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    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

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Perform data science with Azure Databricks

      Skills you'll gain: PySpark, Databricks, Apache Spark, MLOps (Machine Learning Operations), Microsoft Azure, Big Data, Scikit Learn (Machine Learning Library), Deep Learning, Data Transformation, Machine Learning, Distributed Computing, Feature Engineering, Exploratory Data Analysis

      3.2
      Rating, 3.2 out of 5 stars
      ·
      74 reviews

      Intermediate · Course · 1 - 3 Months

    • E

      Edureka

      Learn SQL with Databricks

      Skills you'll gain: Databricks, SQL, Database Management, Data Manipulation, Stored Procedure, Query Languages, Data Security, Data Sharing, Big Data, Performance Tuning, Data Integration

      3.7
      Rating, 3.7 out of 5 stars
      ·
      14 reviews

      Beginner · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Data Management with Databricks: Big Data with Delta Lakes

      Skills you'll gain: Databricks, Data Lakes, Data Pipelines, Data Integration, Extract, Transform, Load, Dashboard, PySpark, SQL, Data Management, Data Transformation, Version Control

      4.2
      Rating, 4.2 out of 5 stars
      ·
      26 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • E

      Edureka

      Business Intelligence with Databricks

      Skills you'll gain: Business Intelligence, Databricks, Data Sharing, Business Analytics, Data Warehousing, Azure Synapse Analytics, Database Development, Data Visualization Software, Data Integration, Data Analysis, SQL, Data Governance

      4
      Rating, 4 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      M

      Microsoft

      Microsoft Azure Data Scientist Associate (DP-100) Exam Prep

      Skills you'll gain: Databricks, Unsupervised Learning, PySpark, Microsoft Azure, Apache Spark, Scikit Learn (Machine Learning Library), MLOps (Machine Learning Operations), PyTorch (Machine Learning Library), Exploratory Data Analysis, Deep Learning, Data Visualization, Applied Machine Learning, Regression Analysis, Data Science, Predictive Modeling, Jupyter, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Classification And Regression Tree (CART), Cloud Computing

      4.2
      Rating, 4.2 out of 5 stars
      ·
      546 reviews

      Intermediate · Professional Certificate · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Large Language Model Operations (LLMOps)

      Skills you'll gain: Prompt Engineering, Databricks, Large Language Modeling, Generative AI, Performance Analysis, Apache Airflow, Workflow Management, Data Lakes, ChatGPT, Extract, Transform, Load, OpenAI, AWS SageMaker, Performance Tuning, Scalability, Dataflow, Data Transformation, Data Infrastructure, Microsoft Azure, MLOps (Machine Learning Operations), Natural Language Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      179 reviews

      Beginner · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      D

      Duke University

      Databricks to Local LLMs

      Skills you'll gain: Databricks, Generative AI, Data Lakes, Extract, Transform, Load, MLOps (Machine Learning Operations), Data Transformation, Data Pipelines, Large Language Modeling, Apache Spark, Analytics, Data Analysis, Data Ethics, Data Science, CI/CD, Data Governance

      4.4
      Rating, 4.4 out of 5 stars
      ·
      7 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      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
      ·
      439 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      I

      IBM

      Databases and SQL for Data Science with Python

      Skills you'll gain: SQL, Databases, Stored Procedure, Relational Databases, Database Design, Query Languages, Database Management, Data Analysis, Jupyter, Data Manipulation, Pandas (Python Package), Transaction Processing

      4.7
      Rating, 4.7 out of 5 stars
      ·
      22K reviews

      Beginner · Course · 1 - 3 Months

    • W

      Whizlabs

      Data Governance with Databricks

      Skills you'll gain: Data Governance, Extract, Transform, Load, Metadata Management, Role-Based Access Control (RBAC), Data Cleansing, Databricks, Data Management, Data Pipelines, Amazon Web Services, Data Lakes, Data Migration, Data Architecture, Data Security, Personally Identifiable Information, Data Warehousing, Data Quality, General Data Protection Regulation (GDPR), Data Capture

      3.5
      Rating, 3.5 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 4 Weeks

    • B

      Board Infinity

      Data Governance with Databricks

      Skills you'll gain: Data Governance, Databricks, Data Management, Data Architecture, Metadata Management, Information Management, Data Strategy, Data Security, Data Quality

      2.7
      Rating, 2.7 out of 5 stars
      ·
      27 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: New
      New
      Status: Free Trial
      Free Trial
      P

      Packt

      Mastering Azure Databricks for Data Engineers

      Skills you'll gain: Databricks, CI/CD, Real Time Data, Data Governance, Apache Spark, Microsoft Azure, Data Lakes, Data Architecture, Data Management, Cloud Engineering, Big Data, Secure Coding, Data Storage Technologies, Integration Testing, Automation, Data Infrastructure, Data Pipelines, Restful API, Command-Line Interface, Systems Design

      Intermediate · Specialization · 1 - 3 Months

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

    • Perform data science with Azure Databricks: Microsoft
    • Learn SQL with Databricks: Edureka
    • Data Management with Databricks: Big Data with Delta Lakes: Coursera Project Network
    • Business Intelligence with Databricks: Edureka
    • Microsoft Azure Data Scientist Associate (DP-100) Exam Prep: Microsoft
    • Large Language Model Operations (LLMOps): Duke University
    • Databricks to Local LLMs: Duke University
    • Introduction to Big Data with Spark and Hadoop: IBM
    • Databases and SQL for Data Science with Python: IBM
    • Data Governance with Databricks: Whizlabs

    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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