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    Results for "apache spark"

    • Packt

      Linux Operating System: A Complete Linux Guide for Beginners

      Skills you'll gain: Linux, Linux Administration, Linux Servers, Apache, Linux Commands, Unix Commands, Bash (Scripting Language), Command-Line Interface, File Management, Operating Systems, System Monitoring, Firewall, System Configuration, Virtual Environment, Virtual Machines

      Beginner · Course · 1 - 3 Months

    • Google Cloud

      Building Batch Pipelines in Cloud Data Fusion

      Skills you'll gain: Data Wrangling, Data Transformation, Data Pipelines, Extract, Transform, Load, Cloud Engineering, Google Cloud Platform, Data Integration, Cloud-Based Integration

      Beginner · Project · Less Than 2 Hours

    • Status: Free
      Free

      Exploratorium

      Tinkering Fundamentals: Motion and Mechanisms

      Skills you'll gain: Collaboration, Creative Thinking, Creativity, Curiosity, Design Thinking, Mechanics, Research and Design, Research, Creative Problem-Solving, Experimentation, Engineering Design Process, Liberal Arts, Mechanical Design, Storytelling, Aesthetics, Engineering

      4.8
      Rating, 4.8 out of 5 stars
      ·
      27 reviews

      Beginner · Course · 1 - 3 Months

    • Google Cloud

      Confluent: Clickstream Data Analysis Pipeline Using ksqlDB

      Skills you'll gain: Grafana, Apache Kafka, Real Time Data, Data Pipelines, Dashboard, Data Synthesis, Interactive Data Visualization

      Intermediate · Project · Less Than 2 Hours

    • Universidad Nacional Autónoma de México

      Designing data-intensive applications

      Skills you'll gain: Data Mining, Database Design, Scalability, Database Systems, Relational Databases, Unstructured Data, Transaction Processing, Databases, Systems Design, Big Data, Data Architecture, Data Warehousing, Information Systems, NoSQL, Data Processing, Maintainability, SQL, Apache Hadoop

      4.2
      Rating, 4.2 out of 5 stars
      ·
      38 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Whizlabs

      Exam Prep (DEA-C01): AWS Certified Data Engineer - Associate

      Skills you'll gain: AWS SageMaker, AWS CloudFormation, Amazon S3, Serverless Computing, Amazon DynamoDB, Amazon CloudWatch, Cloud Security, Data Security, Amazon Redshift, AWS Kinesis, Data Integration, Cloud Storage, Amazon Web Services, Data Lakes, Data Storage, Databases, Apache Airflow, Cloud Computing Architecture, Infrastructure as Code (IaC), Cloud-Native Computing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      10 reviews

      Intermediate · Specialization · 3 - 6 Months

    • LearnQuest

      Advanced Java

      Skills you'll gain: Apache Maven, Spring Framework, Microservices, Java Platform Enterprise Edition (J2EE), Spring Boot, Java, Back-End Web Development, Software Architecture, Load Balancing, Cloud Development, Restful API, Systems Architecture, Web Development, Web Applications, Scalability

      4.4
      Rating, 4.4 out of 5 stars
      ·
      48 reviews

      Advanced · Course · 1 - 4 Weeks

    • Google Cloud

      Omnibond: Creating an HPC Environment in Google Cloud with CloudyCluster

      Skills you'll gain: Google Cloud Platform, Cloud Computing, Cloud Infrastructure, Computing Platforms, Jupyter, System Configuration

      Beginner · Project · Less Than 2 Hours

    • Alibaba Cloud Academy

      Big Data Analytical Platform on Alibaba Cloud

      Skills you'll gain: Data Visualization Software, Big Data, Apache Hadoop, Apache Spark, Apache Hive, Distributed Computing, Data Processing, Data Warehousing, Data Analysis, Cloud Security, Cloud Technologies, Artificial Intelligence and Machine Learning (AI/ML), SQL, Artificial Intelligence

      4.3
      Rating, 4.3 out of 5 stars
      ·
      52 reviews

      Intermediate · Course · 1 - 3 Months

    • EDUCBA

      Build A Data Warehouse in Azure

      Skills you'll gain: Data Warehousing, Power BI, Data Lakes, Data Integration, Data Architecture, Microsoft Azure, Apache Spark, SQL Server Integration Services (SSIS), Data Storage, Database Management, Data Pipelines, Performance Tuning, Data Processing, Query Languages, Data Security, Scalability

      4.9
      Rating, 4.9 out of 5 stars
      ·
      39 reviews

      Beginner · Course · 1 - 3 Months

    • Packt

      Apache Kafka Series - Learn Apache Kafka for Beginners v3

      Skills you'll gain: Apache Kafka, Command-Line Interface, Java Programming, Real Time Data, Data Pipelines, Data Processing, Performance Tuning, System Configuration, Scalability

      Intermediate · Course · 3 - 6 Months

    • Status: New
      New

      Johns Hopkins University

      HDFS Architecture and Programming

      Skills you'll gain: Apache Hadoop, File Systems, Big Data, Data Structures, Java Programming, Infrastructure Architecture, File Management, Systems Architecture, Data Processing, Distributed Computing, Data Storage, Development Environment, Scalability, Application Programming Interface (API)

      Intermediate · Course · 1 - 4 Weeks

    Searches related to apache spark

    apache spark with scala – hands-on with big data!
    machine learning with apache spark
    scalable machine learning on big data using apache spark
    1…151617…23

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

    • Linux Operating System: A Complete Linux Guide for Beginners: Packt
    • Building Batch Pipelines in Cloud Data Fusion: Google Cloud
    • Tinkering Fundamentals: Motion and Mechanisms: Exploratorium
    • Confluent: Clickstream Data Analysis Pipeline Using ksqlDB: Google Cloud
    • Designing data-intensive applications: Universidad Nacional Autónoma de México
    • Exam Prep (DEA-C01): AWS Certified Data Engineer - Associate: Whizlabs
    • Advanced Java: LearnQuest
    • Omnibond: Creating an HPC Environment in Google Cloud with CloudyCluster: Google Cloud
    • Big Data Analytical Platform on Alibaba Cloud : Alibaba Cloud Academy
    • Build A Data Warehouse in Azure: EDUCBA

    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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