EdX

Data Science: Productivity Tools (edX)

Data Science: Productivity Tools (edX)

Keep your projects organized and produce reproducible reports using GitHub, git, Unix/Linux, and RStudio. A typical data analysis project may involve several parts, each including several data files and different scripts with code. Keeping all this organized can be challenging.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

Part of our Data Science Professional Certificate, this course explains how to use Unix/Linux as a tool for managing files and directories on your computer and how to keep the file system organized. You will be introduced to the version control systems git, a powerful tool for keeping track of changes in your scripts and reports. We also introduce you to GitHub and demonstrate how you can use this service to keep your work in a repository that facilitates collaborations.
Finally, you will learn to write reports in R markdown which permits you to incorporate text and code into a document. We'll put it all together using the powerful integrated desktop environment RStudio.

What you'll learn

  • How to use Unix/Linux to manage your file system
  • How to perform version control with git
  • How to start a repository on GitHub
  • How to leverage the many useful features provided by RStudio
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Data Science and Machine Learning Capstone Project (edX) EdX
IBM

Data Science and Machine Learning Capstone Project (edX)

Create a project that you can use to showcase your Data Science skills to prospective employers. Apply various data science and machine learning techniques to analyze and visualize a data set involving a real life business scenario and build a predictive model. Now that you've taken several courses on data science and machine learning, it’s time to put your learning to work on a data problem involving a real life scenario. Employers really care about how well you can apply your knowledge and skills to solve real world problems, and the work you do in this capstone project will make you stand out in the job market.

Self Paced
Self-Paced
Data Science: Inference and Modeling (edX) EdX
HarvardX,Harvard University

Data Science: Inference and Modeling (edX)

Learn inference and modeling, two of the most widely used statistical tools in data analysis. Statistical inference and modeling are indispensable for analyzing data affected by chance, and thus essential for data scientists. In this course, you will learn these key concepts through a motivating case study on election forecasting.

Self Paced
Self-Paced
Irrigation Efficiency: more food with less water (edX) EdX
KU Leuven University,KULeuvenX

Irrigation Efficiency: more food with less water (edX)

Learn to improve the efficiency of different irrigation system components over varying scales in order to extract less water from our resources while producing more food. How can we meet the demands of our ever hungrier and thirstier world? Irrigation water uses 70% of the fresh water extraction worldwide to produce 40% of the food.

Self Paced
Self-Paced
Programming for Data Science (edX) EdX
University of Adelaide,AdelaideX

Programming for Data Science (edX)

Learn how to apply fundamental programming concepts, computational thinking and data analysis techniques to solve real-world data science problems. There is a rising demand for people with the skills to work with Big Data sets and this course can start you on your journey through our Big Data MicroMasters program towards a recognised credential in this highly competitive area. Using practical activities you will learn how digital technologies work and will develop your coding skills through engaging and collaborative assignments.

Self Paced
Self-Paced
Analyzing and Visualizing Data with Power BI (edX) EdX
Davidson College,DavidsonX

Analyzing and Visualizing Data with Power BI (edX)

Step up your analytics game and learn one of the most in-demand job skills in the United States. Power BI is a robust business analytics and visualization tool from Microsoft that helps data professionals bring their data to life and tell more meaningful stores. This four-week course is a beginner's guide to working with data in Power BI and is perfect for professionals. You'll become confident in working with data, creating data visualizations, and preparing reports and dashboards.

Self Paced
Self-Paced
Data Science Tools (edX) EdX
IBM

Data Science Tools (edX)

Learn about the most popular data science tools, including how to use them and what their features are. In this course, you'll learn about Data Science tools like Jupyter Notebooks, RStudio IDE, and Watson Studio. You will learn what each tool is used for, what programming languages they can execute, their features and limitations and how data scientists use these tools today.

Self Paced
Self-Paced
Case Studies in Functional Genomics (edX) EdX
HarvardX,Harvard University

Case Studies in Functional Genomics (edX)

Perform RNA-Seq, ChIP-Seq, and DNA methylation data analyses, using open source software, including R and Bioconductor. We will explain how to perform the standard processing and normalization steps, starting with raw data, to get to the point where one can investigate relevant biological questions.

Self Paced
Self-Paced
Data Processing and Analysis with Excel (edX) EdX
Rochester Institute of Technology,RITx

Data Processing and Analysis with Excel (edX)

Learn to use Excel to organize and clean data so it can be manipulated and analyzed. In this course, you will learn how to organize your data within the Microsoft Office Excel software tool. Once organized, we will discuss data cleaning. You will learn how to identify outliers and anomalies in the data, and how to identify and change data-types. Together we will develop a data analysis plan, after which we will apply analysis methods and tools, including exploratory analysis, evaluation of results, and comparison with other findings.

Self Paced
Self-Paced
Statistics and R (edX) EdX
HarvardX,Harvard University

Statistics and R (edX)

An introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences. We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation.

Self Paced
Self-Paced
Fundamentals of TinyML (edX) EdX
HarvardX,Harvard University

Fundamentals of TinyML (edX)

Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML. What do you know about TinyML? Tiny Machine Learning (TinyML) is one of the fastest-growing areas of Deep Learning and is rapidly becoming more accessible. This course provides a foundation for you to understand this emerging field.

Self Paced
Self-Paced
Data Science: Wrangling (edX) EdX
HarvardX,Harvard University

Data Science: Wrangling (edX)

Learn to process and convert raw data into formats needed for analysis. In this course, we cover several standard steps of the data wrangling process like importing data into R, tidying data, string processing, HTML parsing, working with dates and times, and text mining. Rarely are all these wrangling steps necessary in a single analysis, but a data scientist will likely face them all at some point.

Self Paced
Self-Paced