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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

    • G

      Google Cloud

      Building Realtime Pipelines in Cloud Data Fusion

      Skills you'll gain: Cloud-Based Integration, Real Time Data, Data Pipelines, Apache Spark, Data Integration, Data Transformation, Data Wrangling

      Beginner · Project · Less Than 2 Hours

    • G

      Google Cloud

      Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors

      Skills you'll gain: MySQL, Google Cloud Platform, Data Mining, Database Administration, Microsoft SQL Servers, Cloud API, PostgreSQL, Metadata Management

      4.8
      Rating, 4.8 out of 5 stars
      ·
      12 reviews

      Beginner · Project · Less Than 2 Hours

    • K

      KodeKloud

      DevOps Prerequisite Course

      Skills you'll gain: Linux Administration, Devops Tools, General Networking, Linux, Linux Commands, Systems Administration, Network Administration, Application Development, Unix, TCP/IP, Network Troubleshooting, Package and Software Management, Application Servers, Development Environment, Command-Line Interface, Java, Software Installation, Node.JS

      4.6
      Rating, 4.6 out of 5 stars
      ·
      63 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New
      J

      Johns Hopkins University

      Data Analysis Using Hadoop Tools

      Skills you'll gain: Apache Hadoop, Apache Hive, Big Data, Apache Spark, NoSQL, Data Management, Data Processing, SQL, Query Languages, Data Manipulation, Scripting Languages, Data Transformation

      Intermediate · Course · 1 - 3 Months

    • D

      Duke University

      Data Engineering with Rust

      Skills you'll gain: Data Pipelines, Rust (Programming Language), Restful API, Amazon Web Services, Data Structures, Secure Coding, Data Processing, Cloud Applications, Data Manipulation, Encryption, Algorithms

      3.6
      Rating, 3.6 out of 5 stars
      ·
      50 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google Cloud

      Building Batch Data Pipelines on GCP en Français

      Skills you'll gain: Data Pipelines, Google Cloud Platform, Apache Airflow, Data Processing, Big Data, Extract, Transform, Load, Data Integration, Data Transformation, Serverless Computing, Apache Spark, Apache Hadoop, Public Cloud

      Intermediate · Course · 1 - 3 Months

    • U

      University of Virginia

      Design Thinking: Discovery Tools

      Skills you'll gain: Design Thinking, Human Centered Design, Stakeholder Management, Persona Development, Process Mapping, Value Engineering, User Research, Customer experience improvement, Qualitative Research, Customer Insights, Business Workflow Analysis, Consumer Behaviour, Innovation, Interviewing Skills

      4.7
      Rating, 4.7 out of 5 stars
      ·
      26 reviews

      Beginner · Course · 1 - 3 Months

    • G

      Google Cloud

      Serverless Data Processing with Dataflow en Español

      Skills you'll gain: Dataflow, Data Pipelines, Serverless Computing, Data Processing, Apache Kafka, Cloud Security, Identity and Access Management, Performance Tuning, Google Cloud Platform, Site Reliability Engineering, Data Infrastructure, Maintainability, Real Time Data, Data Transformation, Debugging, Extract, Transform, Load, System Monitoring, CI/CD, Containerization, Unit Testing

      Intermediate · Specialization · 3 - 6 Months

    • P

      Packt

      The Ultimate Hands-On Hadoop

      Skills you'll gain: Apache Hadoop, Real Time Data, Apache Kafka, Apache Hive, Apache Spark, AWS Kinesis, Apache Cassandra, Big Data, PySpark, Database Systems, MongoDB, SQL, Data Processing, NoSQL, System Design and Implementation, Distributed Computing, Scalability

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Analyze Data in Azure ML Studio

      Skills you'll gain: Descriptive Statistics, Jupyter, Microsoft Azure, Matplotlib, Feature Engineering, Scatter Plots, Data Analysis, Statistics, Exploratory Data Analysis, Seaborn, Data Visualization Software, Correlation Analysis, Applied Machine Learning

      Beginner · Guided Project · Less Than 2 Hours

    • G

      Google Cloud

      Serverless Data Processing with Dataflow:Foundations Español

      Skills you'll gain: Dataflow, Serverless Computing, Data Pipelines, Data Processing, Cloud Security, Identity and Access Management, Google Cloud Platform, Data Transformation, Containerization, Data Storage Technologies, Scalability

      Intermediate · Course · 1 - 3 Months

    • Status: New
      New
      C

      Coursera Project Network

      Machine Learning with PySpark: Recommender System

      Skills you'll gain: PySpark, Data Pipelines, Data Processing, AI Personalization, Dimensionality Reduction, OpenAI, Pandas (Python Package), Data Transformation, Predictive Modeling, Unsupervised Learning, Applied Machine Learning, Machine Learning

      Intermediate · Guided Project · Less Than 2 Hours

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

    • Building Realtime Pipelines in Cloud Data Fusion: Google Cloud
    • Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors: Google Cloud
    • DevOps Prerequisite Course: KodeKloud
    • Data Analysis Using Hadoop Tools: Johns Hopkins University
    • Data Engineering with Rust: Duke University
    • Building Batch Data Pipelines on GCP en Français: Google Cloud
    • Design Thinking: Discovery Tools: University of Virginia
    • Serverless Data Processing with Dataflow en Español: Google Cloud
    • The Ultimate Hands-On Hadoop: Packt
    • Analyze Data in Azure ML Studio: Coursera Project Network

    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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