Apache Spark 3 for Data Engineering & Analytics with Python

🎓 Master Apache Spark for Data Engineering & Analytics with Python!

🚀 Course Title: Apache Spark 3 for Data Engineering & Analytics with Python

👩‍💻 Course Description:

Are you ready to unlock the full potential of Big Data with Apache Spark 3.0.1 and Python? Dive into the world of Data Engineering and Analytics by mastering PySpark, and learn how to leverage the power of Databricks to run your data processing workloads efficiently!

🎯 Key Objectives:

• 🌟 Understand Spark Architecture and its execution model.
• Master Spark Transformations with both DataFrame and RDD APIs.
• 📊 Learn to perform complex Data Analytics and generate insightful visualizations.
• Gain proficiency in using PySpark within the Jupyter ecosystem (Notebook & Lab).
• 🛠️ Get hands-on experience with Databricks, SQL, Pandas, Matplotlib, and Seaborn.

⚒️ Course Projects:

1. Sales Data Analysis: Work with real-world datasets to extract meaningful insights about sales orders by region and country.
2. Fahrenheit to Centigrade Conversion: Implement temperature conversion logic across distributed data using Spark's RDD API.
3. XYZ Research Data Analysis: Process and analyze research data, exploring patterns over time with Spark's RDD transformations.
4. Sales Analytics: Clean, structure, and analyze sales data to generate visualizations that provide actionable business insights.

📅 Course Syllabus:

1. Python Essentials: Refresh your Python skills to ensure you're up-to-speed with the programming language used for data processing.
2. Introduction to Spark: Understand the core concepts of Apache Spark and its ecosystem.
3. Spark SQL: Learn how to work with structured data using DataFrames.
4. Spark Streaming: Discover real-time data processing capabilities (optional, based on course progress).
5. Machine Learning with MLlib: Explore the basics of building machine learning models on Spark (optional, based on course progress).
6. Data Analysis and Visualization: Utilize Matplotlib and Seaborn to create compelling visualizations of your data.
7. Databricks Workshop: Get hands-on experience with the Databricks platform for cloud-based Spark workloads.
8. Final Project: Apply all the concepts learned throughout the course to a comprehensive, real-world dataset.

👨‍🏫 Who is this course for?

This course is designed for:

• Data Analysts who want to leverage Spark for large-scale data processing.
• Data Engineers looking to enhance their skill set with PySpark and Databricks.
• Aspiring Data Scientists aiming to build a strong foundation in distributed data processing and analysis.
• Anyone interested in understanding the capabilities of Apache Spark for handling Big Data challenges.

🎓 Why Join David Charles Academy?

• Learn from industry experts with real-world experience.
• Interactive and practical learning approach with hands-on projects.
• Exclusive access to a supportive community for peer collaboration.
• Lifetime access to course materials and updates.
• Engage with case studies and examples that mirror real-world scenarios.

Embark on your journey to becoming a Spark pro today! 🚀✨

Enroll now and transform the way you handle data engineering and analytics with Apache Spark and Python at Apache Spark 3 for Data Engineering & Analytics with Python! 🌟