The 14 Best Big Data Courses on Coursera for 2021

The Best Big Data Courses on Coursera

Source: Coursera

The editors at Solutions Review have compiled this list of the best big data courses on Coursera to consider if you’re looking to grow your skills.

The growing importance of data management best practices and techniques for delivering against big data are becoming paramount in the enterprise. The big data landscape is evolving in real-time, which has organizations scrambling to utilize their data architectures soundly. Coupled with this, Hadoop and the data lake have emerged as technologies no company can ignore, as they complement the data warehouse quite nicely, and in some cases are even replacing it.

With this in mind, we’ve compiled this list of the best big data courses on Coursera if you’re looking to grow your skills for work or play. Coursera is one of the top online education platforms in the world, partnering with more than 200 universities and companies to provide a range of learning opportunities. The platform touts more than 77 million learners around the globe. As you can see below, we broke the best big data courses on Coursera down into categories based on the recommended proficiency level. Each section also features our inclusion criteria. Click GO TO TRAINING to learn more and register.

Best Big Data Courses on Coursera for Beginners

Note: We included top-rated Coursera big data training via the Level selection to make your search easier.

Big Data, Artificial Intelligence, and Ethics

Description: This course gives you context and first-hand experience with the two major catalyzers of the computational science revolution: big data and artificial intelligence. With more than 99% of all mediated information in digital format and with 98% of the world population using digital technology, humanity produces an impressive digital footprint. In theory, this provides unprecedented opportunities to understand and shape society.

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Foundations for Big Data Analysis with SQL

Description: In this course, you’ll get a big-picture view of using SQL for big data, starting with an overview of data, database systems, and the common querying language (SQL). Then you’ll learn the characteristics of big data and SQL tools for working on big data platforms. You’ll also install an exercise environment (virtual machine) to be used through the specialization courses, and you’ll have an opportunity to do some initial exploration of databases and tables in that environment.

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Analyzing Big Data with SQL

Description: In this course, you’ll get an in-depth look at the SQL SELECT statement and its main clauses. The course focuses on big data SQL engines Apache Hive and Apache Impala, but most of the information is applicable to SQL with traditional RDBMs as well; the instructor explicitly addresses differences for MySQL and PostgreSQL.

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Managing Big Data in Clusters and Cloud Storage

Description: In this course, you’ll learn how to manage big datasets, how to load them into clusters and cloud storage, and how to apply structure to the data so that you can run queries on it using distributed SQL engines like Apache Hive and Apache Impala. You’ll learn how to choose the right data types, storage systems, and file formats based on which tools you’ll use and what performance you need.

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Best Big Data Courses on Coursera for Intermediate

Note: We included top-rated Coursera big data training via the Level selection to make your search easier.

Big Data Essentials: HDFS, MapReduce and Spark RDD

Description: In this 6-week course, you will learn some basic technologies of the modern big data landscape, be guided both through system internals and their applications, and learn about distributed file systems, why they exist, and what functions they serve. Get ready to work with real datasets alongside with real masters!

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Google Cloud Platform Big Data and Machine Learning Fundamentals

Description: This course introduces participants to the big data capabilities of Google Cloud. Through a combination of presentations, demos, and hands-on labs, participants get an overview of Google Cloud and a detailed view of the data processing and machine learning capabilities. This course showcases the ease, flexibility, and power of big data solutions on Google Cloud.

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Best Big Data Courses on Coursera for All Levels

Note: We included top-rated Coursera big data training via the Level selection to make your search easier.

Introduction to Big Data

Description: This course is for those new to data science and interested in understanding why the big data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how big data might be useful in their business or career.

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Graph Analytics for Big Data

Description: This course gives you a broad overview of the field of graph analytics so you can learn new ways to model, store, retrieve and analyze graph-structured data. After completing this course, you will be able to model a problem into a graph database and perform analytical tasks over the graph in a scalable manner. Better yet, you will be able to apply these techniques to understand the significance of your data sets for your own projects.

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Hadoop Platform and Application Framework

Description: This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment.

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Big Data Modeling and Management Systems

Description: In this course, you will experience various data genres and management tools appropriate for each. You 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. Through guided hands-on tutorials, you will become familiar with techniques using real-time and semi-structured data examples.

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Machine Learning With Big Data

Description: This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems.

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Managing Big Data with MySQL

Description: This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases.

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Big Data – Capstone Project

Description: In this culminating project, you will build a big data ecosystem using tools and methods from the earlier courses in Coursera’s big data specialization. You will analyze a data set simulating big data generated from a large number of users who are playing our imaginary game “Catch the Pink Flamingo”. During the five-week Capstone Project, you will walk through the typical big data science steps for acquiring, exploring, preparing, analyzing, and reporting.

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Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud

Description: In this course, instructors continue Cloud Computing Applications by exploring how the cloud opens up data analytics of huge volumes of data that are static or streamed at high velocity and represent an enormous variety of information. Learners start the first week by introducing some major systems for data analysis including Spark and the major frameworks and distributions of analytics applications including Hortonworks, Cloudera, and MapR.

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NOW READ: The Best Big Data Courses and Online Training to Consider (All platforms)

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Timothy King
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