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Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender a utilizar el entorno de Big Data de Spark y Databricks desde cero. Aprenderás, de manera practica y efectiva a generar a utilizar todos los componentes de Spark como Spark SQL, MLlib... Además desarrollaras un modelo de Machine Learning completo con Spark en Databricks.
Register for this course and see more details by visiting:
OpenCourser.com/course/8we8jr/curso
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches Spark and Databricks from the ground up, providing a practical and effective learning experience
Covers all the major components of Spark, including Spark SQL and MLlib, giving learners a comprehensive understanding
Leads learners through the development of a complete Machine Learning model using Spark in Databricks
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Save Curso Completo de Spark con Databricks (Big Data) to your list so you can find it easily later:
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Reviews summary
Spark with databricks big data course
There is a wide range of opinions on this course with over 42% of reviewers rating it among the worst courses they have taken on this platform. Feedback suggests that this course has a basic and introductory overview with some severe issues. Poor instruction and missing course components make it difficult to begin the course and to work through exercises.
Basic fundamentals
"...Es un buen curso a nivel introductorio. Comparte información esencial..."
Insufficient guidance
"...algunos pasos no son los suficientemente claros..."
Missing components
"...no explica la forma de ingresar a databricks, no explica como añadir los notebooks a databricks y el notebook del ejercicio 3 no funciona..."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Curso Completo de Spark con Databricks (Big Data) with these
activities:
Read 'Spark: The Definitive Guide'
Show steps
Gain a comprehensive understanding of Spark by reading this authoritative guide.
View
Spark: The Definitive Guide: Big Data...
on Amazon
Show steps
-
Acquire a copy of the book
-
Read the chapters relevant to the course
-
Take notes and highlight important concepts
Review Spark SQL basics
Show steps
Review the basics of Spark SQL to refresh your knowledge before starting the course.
Browse courses on
Spark SQL
Show steps
-
Read documentation or tutorials on Spark SQL
-
Complete practice exercises on Spark SQL
Follow tutorials on Databricks
Show steps
Enhance your understanding of Databricks by following guided tutorials.
Browse courses on
Databricks
Show steps
-
Find tutorials on Databricks
-
Follow the tutorials step-by-step
-
Practice the concepts learned in the tutorials
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice working with Spark DataFrames
Show steps
Gain practical experience working with Spark DataFrames to solidify your understanding.
Browse courses on
spark dataframes
Show steps
-
Load data into a DataFrame
-
Perform data transformations on the DataFrame
-
Filter and aggregate data in the DataFrame
Create a demonstration of Spark MLlib
Show steps
Develop a deeper understanding of Spark MLlib by creating a demonstration of its capabilities.
Browse courses on
Spark MLlib
Show steps
-
Create a demonstration that showcases the model's performance
-
Choose a machine learning algorithm from Spark MLlib
-
Prepare the data for the algorithm
-
Train and evaluate the machine learning model
Contribute to open-source projects related to Spark
Show steps
Deepen your understanding of Spark by contributing to its open-source community.
Browse courses on
Apache Spark
Show steps
-
Find open-source Spark projects that align with your interests
-
Review the project documentation and codebase
-
Identify areas where you can contribute
-
Submit pull requests with your contributions
Read 'Spark: The Definitive Guide'
Show steps
Gain a comprehensive understanding of Spark by reading this authoritative guide.
View
Spark: The Definitive Guide: Big Data...
on Amazon
Show steps
Show steps
Show steps
- Acquire a copy of the book
- Read the chapters relevant to the course
- Take notes and highlight important concepts
Review Spark SQL basics
Show steps
Review the basics of Spark SQL to refresh your knowledge before starting the course.
Browse courses on
Spark SQL
Show steps
Show steps
Show steps
- Read documentation or tutorials on Spark SQL
- Complete practice exercises on Spark SQL
Follow tutorials on Databricks
Show steps
Enhance your understanding of Databricks by following guided tutorials.
Browse courses on
Databricks
Show steps
Show steps
Show steps
- Find tutorials on Databricks
- Follow the tutorials step-by-step
- Practice the concepts learned in the tutorials
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice working with Spark DataFrames
Show steps
Gain practical experience working with Spark DataFrames to solidify your understanding.
Browse courses on
spark dataframes
Show steps
Show steps
Show steps
- Load data into a DataFrame
- Perform data transformations on the DataFrame
- Filter and aggregate data in the DataFrame
Create a demonstration of Spark MLlib
Show steps
Develop a deeper understanding of Spark MLlib by creating a demonstration of its capabilities.
Browse courses on
Spark MLlib
Show steps
Show steps
Show steps
- Create a demonstration that showcases the model's performance
- Choose a machine learning algorithm from Spark MLlib
- Prepare the data for the algorithm
- Train and evaluate the machine learning model
Contribute to open-source projects related to Spark
Show steps
Deepen your understanding of Spark by contributing to its open-source community.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Find open-source Spark projects that align with your interests
- Review the project documentation and codebase
- Identify areas where you can contribute
- Submit pull requests with your contributions
Career center
Learners who complete Curso Completo de Spark con Databricks (Big Data) will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Responsible for designing, developing, and managing big data systems, a Data Engineer would leverage Spark to build data pipelines and data warehouses. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. With hands-on experience in building real-world data pipelines, this course helps Data Engineers gain the skills required to succeed in this field.
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems and make predictions. This course provides a solid foundation in Spark, which is a powerful tool for data analysis and machine learning. By learning how to use Spark's machine learning library, MLlib, Data Scientists can develop and deploy machine learning models to solve complex business problems.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models. This course provides a deep dive into Spark's MLlib, which is a comprehensive machine learning library. With hands-on experience in developing and deploying machine learning models using Spark, this course helps Machine Learning Engineers gain the skills required to succeed in this field.
Hadoop Developer
Hadoop Developer
A Hadoop Developer is responsible for developing and maintaining Hadoop-based big data solutions. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to develop and maintain Spark-based Hadoop solutions, this course helps Hadoop Developers gain the skills required to succeed in this field.
Big Data Architect
Big Data Architect
A Big Data Architect designs and implements big data solutions. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to design and implement Spark-based big data solutions, this course helps Big Data Architects gain the skills required to succeed in this field.
Data Analyst
Data Analyst
A Data Analyst analyzes data and draws insights from it. This course provides a solid foundation in Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to analyze data using Spark, this course helps Data Analysts gain the skills required to succeed in this field.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to build software systems, this course helps Software Engineers gain the skills required to succeed in this field.
Cloud Engineer
Cloud Engineer
A Cloud Engineer designs, deploys, and manages cloud-based solutions. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to build cloud-based solutions, this course helps Cloud Engineers gain the skills required to succeed in this field.
Business Analyst
Business Analyst
A Business Analyst analyzes business needs and develops solutions to improve business outcomes. This course provides a solid foundation in Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to analyze business data, this course helps Business Analysts gain the skills required to succeed in this field.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to manage and maintain databases, this course helps Database Administrators gain the skills required to succeed in this field.
Systems Analyst
Systems Analyst
A Systems Analyst analyzes and designs computer systems. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to analyze and design computer systems, this course helps Systems Analysts gain the skills required to succeed in this field.
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to manage projects, this course helps Project Managers gain the skills required to succeed in this field.
Quality Assurance Analyst
Quality Assurance Analyst
A Quality Assurance Analyst ensures that software systems meet quality standards. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to test and validate software systems, this course helps Quality Assurance Analysts gain the skills required to succeed in this field.
Technical Writer
Technical Writer
A Technical Writer creates and maintains technical documentation. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to create and maintain technical documentation, this course helps Technical Writers gain the skills required to succeed in this field.
Computer Programmer
Computer Programmer
A Computer Programmer writes and maintains computer code. This course provides a comprehensive introduction to Spark and its ecosystem, including Spark SQL, MLlib, and Databricks. By learning how to use Spark to write and maintain computer code, this course helps Computer Programmers gain the skills required to succeed in this field.
For more career information including salaries, visit:
OpenCourser.com/course/8we8jr/curso
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Curso Completo de Spark con Databricks (Big Data).
Provides a comprehensive reference guide to Spark. It covers a wide range of topics, from Spark's architecture to its APIs and libraries.
Save
Provides a comprehensive overview of Spark, its components, and its use cases. It is particularly useful for readers who are new to Spark or who want to learn more about its core concepts.
Provides a comprehensive guide to using Spark with R. It covers a wide range of topics, from Spark's R API to real-world applications.
Provides a comprehensive overview of advanced analytics with Spark. It covers a wide range of topics, from data engineering and machine learning to streaming and graph processing.
Is an excellent resource to understand the fundamentals of Hadoop. Some of the concepts and principles covered in this book will help you understand Spark.
Covers how to use R with Spark for big data analytics. Useful for those who prefer to use R for data analysis.
Is an introduction to Python for data analysis. Helpful for those who are new to Python or want to refresh their knowledge.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8we8jr/curso
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Leire Ahedo
Good to know
Teaches Spark and Databricks from the ground up, providing a practical and effective learning experience
Covers all the major components of Spark, including Spark SQL and MLlib, giving learners a comprehensive understanding
Leads learners through the development of a complete Machine Learning model using Spark in Databricks
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