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Spark architecture, the Data Sources API, and the DataFrame API.
Updated on Sep, 2026
Programming, Data Science, Big Data
Training 5 or more people ?
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Learn the latest Big Data technology, Apache Spark, and its collaboration with Python, one of the most popular programming languages. This comprehensive course covers everything from the basics to advanced levels of data analysis.
Apache Spark is a highly sought-after technology in the Big Data analytics industry, with top companies like Google, Facebook, Netflix, Airbnb, Amazon, and NASA utilizing it to solve their data challenges. Its superior performance, up to 100 times faster than Hadoop MapReduce, has led to a surge in demand for professionals skilled in Spark.
By mastering Spark and its DataFrame framework, which is relatively new and in high demand, you'll position yourself as a highly knowledgeable candidate in the job market.
Throughout the course, you'll work with PySpark for data analysis, exploring Spark RDDs, DataFrames, and the various transformations and actions you can perform on data using them.
In addition, the course covers essential topics such as Spark architecture, the Data Sources API, and the DataFrame API. You'll learn how to efficiently ingest CSV files, as well as simple and complex JSON files, into the data lake as parquet files or tables.
The course also delves into important PySpark transformations, including filtering, joining, simple aggregations, groupBy operations. These transformations enable you to manipulate and analyze data effectively within PySpark.
Furthermore, you'll gain expertise in creating local and temporary views, allowing you to organize and work with data more efficiently in PySpark.
With a comprehensive coverage of topics ranging from Spark architecture to transformations, and view creation, this course equips you with the necessary skills to become a proficient PySpark Developer.
With over 150 concise tutorial videos, this course provides a comprehensive understanding of the concepts and methodologies of PySpark. Whether you're aiming to become a PySpark Developer or enhance your Big Data skills, this course is a must-have.
Learners will understand the Apache Spark Foundation and Spark Architecture
How Apache Spark can be used in Data Engineering and Data Processing
Working with different Data Sources and types of Datasets
Working with Data Frames and PySpark
Use Python and Spark together to analyze Big Data
Learner will understand about PySpark RDD
PySpark DataFrames Actions and Transformation
Use of different file formats such as Parquet, JSON, CSV etc in building Data Engineering Pipelines
Basic Knowledge of Python and SQL are necessary
Having a reliable internet connection and a strong desire to learn are essential prerequisites.
Check out the detailed breakdown of what’s inside the course
Practitioners of Big Data and related technologies
Team has over two decades of experience in the industry
Passionate in dealing with data and providing IT solutions
We believe in continuous learning
Enjoy spreading the knowledge through Training, Workshops, Internships and Projects assignments
Our Solution provides support and expertise advice that is presented for consideration and decision-making in Big Data Technologies
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