services available through MICA. The content and assignments in the orientation course are designed to be an introduction to the program as well as a resource throughout the students' time at MICA.

This course will be focused on creating impactful data visualizations and understanding why they work. We’ll discuss the use of color, type, and organizing space based on well-established guidance such as Gestalt Laws, universal principles of design, and principles of perception and cognition. We’ll also look at ethical issues in data visualization regarding accessibility and practicing inclusive design. Lastly, we’ll explore how principles of narrative and storytelling can be used to create engaging visualizations.

Building upon Visual Storytelling I, in this course students learn about different forms of storytelling and the ways in which techniques such as sequence, relationship, context, and audience can be combined through analysis and design strategies to tell a powerful story. Students continue to engage in the design process and apply principles of human-centered design. Additionally, through critique, students learn to refine information, data, and their design to strengthen and clarify a visual story.

This course introduces students to methods for gathering, organizing, preparing, and analyzing information and data that are central to visualization. Topics will include data types, data gathering, data cleaning, preparation, organization and exploratory summarizations. Students will explore tools and applications that help establish and/or understand descriptive statistical relationships such as range, centrality, histograms, distributions with data and information and develop foundational skills needed to transform research into visualizations. R (https://www.r-project.org/) is a free, open-source language and environment for statistical computing and graphics. R has an incredibly rich set of capabilities, and this course will focus on loading data, performing basic statistical operations, and producing graphical outputs.

This course is the second in the sequence of Statistics and Analytics which are key concepts in Data Analytics and Visualization. This course will expand upon the concepts of data aggregation, grouping methods, data cleaning, and more complex methods of presentation. Students will explore tools and applications that help in transforming data into visualizations. Students are expected to have a basic working understanding of R (https://www.r-project.org/ ) which is a free, open-source language and environment for statistical computing and graphics. R has an incredibly rich set of capabilities, and this course will focus on loading data, performing basic statistical operations, and producing graphical outputs. The emphasis during the course will further the student's ability to use R, for more complex data manipulations and advanced visualizations. By using the functionality provided by the tool students will understand the entire pipeline of data processing and the connections between data processing concepts and their visual representations.

This Independent Study will cover the usual content for the corresponding regular curriculum course, excepting minor adaptations to fit the student’s personalized needs and interests, and will use the same learning outcomes

This course integrates all the various concepts explored throughout the program and engages MICA's industry partners to present students with challenges faced by professionals in the Data Analytics and Visualization industry. You will engage with the project decision-making process, ethical uses of data and visualizations, project management, budget and risk management, user interface design, and testing. Additionally, you will use visualization applications to help execute business strategy and support communication with a wide variety of stakeholders. Data Analytics and Visualization professionals provide you feedback, insight, encouragement, and critical analysis as you execute your projects. The goal of this course is to serve as a cornerstone of your portfolio showcasing end-to-end design thinking.

This course is designed for a preliminary exploration of the capstone project. Students integrate the theories, methodologies, and skills acquired throughout the program to work from concept to proposal, which will then be developed into a fully-realized prototype at the end of the Capstone course next term. Throughout this course, students will also engage with the project decision-making process, ethical uses of data and visualizations, and project management. In addition, students will collaborate with peers, faculty, advisors, and other industry professionals for critique and guidance during the project development through the presentation of the capstone project proposal.

In this intensive course, students prepare a final thesis project from concept to a fully-realized product, using research and materials developed over the course of the program. Students work with a faculty advisor who provides guidance and critique for projects as well as provides guidance for the student presentations. For the presentation, students must describe their project process, including concept development, research and development documentation, and design.