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    • Databricks

    Databricks Courses Online

    Explore Databricks for big data processing and analytics. Learn to use Apache Spark and Databricks for scalable data analysis and machine learning.

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    Explore the Databricks Course Catalog

    • L

      LearnQuest

      Data Processing with Azure

      Skills you'll gain: Microsoft Azure, Big Data, Data Processing, Analytics, Data Pipelines, Databricks, Apache Spark, PySpark, Data Analysis, Data Warehousing, Extract, Transform, Load, Real Time Data, Data Transformation, Scheduling, Data Storage

      3.7
      Rating, 3.7 out of 5 stars
      ·
      67 reviews

      Intermediate · Course · 1 - 3 Months

    • P

      Packt

      Streaming Big Data with Spark Streaming, Scala, and Spark 3!

      Skills you'll gain: Apache Kafka, Apache Spark, Scala Programming, Real Time Data, Apache Hadoop, Apache Cassandra, Applied Machine Learning, Big Data, Data Processing, Application Deployment, Distributed Computing, Development Environment

      Advanced · Course · 1 - 3 Months

    • Status: New
      New
      W

      Whizlabs

      Getting Started with Microsoft Fabric

      Skills you'll gain: Power BI, Data Analysis Expressions (DAX), Data Pipelines, Data Transformation, Data Analysis, Microsoft Azure, Analytics, Data Warehousing, Data Integration, Data Processing, Data Cleansing, Data Modeling, Dashboard, Data Governance

      Beginner · Course · 1 - 3 Months

    • 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

    • Status: Free Trial
      Free Trial
      I

      IBM

      SQL for Data Science with R

      Skills you'll gain: Relational Databases, Database Design, SQL, Database Management, Databases, Query Languages, Data Analysis, Exploratory Data Analysis, R Programming, Data Manipulation, Data Modeling, Data Access

      4.3
      Rating, 4.3 out of 5 stars
      ·
      176 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Build and Operate Machine Learning Solutions with Azure

      Skills you'll gain: Microsoft Azure, MLOps (Machine Learning Operations), Databricks, Cloud Computing, Applied Machine Learning, Data Ethics, Data Pipelines, Machine Learning, Tensorflow, Continuous Monitoring, Scalability

      3.8
      Rating, 3.8 out of 5 stars
      ·
      65 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Pandas for Data Science

      Skills you'll gain: Pandas (Python Package), Data Cleansing, Data Manipulation, NumPy, Query Languages, Data Integration, Python Programming, Data Import/Export, Data Analysis, Debugging

      4.3
      Rating, 4.3 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      G

      Google Cloud

      Serverless Data Processing with Dataflow: Foundations

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

      4.2
      Rating, 4.2 out of 5 stars
      ·
      89 reviews

      Intermediate · Course · 1 - 3 Months

    • P

      Packt

      Azure SQL Data Warehouse Synapse Analytics Service

      Skills you'll gain: Azure Synapse Analytics, Data Migration, Microsoft Azure, Data Warehousing, SQL Server Integration Services (SSIS), Microsoft SQL Servers, Cloud Security, Performance Tuning, System Configuration, Cloud Storage, Cloud Computing Architecture, Data Security, Apache Spark, Data Integration

      Intermediate · Course · 1 - 3 Months

    • 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

    • U

      University of California San Diego

      Hadoop Platform and Application Framework

      Skills you'll gain: Apache Hadoop, Big Data, Data Analysis, Apache Spark, Data Science, Data Processing, Distributed Computing, Performance Tuning, Scalability

      4
      Rating, 4 out of 5 stars
      ·
      3.3K reviews

      Mixed · Course · 1 - 3 Months

    • P

      Packt

      Apache Spark with Scala – Hands-On with Big Data!

      Skills you'll gain: Apache Spark, Scala Programming, Data Processing, Big Data, Real Time Data, Programming Principles, Machine Learning Algorithms, Graph Theory, Integrated Development Environments, Data Transformation, Development Environment, Distributed Computing, Build Tools, Regression Analysis, Performance Tuning

      Intermediate · Course · 1 - 3 Months

    Databricks learners also search

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    In summary, here are 10 of our most popular databricks courses

    • Data Processing with Azure: LearnQuest
    • Streaming Big Data with Spark Streaming, Scala, and Spark 3!: Packt
    • Getting Started with Microsoft Fabric: Whizlabs
    • Build and Execute MySQL, PostgreSQL, and SQLServer to Data Catalog Connectors: Google Cloud
    • SQL for Data Science with R: IBM
    • Build and Operate Machine Learning Solutions with Azure: Microsoft
    • Pandas for Data Science: Duke University
    • Serverless Data Processing with Dataflow: Foundations: Google Cloud
    • Azure SQL Data Warehouse Synapse Analytics Service: Packt
    • Scalable Machine Learning on Big Data using Apache Spark: IBM

    Frequently Asked Questions about Databricks

    Databricks is a unified analytics platform that is designed for big data and machine learning. It provides an interactive workspace where users can collaborate, analyze data, build and deploy machine learning models, and create reports and dashboards. Databricks is known for its powerful Apache Spark engine, which enables processing and analyzing large datasets quickly and efficiently. It also offers a rich set of tools and libraries that make it easier for users to work with big data and perform advanced analytics tasks.‎

    To effectively work with Databricks, it is recommended to acquire the following skills:

    1. Apache Spark: Databricks is built on Apache Spark, a popular big data processing framework. Understanding the concepts, architecture, and usage of Apache Spark will help you leverage the full potential of Databricks.

    2. SQL: Having a strong foundation in SQL (Structured Query Language) is essential when working with Databricks. SQL is used for querying and manipulating data in Databricks, so understanding SQL syntax and advanced SQL operations will be beneficial.

    3. Python or Scala: Databricks supports multiple programming languages, but Python and Scala are commonly used. Familiarity with either Python or Scala will be beneficial for scripting, data analysis, and developing custom code in Databricks.

    4. Data manipulation and analysis: Having skills in data manipulation, cleansing, and analysis is crucial for working with Databricks. This includes understanding data structures, data transformation techniques, and statistical analysis.

    5. Machine Learning: Databricks provides built-in support for machine learning frameworks like TensorFlow, PyTorch, and Scikit-Learn. Knowledge of machine learning concepts, algorithms, and model training will enable you to leverage the machine learning capabilities of Databricks effectively.

    6. Cloud platforms: Databricks is often deployed on cloud platforms like AWS, Azure, or Google Cloud. Familiarity with the cloud platform on which Databricks is used will be advantageous for managing resources, accessing data, and setting up the infrastructure.

    By developing these skills, you will be well-equipped to work with Databricks and harness its potential for data processing, analytics, and machine learning.‎

    With Databricks skills, you can pursue various job opportunities in the field of data analysis and data engineering. Some potential job roles you can obtain include:

    1. Data Engineer: As a data engineer with Databricks skills, you can design, develop, and maintain data pipelines and infrastructure needed to process and analyze vast amounts of data.

    2. Data Analyst: With Databricks skills, you can leverage the platform to analyze and interpret complex datasets in order to uncover insights and make data-driven decisions for organizations.

    3. Data Scientist: Databricks skills can be advantageous for data scientists, allowing them to perform advanced analytics and machine learning tasks on big data using the platform's collaborative and scalable environment.

    4. Big Data Engineer: Companies dealing with large-scale data often seek professionals skilled in Databricks to build and maintain big data processing systems, utilizing Apache Spark and other tools supported by Databricks.

    5. Business Intelligence Developer: Databricks skills can also be valuable for business intelligence developers, enabling them to create interactive dashboards, visualizations, and reports by leveraging the platform's data processing capabilities and integrations.

    6. Cloud Solutions Architect: As a cloud solutions architect with Databricks expertise, you can design and implement scalable and efficient cloud-based data solutions using Databricks in conjunction with cloud platforms like AWS, Azure, or Google Cloud.

    These are just a few examples of the job possibilities with Databricks skills. The demand for professionals with Databricks expertise is continuously growing as organizations recognize the importance of effectively managing and extracting insights from their data.‎

    People who are interested in data analytics, data engineering, or machine learning would be best suited for studying Databricks. Additionally, individuals with a background in programming and a strong understanding of data manipulation and analysis would find Databricks beneficial.‎

    There are several topics related to Databricks that you can study. Here are a few options:

    1. Big Data Analysis: Learn how to work with large datasets efficiently using Databricks' unified analytics platform.

    2. Apache Spark: Dive deep into Apache Spark, the open-source big data processing framework that powers Databricks, and understand its architecture, components, and advanced features.

    3. Data Engineering: Master the skills needed to design, build, and maintain data pipelines using Databricks to handle various data sources, transformations, and integrations.

    4. Machine Learning with PySpark: Explore how to leverage Databricks and PySpark libraries to implement machine learning algorithms for tasks such as classification, regression, clustering, and recommendation systems.

    5. Data Visualization with Databricks: Learn how to create interactive and insightful visualizations using Databricks' collaborative environment, enabling you to gain valuable insights from your data.

    6. Cloud Computing: Understand how Databricks utilizes cloud computing technologies like AWS, Azure, or GCP to provide scalable and performant data processing and analytics solutions.

    7. Data Science with Databricks: Develop skills in data exploration, feature engineering, model training, and evaluation using Databricks' collaborative environment along with popular data science libraries like Pandas, NumPy, and scikit-learn.

    These topics cover a range of skills and knowledge related to Databricks, allowing you to improve your proficiency in big data analytics, data engineering, machine learning, and cloud-based data solutions.‎

    Online Databricks courses offer a convenient and flexible way to enhance your knowledge or learn new Databricks is a unified analytics platform that is designed for big data and machine learning. It provides an interactive workspace where users can collaborate, analyze data, build and deploy machine learning models, and create reports and dashboards. Databricks is known for its powerful Apache Spark engine, which enables processing and analyzing large datasets quickly and efficiently. It also offers a rich set of tools and libraries that make it easier for users to work with big data and perform advanced analytics tasks. skills. Choose from a wide range of Databricks courses offered by top universities and industry leaders tailored to various skill levels.‎

    Choosing the best Databricks course depends on your employees' needs and skill levels. Leverage our Skills Dashboard to understand skill gaps and determine the most suitable course for upskilling your workforce effectively. Learn more about 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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