The Data Science Salon
The Data Science Salon
A Collaborative Learning Experience
About the Book
Data science has taken the world by storm. In a recent survey by Glassdoor, Data Scientist was named the best job in America. But what is the job of the data scientist? Data science is a process by which we state a question, gather and explore relevant data, conduct formal modeling, interpret results, and communicate findings. There is an art to this process that requires experience and collaboration to master.
The goal of the Data Science Salon is to provide a guided path to learning the conceptual and analytical skills needed to be an effective data scientist. We formulate this path as a group activity that can be done in small chunks on a regular basis. The primary objective is for your salon team to apply the Art of Data Science framework to a data science question of your choice and produce a report or summary of the analysis. After working through your own data science question using the TAODS framework, you will be well equipped to embark on additional data analysis projects of even greater complexity. Unlike didactic coursework with short answer questions and data analysis courses where you analyze the instructor’s sample data, in your Salon, you will be provided a structure to support your team’s analysis of its own data science question. This learning format is especially well suited to those who have had some traditional coursework and are poised to make the leap to applying technical skills to a real world data science question.
The Data Science Salon series is composed of weekly sessions, which can be completed at any pace. The book provides summaries of what activities should be conducted each week and presents questions that should be answered by the end of each session. The objective of the Salon is for your group to meet regularly to work out different aspects of your data science problem. Each session will be supported by reading materials from the Art of Data Science, lecture videos from the authors, and additional reading material specifically supporting each session.
- Before You Begin
- Organizing the Team
- Brainstorming Ideas
- Publicly Available Data
- Related Links:
- About the Authors
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