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Updated in [February 21st, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)

Tutorial 1-Pyspark With Python-Pyspark Introduction and Installation.
Tutorial 2-Pyspark With Python-Pyspark DataFrames- Part 1.
Tutorial 3- Pyspark With Python-Pyspark DataFrames- Handling Missing Values.
Tutorial 4- Pyspark With Python-Pyspark DataFrames- Filter Operations.
Tutorial 5- Pyspark With Python-GroupBy And Aggregate Functions.
Tutorial 6- Pyspark With Python-Introduction To Pyspark Mlib.
Tutorial 26- Linear Regression Indepth Maths Intuition- Data Science.
Tutorial 7- Pyspark With Python|Introduction To Databricks.
Tutorial 8- Pyspark Multiple Linear Regression Implementation In Databricks.
What can you get from this course?
We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
This course will provide learners with a comprehensive understanding of the features of Spark with Python. Participants will acquire skills in installing the Pyspark environment, working with DataFrames to handle missing values and perform filter operations, using GroupBy and aggregate functions, and utilising Pyspark’s Machine Learning Library (Mlib). Additionally, learners will gain knowledge in Linear Regression and its implementation in Databricks. Upon completion of the course, participants will have a solid foundation on Pyspark and its applications in data science.

How does this course contribute to professional growth?
This course provides a comprehensive understanding of the features of Spark with Python. It covers topics such as installing the Pyspark environment, working with DataFrames, using GroupBy and aggregate functions, and utilising Pyspark’s Machine Learning Library (Mlib). Additionally, the course provides an in-depth look at Linear Regression and its implementation in Databricks. Through this course, professionals can gain the necessary skills to effectively use Pyspark and its applications in data science, thus contributing to their professional growth.

Is this course suitable for preparing further education?
This course is suitable for preparing further education as it provides a solid foundation on Pyspark and its applications in data science.