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Swetha Kolalapudi
80% of a data scientist's job is data preparation. This course is all about data preparation i.e. cleaning, transforming, summarizing data using Spark.
Read more
80% of a data scientist's job is data preparation. This course is all about data preparation i.e. cleaning, transforming, summarizing data using Spark.
Read more
80% of a data scientist's job is data preparation. This course is all about data preparation i.e. cleaning, transforming, summarizing data using Spark.
Data preparation is a staple task for any data professional, whether you just want to explore data or develop sophisticated Machine Learning models. Spark is an engine that helps do this in a very intuitive way, using functional constructs that abstract the user from all the messiness of working with large datasets. In this course, Beginning Data Exploration and Analysis with Apache Spark, you'll go through exploratory data analysis and data munging with Spark, step-by-step. First, you'll explore RDDs and functional constructs that make processing in Spark extremely intuitive. Next, you'll discover how to transform and clean unstructured data. Finally, you'll learn how to summarize data along dimensions and how to model relationships to build co-occurrence networks. By the end of this course, you'll be able to use Spark to transform data in any way that you would like.
Register for this course and see more details by visiting:
OpenCourser.com/course/3sb4fj/beginning
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What's inside
Syllabus
Course Overview
Getting Started with Spark's Resilient Distributed Datasets
Transforming and Cleaning Unstructured Data
Summarizing Data Along Dimensions
Read more
Syllabus
Course Overview
Getting Started with Spark's Resilient Distributed Datasets
Transforming and Cleaning Unstructured Data
Summarizing Data Along Dimensions
Read more
Modeling Relationships in the Marvel Social Universe
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines data preparation, a vital skill for both data exploration and modeling
Taught by industry experts who are recognized for their work in data science
Emphasizes hands-on practice with Apache Spark, a popular tool for data preparation
Develops skills in transforming, cleaning, and summarizing data, which are essential for data analysis
Provides a comprehensive overview of data preparation, covering key concepts and techniques
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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 Beginning Data Exploration and Analysis with Apache Spark with these
activities:
Read 'Learning Spark'
Show steps
Gain a comprehensive understanding of Spark concepts and best practices.
View
Learning Spark: Lightning-Fast Big Data Analysis
on Amazon
Show steps
-
Read through the book, focusing on the chapters relevant to course topics
-
Take notes and highlight important concepts
Read through Spark documentation
Show steps
Reinforce knowledge of functional programming and prepare for Spark concepts introduced in the course.
Browse courses on
Apache Spark
Show steps
-
Read through the Spark SQL, DataFrames and Datasets Programming Guide
-
Review the Apache Spark Programming Guide
Follow Spark Tutorials on Data Summarization
Show steps
Enhance your knowledge of data summarization techniques by exploring guided tutorials.
Show steps
-
Search for tutorials on Spark data summarization
-
Follow the steps and implement the techniques
-
Experiment with different data summarization methods
One other activity
Expand to see all activities and additional details
Show all four activities
Data Munging Exercises with Spark
Show steps
Reinforce your understanding of data munging techniques by working through practical exercises.
Show steps
-
Find datasets online and import them into Spark
-
Apply data cleaning and transformation operations
-
Export the transformed data in different formats
Read 'Learning Spark'
Show steps
Gain a comprehensive understanding of Spark concepts and best practices.
View
Learning Spark: Lightning-Fast Big Data Analysis
on Amazon
Show steps
Show steps
Show steps
- Read through the book, focusing on the chapters relevant to course topics
- Take notes and highlight important concepts
Read through Spark documentation
Show steps
Reinforce knowledge of functional programming and prepare for Spark concepts introduced in the course.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Read through the Spark SQL, DataFrames and Datasets Programming Guide
- Review the Apache Spark Programming Guide
Follow Spark Tutorials on Data Summarization
Show steps
Enhance your knowledge of data summarization techniques by exploring guided tutorials.
Show steps
Show steps
Show steps
- Search for tutorials on Spark data summarization
- Follow the steps and implement the techniques
- Experiment with different data summarization methods
One other activity
Expand to see all activities and additional details
Show all four activities
Data Munging Exercises with Spark
Show steps
Reinforce your understanding of data munging techniques by working through practical exercises.
Show steps
Show steps
Show steps
- Find datasets online and import them into Spark
- Apply data cleaning and transformation operations
- Export the transformed data in different formats
Career center
Learners who complete Beginning Data Exploration and Analysis with Apache Spark will develop knowledge and skills
that may be useful to these careers:
Data Engineer
Data Engineer
Data Engineers use their skills to build and maintain the infrastructure that supports data analysis. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Data Engineer. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Data Engineers, and the course will help you build a strong foundation for your career.
Data Scientist
Data Scientist
Data Scientists use their skills to explore and analyze data to help businesses make better decisions. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Data Scientist. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Data Scientists, and the course will help you build a strong foundation for your career.
Data Analyst
Data Analyst
Data Analysts use their skills to clean, transform, and summarize data to help businesses make better decisions. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Data Analyst. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Data Analysts, and the course will help you build a strong foundation for your career.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their skills to develop and implement mathematical models to improve business processes. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Operations Research Analyst. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Operations Research Analysts, and the course will help you build a strong foundation for your career.
Statistician
Statistician
Statisticians use their skills to collect, analyze, and interpret data. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Statistician. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Statisticians, and the course will help you build a strong foundation for your career.
Financial Analyst
Financial Analyst
Financial Analysts use their skills to analyze and interpret financial data. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Financial Analyst. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Financial Analysts, and the course will help you build a strong foundation for your career.
Risk Analyst
Risk Analyst
Risk Analysts use their skills to identify and assess risks to businesses. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Risk Analyst. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Risk Analysts, and the course will help you build a strong foundation for your career.
Data Journalist
Data Journalist
Data Journalists use their skills to collect, analyze, and present data in a way that is accessible to the public. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Data Journalist. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Data Journalists, and the course will help you build a strong foundation for your career.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their skills to develop and deploy machine learning models. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Machine Learning Engineer. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Machine Learning Engineers, and the course will help you build a strong foundation for your career.
Business Analyst
Business Analyst
Business Analysts use their skills to analyze data and identify opportunities for improvement. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Business Analyst. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Business Analysts, and the course will help you build a strong foundation for your career.
Actuary
Actuary
Actuaries use their skills to assess and manage financial risks. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Actuary. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Actuaries, and the course will help you build a strong foundation for your career.
Market Researcher
Market Researcher
Market Researchers use their skills to collect and analyze data about markets and consumers. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Market Researcher. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Market Researchers, and the course will help you build a strong foundation for your career.
Software Developer
Software Developer
Software Developers use their skills to design, develop, and maintain software applications. This course, Beginning Data Exploration and Analysis with Apache Spark, can help you develop the skills you need to be a successful Software Developer. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Software Developers, and the course will help you build a strong foundation for your career.
Data Architect
Data Architect
Data Architects use their skills to design and implement data management solutions. This course, Beginning Data Exploration and Analysis with Apache Spark, may be useful for you if you are interested in a career as a Data Architect. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Data Architects, and the course will help you build a strong foundation for your career.
Database Administrator
Database Administrator
Database Administrators use their skills to manage and maintain databases. This course, Beginning Data Exploration and Analysis with Apache Spark, may be useful for you if you are interested in a career as a Database Administrator. The course covers topics such as RDDs, functional constructs, transforming and cleaning unstructured data, summarizing data along dimensions, and modeling relationships. These skills are essential for Database Administrators, and the course will help you build a strong foundation for your career.
For more career information including salaries, visit:
OpenCourser.com/course/3sb4fj/beginning
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
Beginning Data Exploration and Analysis with Apache Spark.
Save
Provides a comprehensive overview of Apache Spark, from its core concepts to advanced topics like machine learning and graph processing. It is written by the creators of Spark, so you can be sure that you are getting the most up-to-date information.
Covers advanced topics in Apache Spark, such as machine learning, graph processing, and streaming data analysis. It great resource for anyone who wants to learn how to use Spark to solve complex data analytics problems.
Provides a comprehensive overview of data munging techniques in Python. It covers everything from basic data cleaning to advanced data transformation techniques. It great resource for anyone who wants to learn how to prepare data for analysis.
Provides a comprehensive overview of data science for business professionals. It covers everything from data collection to model deployment. It great resource for anyone who wants to learn how to use data to make better business decisions.
Provides a comprehensive introduction to Python programming for data analysis, which popular language for working with Spark.
Save
Introduces the R programming language, which is commonly used for data analysis and visualization, providing a foundation for working with Spark's R interface.
Provides the definitive guide to Apache Spark. It covers a wide range of topics, including the Spark architecture, programming model, and use cases.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3sb4fj/beginning
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Time
117 hours
Level
Introductory
Via
Pluralsight
Instructor
Swetha Kolalapudi
Language
English
Good to know
Examines data preparation, a vital skill for both data exploration and modeling
Taught by industry experts who are recognized for their work in data science
Emphasizes hands-on practice with Apache Spark, a popular tool for data preparation
Develops skills in transforming, cleaning, and summarizing data, which are essential for data analysis
Provides a comprehensive overview of data preparation, covering key concepts and techniques
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