We teach data science as a collaborative lifecycle, where data and processes have provenance from the raw data stage through to the resulting business intelligence products. A data lifecycle starting with data curation, exploratory data analysis, statistical and machine learning modeling and refinements, and decision product production is used to tell the story of the data.
Two key philosophies drive this:
1 Data scientists must be able to tell the story of data, including walking stakeholders backward from the final product, all the way to the beginning of the source data; including discussing the implications of all assumptions and transformations and decisions made along the way.
2 Data scientists will be working increasingly in interdisciplinary teams, potentially distributed, where collaboration of ideas and exploration and processes are essential. Version control systems are central within our curriculum, with students using Git to fetch new modules and submit their completed work.
Classes are uniformly designed from the ground up with a consistent weekly schedule and pace, allowing working professionals to successfully manage their work-life-education commitments. Numerous students within this class have already begun transitioning to more analytical work-roles.
Mizzou’s Data Science & Analytics MS multi-disciplinary program focuses on the concentration areas best fitting your company and career.Geospatial Biotechnology High Performance Computing Human-Centered Design for Data Data Journalism & Strategic Communication
One of the key targets of our training is to develop the students’ soft skills as it relates to data science and communication. To facilitate this, we use a cohort-based program that develops the students’ sense of community and collaborative group dynamics.
The diverse student backgrounds enable some lively discussions and numerous perspectives based on prior experiences and the diverse industry background. We strive to enhance student learning of technology in cooperative, team oriented settings.
Students are routinely (weekly) tasked to perform cooperative communication with fellow students to help them develop their communication and collaboration skills around the technical coursework and subject matter.
“The biggest and most important thing that I have learned is how to clean up data…how to figure out what is most important and how to tell that story with great visualization.”
DSA Class of ’18