To get started, click the course card that interests you and enroll. (source: Glassdoor) Companies are leveraging the power of data analysis to drive innovation. After that, we don’t give refunds, but you can cancel your subscription at any time. These courses and Specializations have been hand-picked by the learning team at Coursera, Popular Categories on Coursera: Business | Computer Science | Data Science | Information Technology | Health | Career Success | See All, Popular Degrees on Coursera: Business | Computer Science | Data Science | Health | Bachelor’s Degrees | See All. Happy Learning All notes are written in R Markdown format and encompass all concepts covered in the Data Science Specialization, as well as additional examples and materials I compiled from lecture, my own exploration, StackOverflow, and Khan Academy.. Use GitHub to manage data science projects. Find Service Provider. Data Science Specialization | John Hopkins Coursera. 2. Accelerated Computer Science Fundamentals Specialization This project-based course focuses on the more advanced material in the Computer Science specialization, covering topics such as programming in C++, data structures, algorithms, and object-oriented software. Learners who complete this specialization will be prepared to take the Data Science: Statistics and Machine Learning specialization, in which they build a data product using real-world data. See what Reddit thinks about this specialization and how it stacks up against other Coursera offerings. You’ll have a foundational understanding of the field and be prepared to continue studying data science. Data Science: Foundations using R Specialization by Johns Hopkins (Coursera) This foundational Data Science program is offered by Johns Hopkins University and is taught by 3 eminent professors Jeff Leek, Roger D Peng and Brian Caffo of the Johns Hopkins Bloomberg School of Public Health. This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. In taking the Data Science: Foundations using R Specialization, learners will complete a project at the ending of each course in this specialization. 1138 reviews, Rated 4.6 out of five stars. Author: Michael Galarnyk . This Specialization is intended for data scientists with some familiarity with the R programming language who are seeking to do data science using the Tidyverse family of packages. Try the full learning experience for most courses free for 7 days. Introduction to Data Science Specialization. #15 in Best of Coursera: Reddsera has aggregated all Reddit submissions and comments that mention Coursera's "Data Science" specialization from Johns Hopkins University. Certificate Data Science Capstone . This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. set.seed(1) rpois(5, 2) Answer. Question 1. They are by no means perfect, but feel free to follow, fork and/or contribute.Please reach out to [email protected] if you have any questions. Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online. Tidy data dramatically speed downstream data analysis tasks. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data. 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