Databricks Certified Associate Developer -Spark 3.0

🎓 Master Databricks Certified Associate Developer - Spark 3.0 with Python! 🚀

Course Overview:

Databricks Certified Associate Developer  Training course.

Are you preparing for the Databricks certified associate developer for Apache Spark certification exam? Look no further! This comprehensive course is designed to provide you with the necessary knowledge and hands-on practice to ace the exam. With over 60 coding questions and real-time datasets, you'll be well on your way to becoming a certified expert.

What You'll Learn:

👨‍💻 Practice Exercises on the Go: Dive into over 60 coding questions that can be executed on the Databricks community edition, ensuring you get real-world practice and experience.

🤔 Understanding & Applying DataFrame APIs: Learn to understand and apply the DataFrame API using two real-time datasets. These datasets are designed to give you a practical understanding of how data is processed in Spark.

🎥 Video Lessons: With over 200 minutes of video lessons, you'll receive in-depth explanations and guidance from our expert instructor.

Key Features of the Course:

📚 Interactive Learning: Write code on the go and see your work in action with immediate feedback. This interactive approach ensures that you learn by doing, which is crucial for mastering Spark.

🎨 Creative Visualisation: Understand complex architecture concepts like never before with creative visualisations that make learning more engaging and effective.

⏱ Extensive Practice Sessions: Benefit from over 120 minutes of practice code, where you can apply your skills and reinforce your knowledge.

Module Breakdown:

🔹 SparkSession

• Understanding the SparkSession object
• Working with DataFrames in a distributed environment

🔹 Dataframe Writer, Reader

• Efficiently reading from and writing to various sources
• Managing data inputs and outputs with ease

🔹 Select, Filter, Where, Drop, Dropduplicates

• Mastering data manipulation and filtering
• Ensuring data quality and relevance

🔹 SelectExpr, WithColumn, Take, First

• Advanced selection techniques
• Manipulating columns and rows for targeted analysis

🔹 Aggregations, Sort, Groupby, Orderby

• Performing computations on datasets
• Sorting and grouping data for better insights

🔹 Date and Time

• Handling temporal data with precision
• Working with time-series data effectively

🔹 UDF including lambda

• Creating custom functions for specific tasks
• Using lambda expressions to simplify code

🔹 Explode, Split

• Transforming data structures for analysis
• Pivoting data from nested arrays or maps into a more tabular form

🔹 Persist, Cache, Unpersist

• Managing data caching and persistence strategies
• Optimizing performance through efficient memory usage

Architecture Concepts:

🔸 Modes of Deployment

• Visualizing the different deployment modes for clarity

🔸 Partition

• Understanding data partitioning concepts with visual aids

🔸 Spark UI

• Interpreting the Spark User Interface to monitor job performance

🔸 Jobs, Stages, Tasks

• Breaking down complex processes into manageable components

🔸 Wide and Narrow Transformations

• Learning the differences and implications of various transformations

🔸 Physical Logical Plans, AQE, DPP

• Exploring the execution plans and understanding how queries are optimized

🔸 Data Locality

• Understanding the importance of data locality in distributed computing

Your Learning Advantage:

This course is meticulously designed by Kanchana Selvakumar, an expert instructor with a passion for making complex topics accessible and engaging. With this course, you'll have all the tools you need to prepare for the Databricks Associate Developer Certification exam on Spark 3.0 in Python.

📝 Important Note: This course is created by Kanchana Selvakumar and is an independent resource to aid your learning journey. It is not associated with or endorsed by Databricks, Inc. The course is designed to complement your study and provide additional practice and insights as you prepare for the certification exam.

Get ready to immerse yourself in a world of big data processing with Spark 3.0 and conquer the Databricks certified associate developer for Apache Spark certification!