Pyspark Foundation for Data Engineering | Beginners
Learn PySpark and become a skilled Data Engineer! This course focuses on practical applications, bridging the gap between theory and practice. Gain hands-on experience and learn essential functions used in PySpark scripting. With Spark’s ability to analyze huge data sets up to 100x faster than Hadoop MapReduce, this skill is in high demand. Whether you’re a beginner or experienced, this course is designed for anyone interested in data engineering. Start your journey today!
What you’ll learn
- Fundamentals of PySpark
- Hands on experience in PySpark
- Understanding of data using PySpark
- Performing various operations on DataFrame
This course will prepare you for a real world Data Engineer role (basics)!
Learn to code PySpark like a real world developer. Here our major focus will be on Practical applications of PySpark and bridge the gap between academic knowledge and practical skill.
In this course we will get to know and apply few of the most essential and basic functions in PySpark, that are used frequently in scripting for any project based on PySpark.
About PySpark:
Learn the latest Big Data Technology – Spark! And learn to use it with one of the most popular programming languages, Python!
One of the most valuable technology skills is the ability to analyze huge data sets, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Spark! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Spark to solve their big data problems!
Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!
What you will learn :
SparkSession and imports
Spark DataFrame and its characteristics
Syntax and example
Print results
Understanding the data
Number of records
Columns in dataFrame
Describe a DataFrame
Schema of a DataFrame
Create a new column
Arithmetic operations on Data
Change column data type
Create a column with integer as constant
Apply what we know
Rounding of digits
Sorting operation
Drop columns
Rename columns
Create a column with string as constant
Conditional Statements
Changing case of a column
Filter operations
Grouping and aggregations
Prerequisites :
Some basic programming skills (Not Mandatory)
Will to implement theoretical knowledge in practical.
Who this course is for:
Beginners who want to learn Big Data or experienced people who want to transition to a Big Data role
Big data beginners who want to learn how to code in the real world
Aspiring candidates for data engineering role
Who this course is for:
- Anyone with interest in Data engineering
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