Apache Spark - PySpark
PySpark
23
students
20 hours
content
Jun 2023
last update
$44.99
regular price
What you will learn
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
Why take this course?
🌟 Apache Spark - PySpark Course: Harness the Power of Big Data with Python 🌟
Course Overview:
Dive into the world of Big Data with our comprehensive and hands-on Apache Spark - PySpark Course. This course is designed to take you from a beginner to an advanced user of Apache Spark using Python, one of the most influential programming languages in the data science domain.
Why Choose PySpark? 🚀
- Industry Demand: Top tech giants like Google, Facebook, Netflix, Airbnb, Amazon, and NASA are harnessing the power of Apache Spark for their Big Data needs.
- Performance: Up to 100 times faster than Hadoop MapReduce, making it a key tool for large-scale data processing.
- Market Value: Mastering Spark, especially with its PySpark framework, makes you a highly sought-after professional in the job market.
What You'll Learn:
Apache Spark Fundamentals:
- Understand the Spark architecture and its ecosystem.
- Get to grips with Spark's Data Sources API and DataFrame API.
Data Manipulation & Analysis:
- Efficiently ingest data from CSVs, JSON files, and more into your data lake as parquet files or tables.
- Execute crucial PySpark transformations such as filtering, joining, aggregations, and groupBy operations to manipulate and analyze data effectively.
DataFrame Operations:
- Learn how to create local and temporary views to organize your data within PySpark more efficiently.
- Master PySpark DataFrames for advanced data analysis tasks.
Advanced Topics:
- Explore Spark RDDs (Resilient Distributed Datasets) as the foundation of Spark's distributed data processing capabilities.
- Understand the use of DataFrame transformations and actions to perform complex data operations.
Key Features of the Course:
- Interactive Learning: Engage with over 150 tutorial videos that cover all aspects of PySpark.
- Real-World Scenarios: Apply your knowledge through practical examples and case studies.
- Expert Guidance: Learn from experienced instructors who are experts in Big Data technologies.
- Hands-On Projects: Gain hands-on experience by working on real-world projects that showcase PySpark's capabilities.
- Community Support: Join a community of learners and professionals to exchange knowledge, share experiences, and grow together.
Course Highlights:
- Comprehensive Curriculum: A complete guide from Spark architecture to transformations, ensuring you understand all the critical aspects of PySpark.
- Flexible Learning: Access the course material anytime, anywhere, fitting learning into your schedule.
- Skill Advancement: Transition from a PySpark beginner to an advanced developer with the skills to tackle real-world Big Data challenges.
- Career Growth: Position yourself as a valuable asset in the job market by mastering one of the most critical technologies for data processing and analysis.
Don't miss this opportunity to become proficient in PySpark and unlock the potential of Big Data! Enroll now and take the first step towards a rewarding career in data science and analytics. 📊✨
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udemy ID
02/06/2023
course created date
05/07/2023
course indexed date
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