Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
6 Hour(s) 43 Minute(s)
Language
English
Taught by
Gustavo R Santos
Certificate
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
Course Overview
From Beginner to Pro: Learn Key Data Processing Skills and Machine Learning with PySpark in Databricks
Explore the world of big data analytics with our comprehensive course, 'Mastering Data Processing with PySpark in Databricks.'
In this course, we equip you with the practical skills and knowledge required to navigate the complexities of PySpark and Databricks, two industry-leading tools for efficient data processing, analysis, and the extraction of valuable insights from large datasets.
As technology evolves, the access to Big Data is easier each day, making professionals with the skill to process and extract insights from those large datasets wanted by the Big Tech Companies. Learning how to use Databricks will upskill you to be that wanted professional!
Gain practical skills in PySpark and Databricks to efficiently process, analyze, and extract valuable insights from vast datasets. Discover data processing, transformation, query optimization, and machine learning techniques from the basic.
In the age of data-driven decision-making, understanding PySpark in Databricks is not just an advantage but a necessity. By enrolling in this course, you'll be poised to take your data analytics capabilities to the next level, making you a sought-after professional in a data-centric world.
Join us and take the first step towards optimizing your data processing skills.
By the end of this course, you will be ready to add PySpark to your resume!
Enroll today to enhance your data analytics capabilities and boost your career in the data-driven world!
Course Content
- 8 section(s)
- 56 lecture(s)
- Section 1 Introduction
- Section 2 Getting Started with PySpark and Databricks
- Section 3 Basics of PySpark
- Section 4 Data Wrangling With PySpark
- Section 5 Query Optimization
- Section 6 Databricks SQL
- Section 7 Machine Learning with PySpark
- Section 8 Conclusion
What You’ll Learn
- Understand the fundamental concepts of PySpark and Databricks and their significance in the world of big data analytics.
- Learn how to set up and configure your Databricks environment, including creating an account and managing clusters.
- Explore PySpark's data structures, DataFrames, and Datasets, and learn to create and work with structured data.
- Master the essential data manipulation techniques in PySpark, including selecting, filtering, transforming, aggregating, and handling missing data.
- Discover how to use PySpark SQL for structured queries, compare it with DataFrame operations, and understand when to use each.
- Learn the essentials of ETL (Extract, Transform, Load) processes with PySpark, including reading and writing data, data cleaning, and partitioning.
- Gain an overview of PySpark's MLlib library and different types of machine learning tasks.
- Dive into feature engineering, model selection, evaluation, and hyperparameter tuning for building robust machine learning models using PySpark.
- Discover performance optimization techniques in PySpark, including data caching, broadcast variables, and query optimization.
- Explore strategies for scaling PySpark workloads, including best practices for handling large datasets.
Skills covered in this course
Reviews
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OObehi
being quite comprehensive to get a grasp of using databricks . so happy with how this has taught me about the functions in pyspark and how to make use of them
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OOmkar Shelkikar
Very informative course with clear, detailed coverage of the topics. Thank you
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SSridhar S Pai
Excellent ! Please attach source code with each lesson.
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AAbhisek Panigrahi
Yes it is good
