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 on MICA’s campus 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, and experiment with technologies and applications in workshop settings to create visualizations. Additionally, you will be encouraged to explore the city of Baltimore to learn about its rich history, entrepreneurial culture, and its future as an East Coast tech hub.

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.

Information and Data Visualization Orientation

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.

You now know how to produce data reports. But can you tell a compelling visual narrative with the information? This course will help you answer this question as you 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. Additionally, methods such as editing, iterative process, feedback and evaluation will be used to refine information and data to strengthen and clarify a visual story.

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 Residency 3 student presentations. For the Residency 3 presentation, students must describe their project process, including concept development, research and development documentation, and design.

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.

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.

The Data & Statistics Bootcamp provided the foundation to this course in which you will dive more deeply into topics such as data mining, data aggregation, grouping methods, data cleaning, and evaluation. You will use applications for statistical computing and perform tasks such as calculating and describing statistical summaries of the data, as well as examining relationships between data elements. By the end of this course, you will begin the transformation of data analysis into visualizations.

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.

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.

You will tie together the theories, methodologies, and skills you have acquired throughout the program to work from concept to a 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.