By the end of the course, students will be able to: Gain experience with tools used to develop and publish a web site. Create boilerplates for a website Gain experience programming in D3 Create a web-based visualization using a dataset

This weekend-long experience is designed to have you implement the concepts, methods, and strategies learned thus far in the program. You will network with industry professionals collaborate with your cohort and faculty experiment with technologies and applications in workshop settings to create visualizations listen to experts and gain insight into design trends and strategies + Two elective sessions will be offered across all three MPS residencies to enable you to meet, learn from, and network with peers in UX Design and Business of Art and Design sections

Your final prototypes will be virtually shared with your faculty, a panel of professionals in the field, and your cohort, and you will receive feedback based on criteria and guidelines provided. During this time, you may also share your portfolio to showcase the projects, assignments, and reflections you developed over the past 15 months that demonstrate your expertise in the field of data analytics and visualization.

To ensure student success in the program, the orientation supports the navigation of MICA’s administrative tools and academic services, the development of greater competencies around data and design, and community building with faculty and the cohort of students. The exploration of foundation concepts such as design thinking, digital/information literacy, data/design approaches, data presentation, and digital tools for data visualization will take place through independent and collaborative activities, and students will work through the orientation with the end in mind as they consider their career paths and the types of portfolios they want to create. Orientation is a required activity. The content and assignments designed for orientation are introductions to courses that follow.

Data analytics is the science of making meaning out of raw data. But how is this done, and what does visualization have to do with it? 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, art/design 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 in visual formats.

Course Description: This course is designed to prepare incoming Data Analytics and Visualization students to begin their online MPS program at MICA. The course includes information on the program, technology and tools used within the program, Canvas training, MICA policies, and information on all student resources. There are also details on the Virtual Orientation held during the first week of classes.

This course teaches students not only how to create impactful information visualizations, but why they work. Students will be introduced to good practices in organizing space, using type, and using color based on well-established guidance such as Gestalt Laws, universal principles of design, and principles of perception and cognition. Students will also be introduced to ethical issues in data visualization, issues regarding accessibility, and how to practice inclusive design.

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.

You will use your working knowledge of statistical concepts and learn key concepts that help tell a well-designed visual story. Topics of the course include art and design theories, methods, and applications such as design thinking, color theory, graphic design, constructive critique, and prototyping. In this course, you will investigate and apply ideas while learning how to use a leading design tool.

Raw data is messy, and the goal of this course is to increase your competencies around how to capture, curate, manipulate, and analyze raw data as part of a visualization process. Here, you will learn about commonly utilized statistics concepts such as: descriptive and inferential statistics, probability, histograms, statistical measures, sampling, distributions, correlation, regression, and fitting to data sets. You will become familiar with the shortcomings and challenges of data, and you will use industry-leading visualization applications to help you think about and model data sets. By the end of this course, you will be prepared to design with data in an intentional way, and you will have the foundation needed for the more advanced Statistics & Analysis course to follow.

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.

You create what you think is the perfect data visualization project, but how do others see and understand it? After this course, you will better understand perception theories in the arts and sciences and methods by which information is visually acquired and processed. You will gain an understanding of how the brain receives, acquires, processes, and stores information and data through cognitive neuropsychology. This, combined with design strategies such as patterning, spatial relationships, shape, and color, will support your growth as a data visualization expert.

This course focuses on historical, cultural, social, economic, and political contexts of visualizations and information access. In addition to perspectives and research from the fields of art history, art theory, and studies of visual culture, students explore how visualization has been and is currently being used by a variety of industries to tell compelling narratives in visual formats.

A deep dive into topics such as data mining, data aggregation, grouping methods, data cleaning, and evaluation will take place in this course. You will use applications for statistical computing and perform tasks such as calculating and describing statistical summaries of the data. Additionally, you will examine relationships between data elements. By the end of this course, you will begin to transform data analysis into visualizations.

The course provides an overview of probability and statistics concepts commonly used in the visualization process. Students learn how to apply concepts such as statistical measures, correlation, regression, and fitting to data sets. Students continue to use and gain proficiency in tools and softwares introduced in Statistics and Analysis I, and explore additional methods for data analysis.

The exploration of analytical reasoning using tools and techniques such as mind maps, storyboards, wireframing, tree maps, and prototyping is the focus of this course. As a way to advance your work, you will study topics such as information architecture, human reasoning, networking, mapping, and user-centered designs to create cohesive and compelling stories.

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 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

Information-design case study analyses and critiques will provide you with opportunities in this course to identify the following key elements related to presenting information: design theory, aesthetics, visual rhetoric, and visual interface design. Through your synthesized knowledge of methods and applications related to the design and presentation of information and data, you will move forward in this program with a plan for the development and creation of your own data visualization projects.

As the program nears its end, we take this opportunity to think critically about professional practices in the Data Analytics & Visualization field. The project decision-making process, ethical uses of data and visualizations, project management, budget and risk management, user interface design, and testing are topics of inquiry. Learners will explore the use of visualization applications to help execute business strategy and support communication with a wide variety of stakeholders.

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.

You will tie together the theories, methodologies, and skills you have acquired throughout the program to work from concept to fully-realized prototype. You will use research and materials developed over the course of the program, and you will collaborate with a faculty advisor and your cohort for critique and guidance during the project development. Finally, you will consider the most effective ways to present this work during the final virtual capstone presentation weekend that concludes the program.

During Capstone I students tie together the theories, methodologies, and skills you have acquired throughout the program to work from concept to a fully-realized prototype, which will be presented in Capstone II. Students will develop project management skills as they apply research and user-testing, and utilize skills developed over the course of the program to carry out their capstone projects. Students will collaborate with a faculty advisor and peers for critique and guidance during the project development.

Students will continue to develop the work they started in Capstone I, as they work toward the final prototype of their capstone project. They will also create a written narrative to accompany their visualizations and finally, students will consider the most effective ways to present this work during the final virtual capstone presentation, which concludes the program.