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    • Apache Spark

    Apache Spark Courses Online

    Master Apache Spark for big data processing and analytics. Learn to use Spark for real-time data processing and machine learning.

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    Explore the Apache Spark Course Catalog

    • Status: Free
      Free
      I

      IBM

      Machine Learning with Apache Spark

      Skills you'll gain: Apache Spark, Machine Learning, Generative AI, PySpark, Applied Machine Learning, Supervised Learning, Apache Hadoop, Data Pipelines, Unsupervised Learning, Data Processing, Extract, Transform, Load, Predictive Modeling, Classification And Regression Tree (CART), Data Transformation, Regression Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      97 reviews

      Intermediate · Course · 1 - 4 Weeks

    • I

      IBM

      NoSQL, Big Data, and Spark Foundations

      Skills you'll gain: NoSQL, Apache Hadoop, Apache Spark, MongoDB, PySpark, Apache Hive, Databases, Apache Cassandra, Big Data, Machine Learning, Generative AI, IBM Cloud, Applied Machine Learning, Kubernetes, Supervised Learning, Distributed Computing, Docker (Software), Database Management, Data Pipelines, Scalability

      4.5
      Rating, 4.5 out of 5 stars
      ·
      753 reviews

      Beginner · Specialization · 3 - 6 Months

    • I

      IBM

      Introduction to Big Data with Spark and Hadoop

      Skills you'll gain: Apache Hadoop, Apache Spark, PySpark, Apache Hive, Big Data, IBM Cloud, Kubernetes, Docker (Software), Scalability, Data Processing, Distributed Computing, Performance Tuning, Data Transformation, Debugging

      4.4
      Rating, 4.4 out of 5 stars
      ·
      435 reviews

      Intermediate · Course · 1 - 3 Months

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    • E

      Edureka

      Introduction to PySpark

      Skills you'll gain: PySpark, Apache Spark, Distributed Computing, Big Data, Apache Hadoop, Data Processing, Data Manipulation, Exploratory Data Analysis, Python Programming

      3.7
      Rating, 3.7 out of 5 stars
      ·
      34 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: AI skills
      AI skills
      I

      IBM

      IBM Data Engineering

      Skills you'll gain: NoSQL, Data Warehousing, SQL, Apache Hadoop, Extract, Transform, Load, Apache Airflow, Web Scraping, Linux Commands, Database Design, IBM Cognos Analytics, MySQL, Apache Spark, Data Pipelines, Apache Kafka, Database Management, Bash (Scripting Language), Data Store, Jupyter, Generative AI, Professional Networking

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      58K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    What brings you to Coursera today?

    • D

      Duke University

      Spark, Hadoop, and Snowflake for Data Engineering

      Skills you'll gain: PySpark, Snowflake Schema, Databricks, Data Pipelines, Apache Spark, MLOps (Machine Learning Operations), Apache Hadoop, Big Data, Data Warehousing, Data Quality, Data Integration, Data Processing, DevOps, Data Transformation, SQL

      3.8
      Rating, 3.8 out of 5 stars
      ·
      51 reviews

      Advanced · Course · 1 - 4 Weeks

    • I

      IBM

      Scalable Machine Learning on Big Data using Apache Spark

      Skills you'll gain: Apache Spark, PySpark, Applied Machine Learning, Big Data, Machine Learning Methods, Data Storage, Data Pipelines, Machine Learning Algorithms, Distributed Computing, Data Processing, Exploratory Data Analysis, Statistical Analysis

      3.8
      Rating, 3.8 out of 5 stars
      ·
      1.3K reviews

      Intermediate · Course · 1 - 4 Weeks

    • L

      LearnKartS

      Apache Kafka

      Skills you'll gain: Apache Kafka, Real Time Data, System Monitoring, Performance Tuning, Data Pipelines, Apache Spark, Apache Hadoop, Apache, Big Data, Systems Architecture, Continuous Monitoring, Data Processing, Data Integration, Data Architecture, Middleware, Data Security, Distributed Computing, Scala Programming, Software Architecture, Restful API

      4
      Rating, 4 out of 5 stars
      ·
      29 reviews

      Beginner · Specialization · 1 - 3 Months

    • É

      École Polytechnique Fédérale de Lausanne

      Big Data Analysis with Scala and Spark

      Skills you'll gain: Apache Spark, Apache Hadoop, Scala Programming, Distributed Computing, Big Data, Data Manipulation, Data Processing, Performance Tuning, Functional Design, Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • E

      Edureka

      PySpark for Data Science

      Skills you'll gain: PySpark, Apache Spark, Unsupervised Learning, Data Pipelines, Apache Hadoop, Data Processing, Real Time Data, Big Data, Data Visualization, Distributed Computing, Natural Language Processing, Pandas (Python Package), Data Manipulation, Feature Engineering, Machine Learning, Machine Learning Algorithms, SQL, Data Transformation, Supervised Learning, Text Mining

      2.9
      Rating, 2.9 out of 5 stars
      ·
      9 reviews

      Intermediate · Specialization · 3 - 6 Months

    • C

      Coursera Project Network

      Data Analysis Using Pyspark

      Skills you'll gain: PySpark, Matplotlib, Apache Spark, Big Data, Data Processing, Distributed Computing, Data Visualization, Data Analysis, Data Manipulation, Query Languages, Google Cloud Platform

      4.5
      Rating, 4.5 out of 5 stars
      ·
      301 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • I

      IBM

      Introduction to Data Engineering

      Skills you'll gain: Data Store, Extract, Transform, Load, Data Architecture, Data Pipelines, Big Data, Data Warehousing, Data Governance, Apache Hadoop, Relational Databases, Apache Spark, Data Lakes, Databases, SQL, NoSQL, Data Security

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.1K reviews

      Beginner · Course · 1 - 4 Weeks

    What brings you to Coursera today?

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      In summary, here are 10 of our most popular apache spark courses

      • Machine Learning with Apache Spark: IBM
      • NoSQL, Big Data, and Spark Foundations: IBM
      • Introduction to Big Data with Spark and Hadoop: IBM
      • Introduction to PySpark: Edureka
      • IBM Data Engineering: IBM
      • Spark, Hadoop, and Snowflake for Data Engineering: Duke University
      • Scalable Machine Learning on Big Data using Apache Spark: IBM
      • Apache Kafka: LearnKartS
      • Big Data Analysis with Scala and Spark: École Polytechnique Fédérale de Lausanne
      • PySpark for Data Science: Edureka

      Skills you can learn in Machine Learning

      Python Programming (33)
      Tensorflow (32)
      Deep Learning (30)
      Artificial Neural Network (24)
      Big Data (18)
      Statistical Classification (17)
      Reinforcement Learning (13)
      Algebra (10)
      Bayesian (10)
      Linear Algebra (10)
      Linear Regression (9)
      Numpy (9)

      Frequently Asked Questions about Apache Spark

      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.‎

      Online Apache Spark courses offer a convenient and flexible way to enhance your existing knowledge or learn new Apache Spark skills. With a wide range of Apache Spark classes, you can conveniently learn at your own pace to advance your Apache Spark career.‎

      When looking to enhance your workforce's skills in Apache Spark, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

      This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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