MTDA Program

Information Design [GRADTDA 5505] (3 CREDIT HOURS): Explores relationship between data visualization and design. Presents programming skills and design strategies to structure and visualize information to create effective communications and stimulate viewer attention and engagement. 

Syllabus : http://go.osu.edu/gradtda5505  

Design Thinking and Data in Practice [GRADTDA 5627] (1 CREDIT HOUR): This course will explore the design thinking process as it relates to research methods, data collection, and data analysis. The Design Thinking methodology re-frames problems in human-centric ways. We will learn from professionals who utilize design thinking paired with a creative mindset to gather and apply data to solve big problems.”

	Rebekah Matheny   Associate Professor	Yvette Shen   Assistant Professor

Big Data Computing Foundations 1 [GRADTDA 5621] (3 CREDIT HOURS):  This class teaches students how to construct schemas that locate, scrape, process and clean data to develop practical workflows which extract useful information and create usable representations. Focuses on the use of Python and Javascript, as well as tools such as Hadoop and Scala. Current instructor: Brad Coy

Big Data Computing Foundations 2 [GRADTDA 5622] (3 CREDIT HOURS): Part II of a two semester sequence. This class focuses on creating scalable data organizations and access to high-performance computing workflows for Big Data. Cloud computing, data organization, data warehousing, and basic and advanced data structures are emphasized. 

Data Governance [GRADTDA 5625] (1 CREDIT HOUR): Trust in data assets is essential. This skills based seminar focuses on practical elements of good data governance, privacy and data security through the use of case studies. 

Practical Learning and Mining for Big Data [GRADTDA 5620] (3 CREDIT HOURS): Split into two modules focusing on (1) practical and scalable data mining and (2) scalable machine learning. You’ll learn how to build practical workflows to mine associations and patterns, classify data and build recommendation systems for data and questions. 

Greg Ryslik	Brad Coy		Tom Marlow	Mark Marshalek

Data Analytics Foundations 1 [GRADTDA 5401] (3 CREDIT HOURS):  This class is all about extracting useful information from data, using data to address work challenges, engaging in data-driven decision making under uncertainty, and identifying, sourcing, manipulating and interpreting data. Software and skills taught in this class include using R programming and analysis using R.

Data Analytics Foundations 2 [GRADTDA 5402] (3 CREDIT HOURS): Part II of a two semester sequence. This class layers in more advanced R programming and analysis using R. It teaches distribution theory via simulation, statistical modeling such as A/B testing, ANOVA, multiple linear regressions, logistic regression and multivariate analysis, while also emphasizing the communication of results. 

Research Design [GRADTDA 5626] (1 CREDIT HOUR): The second skills based seminar gives a general overview of research methods which are common across disciplines. Topics include formulating research questions to conducting specific analytical methodologies and writing up/presenting results. 

Practical Learning and Mining for Big Data [GRADTDA 5620] (3 CREDIT HOURS): Split into two modules focusing on (1) practical and scalable data mining and (2) scalable machine learning. You’ll learn how to build practical workflows to mine associations and patterns, classify data and build recommendation systems for data and questions.

Elly Kaizar	Thomas Metzger   Assistant Professor	R. Scott Linder

Capstone I [GRADTDA 5911] (3 CREDIT HOURS): Experiential training for students in data analysis with design thinking on non-trivial data. Students formulate data questions and create complete workflows. Emphasis on teamwork, translational competency and professional competency in data rich environments by deploying and using computing technology, data analysis methods and creation of user interfaces. 

Capstone II [GRADTDA 5912] (3 CREDIT HOURS): Part II of two semester sequence. Culminating experience through direct engagement with community partners who will formulate challenge questions and provide data. Emphasis on teamwork, translational competency with added emphasis on processing of large data and interpretation of domain specific results. Illustrates data storytelling through deployment of scalable computing technology, data analysis and user interfaces.

Interactive Arts Media [GRADTDA 5141] (3 CREDIT HOURS): Practice in methods to design and craft user experiences and user interfaces for applications that provide cohesive, satisfying experiences for users. Contemporary methods and software to produce application prototypes. Cohort identification and user testing and research. 

Emerging Trends in Data Visualization [GRADTDA 5150] (3 CREDIT HOURS): This course enables students to explore new and emerging visualization approaches, topics and trends in visualization research and their applications.  Students will research, write about, create, and experience visualization trends.

Jeremy Patterson   Graphic Designer	Joshua McClurg-Genevese                    Lecturer