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    • Apache Spark

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    54 results for "apache spark"

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      IBM Skills Network

      Introduction to Big Data with Spark and Hadoop

      Skills you'll gain: Distributed Computing Architecture, Kubernetes, Apache, Big Data, Extract, Transform, Load, Data Management, Cloud Computing, Computer Architecture

      4.3

      (105 reviews)

      Beginner · Course · 1-3 Months

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      University of California San Diego

      Big Data

      Skills you'll gain: Algorithms, Apache, Apache Spark, Big Data, Business Analysis, Computer Architecture, Computer Programming, Data Analysis, Data Architecture, Data Clustering Algorithms, Data Management, Data Model, Data Visualization, Data Warehousing, Database Administration, Databases, Distributed Computing Architecture, Exploratory Data Analysis, General Statistics, Graph Theory, Machine Learning, Machine Learning Algorithms, Mathematics, NoSQL, PostgreSQL, Probability & Statistics, Python Programming, Regression, SQL, Statistical Classification, Statistical Programming, Theoretical Computer Science

      4.5

      (13.3k reviews)

      Beginner · Specialization · 3-6 Months

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      Databricks

      Apache Spark (TM) SQL for Data Analysts

      Skills you'll gain: Data Analysis, Statistical Analysis, SQL, Exploratory Data Analysis, Apache, Statistical Programming, Probability & Statistics, Data Management, Business Analysis, Databases, Big Data

      4.5

      (357 reviews)

      Intermediate · Course · 1-3 Months

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      University of California, Davis

      Learn SQL Basics for Data Science

      Skills you'll gain: Analysis, Apache, Apache Spark, Basic Descriptive Statistics, Big Data, Computer Programming, Data Management, Databases, General Statistics, Leadership and Management, Machine Learning, Probability & Statistics, Python Programming, SQL, Statistical Programming

      4.6

      (13.8k reviews)

      Beginner · Specialization · 3-6 Months

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      University of California, Davis

      Distributed Computing with Spark SQL

      Skills you'll gain: Apache, Statistical Programming, Big Data, Machine Learning, SQL, Databases, Data Management, Apache Spark

      4.5

      (494 reviews)

      Intermediate · Course · 1-4 Weeks

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      IBM Skills Network

      Scalable Machine Learning on Big Data using Apache Spark

      Skills you'll gain: Databases, Statistical Analysis, Machine Learning Algorithms, NoSQL, General Statistics, Probability & Statistics, Apache Spark, Big Data, Apache, Statistical Programming, Data Analysis, Machine Learning, Regression, Correlation And Dependence, SQL, Business Analysis, Data Management, Basic Descriptive Statistics

      3.8

      (1.2k reviews)

      Intermediate · Course · 1-4 Weeks

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      Microsoft

      Microsoft Azure Databricks for Data Engineering

      Skills you'll gain: Security Strategy, Security Engineering, Computer Networking, Computer Programming, Statistical Programming, Apache, Data Architecture, Network Security, Data Management, Microsoft Azure, Cloud Computing, Big Data

      4.7

      (27 reviews)

      Intermediate · Course · 1-3 Months

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      Coursera Project Network

      Working with Big Data

      Skills you'll gain: Big Data, Apache, Data Management

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Use the Apache Spark Structured Streaming API with MongoDB

      Intermediate · Guided Project · Less Than 2 Hours

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      University of California San Diego

      Hadoop Platform and Application Framework

      Skills you'll gain: Computer Architecture, Big Data, Apache, Apache Spark, Data Management, Distributed Computing Architecture

      4.0

      (3.3k reviews)

      Mixed · Course · 1-3 Months

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      Microsoft

      Data Engineering with MS Azure Synapse Apache Spark Pools

      Skills you'll gain: Big Data, Cloud Computing, Microsoft Azure, Data Management

      4.2

      (14 reviews)

      Intermediate · Course · 1-4 Weeks

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      Google Cloud

      Machine Learning with Spark on Google Cloud Dataproc

      Intermediate · Project · Less Than 2 Hours

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

    • Introduction to Big Data with Spark and Hadoop: IBM Skills Network
    • Big Data: University of California San Diego
    • Apache Spark (TM) SQL for Data Analysts: Databricks
    • Learn SQL Basics for Data Science: University of California, Davis
    • Distributed Computing with Spark SQL: University of California, Davis
    • Scalable Machine Learning on Big Data using Apache Spark: IBM Skills Network
    • Microsoft Azure Databricks for Data Engineering: Microsoft
    • Working with Big Data: Coursera Project Network
    • Use the Apache Spark Structured Streaming API with MongoDB: Coursera Project Network
    • Hadoop Platform and Application Framework: University of California San Diego

    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.‎

    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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