Apache Spark is an open source analytics framework for large-scale data processing with capabilities for streaming, SQL, machine learning, and graph processing. Apache Spark is important to learn because its ease of use and extreme processing speeds enable efficient and scalable real-time data analysis.

Apache Spark can process in-memory on dedicated clusters to achieve speeds 10-100 times faster than the disc-based batch processing Apache Hadoop with MapReduce can provide, making it a top choice for anyone processing big data. Spark is also easy to use, with the ability to write applications in its native Scala, or in Python, Java, R, or SQL. This versatility and accessibility helps startups harness the powerful data science they need for cutting edge innovation.

Spark also provides the scalable machine learning needed by artificial intelligence (AI) engineers to create applications that can transform the way we interact with digital technology, from recommendation algorithms on services like Netflix and Spotify to automated medical screening.

Many careers in data science benefit from skills in Apache Spark, as software development engineers, data scientists, data analysts, and machine learning engineers use Spark on a daily basis. These roles are in high demand and are thus highly compensated; according to Glassdoor, machine learning engineers earn an average salary of $114,121 per year.

Machine learning engineers design and build self-learning software and monitor its iterations to fine tune how models perform when they are scaled up and put into service. These professionals need a background in both software engineering and data science, and are increasingly being hired in a wide variety of fields such as education, healthcare, and finance. As machine learning continues to expand into many more fields, the need for machine learning engineers will continue to grow.

Yes! Coursera offers a wide range of popular online courses and Specializations on data science in general and Apache Spark specifically, including courses in related topics like scalable machine learning, distributed computing, and big data analysis. You’ll learn from top-ranked institutions and organizations like the University of California Davis, the University of California San Diego, École Polytechnique Fédérale de Lausanne, and IBM, so you don’t have to sacrifice the quality of your education for the flexibility of learning remotely.

Coursera also offers the courses needed to work towards the IBM AI Engineering Professional Certificate. And, if you want to take your data science education to the next level, Coursera provides you with the opportunity to pursue a Master of Science in Data Science through the University of Colorado.