The current global crisis caused by COVID-19 has changed every aspect of human life, from the way people live, learn, and work, to communicate with each other. As the pandemic hit the world, billions of people have now sent to stay home to prevent the spread of the contagious virus. However, this has also created opportunities for learners to explore and learn new things to enhance and improve their skill sets during the Corona-led lockdowns. In this time, a majority of institutions and universities around the world are offering free online courses across various disciplines.
Here we have accumulated the best free online data management courses to enroll during the COVID-19 lockdown.
This course from Wesleyan University will provide learners to discover what data is and think about what questions they have that can be answered by the data, even if candidates have never thought about data before. The course will also offer learners to develop a research question, describe the variables and their relationships, calculate basic statistics, and present their results clearly. By the end of the course, learners will be able to use powerful data analysis tools, such as SAS or Python, to manage and visualize data, including how to deal with missing data, variable groups, and graphs. Moreover, during the course, candidates will share their progress with others to gain valuable feedback, while also learning how their peers use data to answer their own questions.
This course, offered by the University of North Carolina at Chapel Hill and the University of Edinburgh, will provide learners with an introduction to research data management and sharing. After completing this course, learners will understand the diversity of data and their management needs across the research data lifecycle, be able to identify the components of good data management plans, and be familiar with best practices for working with data including the organization, documentation, and storage and security of data. Learners will also understand the impetus and importance of archiving and sharing data as well as how to assess the trustworthiness of repositories.
With this one-week course, candidates will learn the process of analyzing data and how to manage that process. Provided by John Hopkins University, the course will describe the iterative nature of data analysis and the role of stating a sharp question, exploratory data analysis, inference, formal statistical modeling, interpretation, and communication. After completing this course, learners will know how to describe the basic data analysis iteration, identify different types of questions and translate them to specific datasets, and describe different types of data pulls. With this course, the learners will also able to explore datasets to determine if data are appropriate for a given question, direct model building efforts in common data analyses, interpret the results from common data analyses and integrate statistical findings to form coherent data analysis presentations.
This data management course from Vanderbilt University presents critical concepts and practical methods to support planning, collection, storage, and dissemination of data in clinical research. Understanding and implementing solid data management principles is critical for any scientific domain. So, through practical lessons, short quizzes, and hands-on exercises, the course will help aspirants learn best practices for data management. After completing this course, learners will gain skill set in data management principles that will increase their productivity and improve their science.
This course, offered by the University of California, San Diego, will provide learners to experience various data genres and management tools appropriate for each. Through this course, candidates will be able to describe the reasons behind the evolving plethora of new big data platforms from the perspective of big data management systems and analytical tools. With guided hands-on tutorials, they will become familiar with techniques using real-time and semi-structured data examples. In this course, systems and tools discussed include AsterixDB, HP Vertica, Impala, Neo4j, Redis, SparkSQL. Additionally, the course will provide techniques to extract value from existing untapped data sources and discovering new data sources.
The enterprise data management course from Indiana University focuses on realizing the business advantage and business potential of operational, reconciled, and big data systems as well. In this course, learners will learn how to: design relational databases that are used to manage operational systems; query relational databases using Structured Query Language (SQL); and how to design data warehouses and business intelligence systems. Through this course, candidates will understand the principles of data profiling, data integration, and master data management; and the basics of Hadoop, Hive and Pig.