EdX

Data Science: Productivity Tools (edX)

Offered by HarvardX, Harvard University,
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

Observation Theory: Estimating the Unknown (edX) EdX
Delft University of Technology,DelftX

Observation Theory: Estimating the Unknown (edX)

Engineering Sci: Mathematics

Learn how to estimate parameters from observational data for real-world engineering applications and assess the quality of the results. Are you an engineer, scientist or technician? Are you dealing with measurements or big data, but are you unsure about how to proceed? This is the course that teaches you how to find the best estimates of the unknown parameters from noisy observations. You will also learn how to assess the quality of your results.

Self Paced
Self-Paced
Data Analysis Mathematical Models Observation Theory
Details
Big Data Capstone Project (edX) EdX
University of Adelaide,AdelaideX

Big Data Capstone Project (edX)

Statistics & Data Analysis Data Science

Further develop your knowledge of big data by applying the skills you have learned to a real-world data science project. This project will give you the opportunity to deepen your learning by giving you valuable experience in evaluating, selecting and applying relevant data science techniques, principles and theory to a data science problem. This project will see you plan and execute a reasonably substantial project and demonstrate autonomy, initiative and accountability.

Self Paced
Self-Paced
Big Data Data Science Data Analytics
Details
Data Science Ethics (edX) EdX
University of Michigan,MichiganX

Data Science Ethics (edX)

CS: Software Engineering Engineering

Learn how to think through the ethics surrounding privacy, data sharing, and algorithmic decision-making. As patients, we care about the privacy of our medical record; but as patients, we also wish to benefit from the analysis of data in medical records. As citizens, we want a fair trial before being punished for a crime; but as citizens, we want to stop terrorists before they attack us. As decision-makers, we value the advice we get from data-driven algorithms; but as decision-makers, we also worry about unintended bias.

Self Paced
Self-Paced
Ethics Decision Making Privacy
Details
Data Science: Wrangling (edX) EdX
HarvardX,Harvard University

Data Science: Wrangling (edX)

Statistics & Data Analysis Data Science

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
Data Science Data Wrangling Text Mining
Details
SQL for Data Science (edX) EdX
IBM

SQL for Data Science (edX)

Statistics & Data Analysis Data Science

Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field. Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases.

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

Data Science: Inference and Modeling (edX)

Statistics & Data Analysis Data Science

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
Statistics Inference Modeling
Details
Computational Thinking and Big Data (edX) EdX
University of Adelaide,AdelaideX

Computational Thinking and Big Data (edX)

CS: Software Engineering Statistics & Data Analysis

Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets. Computational thinking is an invaluable skill that can be used across every industry, as it allows you to formulate a problem and express a solution in such a way that a computer can effectively carry it out.

Self Paced
Self-Paced
Big Data Data Science Algorithmic Thinking
Details
Case Studies in Functional Genomics (edX) EdX
HarvardX,Harvard University

Case Studies in Functional Genomics (edX)

Sci: Biology & Life Sciences Statistics & Data Analysis

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 Analysis Biological Data Genomics
Details
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Statistics & Data Analysis Data Science

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
Probability Machine Learning Regression
Details
Datos para la efectividad de las políticas públicas (edX) EdX
Inter-American Development Bank - IDB,IDBx

Datos para la efectividad de las políticas públicas (edX)

Management & Leadership Economics & Finance

Este curso te ayudará a tomar el control de los datos y familiarizarte con las herramientas para utilizarlos en la planificación, gestión y evaluación de políticas publicas. En esta era de la información, los datos están disponibles en todos lados y crecen a una tasa exponencial. ¿Cómo podemos darles sentido a todos los datos y aprovecharlos en el momento de tomar decisiones?, ¿cómo los utilizamos para que nos ayuden a guiar la gestión y planificación de nuestras políticas? Tanto si eres ciudadano como planificador de políticas, deberías poder responder a estas preguntas.

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

Data Processing and Analysis with Excel (edX)

Statistics & Data Analysis

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
Excel Data Analysis Microsoft Excel
Details