Tags: Access and Affordability
Dr. Christopher Brooks, Dr. Kevyn Collins-Thompson, Dr. Daniel Romero and Dr. V.G. Vinod Vydiswaran collaboratively developed the Applied Data Science with Python Specialization to enable learners with a basic understanding of programming to effectively manipulate and gain insight into data. The Specialization delves into data science methods, techniques and skills within the Python domain, specifically focusing on the application of statistical analysis, machine learning, information visualization, text analysis and social network analysis. Additionally, the series of MOOCs covers a range of techniques that can be leveraged to gain insight into problems while building a portfolio through the analysis, design and development phases of data science. Learners engaging in this Specialization will gain hands-on experience with Python data science libraries for data analysis, including applied data mining such as clustering and classification, developing best practices for creating basic visualizations and charts, exploring how text documents be manipulated and classified and building network models to identify the relationships within social networks. The Specialization also serves as a resource for undergraduate students interested in exploring the U-M Masters program in Information Analysis and Retrieval while also providing residential and global learners with supplemental learning content and opportunities, from which they may develop a technical background in data science using Python programming.