Skills you'll gain: Apache, Big Data, Data Architecture, Distributed Computing Architecture, Computer Architecture, Data Management, Cloud Applications, Cloud Computing, Data Analysis, Data Warehousing, Database Administration, Databases, DevOps, Extract, Transform, Load, Kubernetes, Network Architecture, Other Programming Languages, SQL
Beginner · Course · 1-3 Months
Skills you'll gain: Apache, Big Data, Computer Programming, Data Management, Data Engineering, Other Programming Languages, Data Analysis, Data Analysis Software, SQL, Scala Programming
Intermediate · Course · 1-4 Weeks
Skills you'll gain: Apache, Data Management, Data Analysis, Exploratory Data Analysis, Big Data, Basic Descriptive Statistics, Databases, Extract, Transform, Load, SQL, Business Analysis, Probability & Statistics, Statistical Analysis, Statistical Programming
Intermediate · Course · 1-3 Months
Skills you'll gain: Data Management, Apache, Algorithms, Computer Programming, Machine Learning, Probability & Statistics, Theoretical Computer Science, Data Analysis, Mathematics, Big Data, Databases, SQL, Data Science, Statistical Programming, Exploratory Data Analysis, Machine Learning Algorithms, Applied Machine Learning, Feature Engineering, General Statistics, Basic Descriptive Statistics, Extract, Transform, Load, Data Structures, Dimensionality Reduction, Business Analysis, Statistical Analysis
Intermediate · Specialization · 3-6 Months
Skills you'll gain: Data Management, Databases, Data Architecture, Data Structures, Big Data, Database Theory, SQL, Apache, Database Administration, Extract, Transform, Load, Python Programming, Data Model, Database Application, Data Warehousing, Data Analysis, NoSQL, Data Engineering, Distributed Computing Architecture, Database Design, Operating Systems, System Programming, System Software, Programming Principles, Statistical Programming, Algebra, Computer Architecture, PostgreSQL, Applied Machine Learning, Correlation And Dependence, Feature Engineering, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Regression, Statistical Analysis, Statistical Machine Learning, Data Visualization, Data Visualization Software, Basic Descriptive Statistics, Exploratory Data Analysis, Cloud Applications, Cloud Computing, Data Science, DevOps, Kubernetes, Leadership and Management, Network Architecture, Network Security, Other Programming Languages, Professional Development, Security Engineering, Algorithms, Computational Logic, Computational Thinking, Computer Networking, Computer Programming, Computer Programming Tools, IBM Cloud, Linux, Mathematical Theory & Analysis, Mathematics, Microarchitecture, Project Management, Security Strategy, Software Architecture, Software Engineering, Strategy and Operations, Theoretical Computer Science
Beginner · Professional Certificate · 3-6 Months
Skills you'll gain: Apache, Data Management, Big Data, Machine Learning, Probability & Statistics, Basic Descriptive Statistics, Business Analysis, Correlation And Dependence, Data Analysis, Databases, General Statistics, Machine Learning Algorithms, NoSQL, Regression, SQL, Statistical Analysis, Statistical Programming, Data Science
Intermediate · Course · 1-4 Weeks
Skills you'll gain: Apache, Big Data, Applied Machine Learning, Correlation And Dependence, Data Analysis, Data Architecture, Distributed Computing Architecture, Extract, Transform, Load, Feature Engineering, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Regression, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Algorithms, Data Management, Mathematics, Theoretical Computer Science
Beginner · Course · 1-4 Weeks
Skills you'll gain: Cloud Computing, Microsoft Azure, Data Management, Big Data, Extract, Transform, Load, Data Warehousing, Cloud Storage, Databases, Data Analysis, Computer Networking, Statistical Programming, Apache, Cloud Infrastructure, Computer Architecture, Network Architecture, SQL, Accounting, Business Analysis, Financial Analysis, Computer Programming, Continuous Delivery, Continuous Integration, DevOps, NoSQL, Business Psychology, Entrepreneurship, Leadership and Management, Organizational Development, Application Development, Data Architecture, Network Security, Security Engineering, Security Strategy, Software Engineering, Software Engineering Tools
Intermediate · Professional Certificate · 3-6 Months
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.
Because Spark works in application programming interfaces like Scala, Java, and Python, it helps to have a good grasp of one or more of these programming languages. Other prerequisites may vary depending on the level of the course you're taking. While beginner-level courses allow you to become familiar with Apache Spark and develop skills as you go, intermediate or advanced courses may require additional skills or experience within data science or computer programming. As you progress with learning Apache Spark, you'll develop the skills needed to read and write data to a variety of sources, parse different types of data, work within the artificial intelligence and machine learning arena, and transform data to leverage insights from it.
People with a passion for data science and a desire to gain increased access to big data are well suited to learning Apache Spark. This tool opens a variety of opportunities for users to explore big data and leverage it to solve key problems within organizations. Additionally, Spark offers a faster pace for machine learning workloads, with large scale data processing capability that's exponentially faster than other tools like Hadoop. Because Apache Spark is on the front lines of innovation within AI and big data, those with an innate sense of curiosity and a desire to innovate are among those best suited to learning Spark and working in relevant roles.
If you want to work within big data, learning Apache Spark could be a good move for you. This unified analytics engine is particularly popular because of its speed, the libraries that come with it, robust APIs, and its support for multiple programming languages. Additionally, it could be a smart career move depending on your aspirations. Demand continues to surge for professionals who can leverage Spark's power. In February 2021, Indeed.com listed more than 1,800 open positions looking for full-time Apache Spark professionals across multiple industries. Additionally, according to Databricks, learning Apache Sparks could give you a boost in your earning potential.