PySpark for Data Scientists
Welcome to the “PySpark for Data Scientists” course! This comprehensive program is designed to equip you with essential knowledge and skills to harness PySpark for big data analytics. Whether you are new to data science or looking to enhance your expertise, this course covers everything required to build, optimize, and analyze large-scale datasets effectively.
What you’ll learn
- Foundations of PySpark: Gain a solid understanding of fundamental PySpark concepts and principles..
- Data Manipulation Techniques: Explore key data manipulation techniques such as dataframes, RDDs, and SQL queries in PySpark..
- Distributed Data Processing: Learn techniques for distributed data processing and optimisation..
- Data Preparation: Understand and implement strategies for data cleaning and transformation..
Course Content
- Introduction to Big Data –> 2 lectures • 48min.
- Introduction tp RDD and Spark –> 9 lectures • 2hr 56min.
- Data Frame & Sparke shell –> 3 lectures • 1hr.
- Quiz –> 0 lectures • 0min.
Requirements
Welcome to the “PySpark for Data Scientists” course! This comprehensive program is designed to equip you with essential knowledge and skills to harness PySpark for big data analytics. Whether you are new to data science or looking to enhance your expertise, this course covers everything required to build, optimize, and analyze large-scale datasets effectively.
Throughout the course, you will explore a wide range of PySpark concepts and practical applications, focusing on distributed data processing and large-scale data analysis. You’ll begin with the fundamental principles of PySpark and its ecosystem, covering crucial topics such as data manipulation techniques, including DataFrames and RDDs, as well as SQL queries for data transformation. Practical applications of distributed computing will help optimize your data processing workflows. In addition to foundational concepts, the course delves into advanced topics, including data preparation strategies for cleaning and transforming datasets and utilizing PySpark’s capabilities for real-time data processing.
By the end of this course, you will be proficient in implementing PySpark techniques to tackle complex data challenges. You will be able to extract meaningful insights from large datasets and apply your skills to real-world scenarios across various data-driven fields. Get ready to unlock limitless opportunities in big data analytics!