The Databricks Certified Associate Developer for Apache Spark is one of the most challenging exams. It's great at assessing how well you understand not just Data Frame APIs, but also how you make use of them effectively as part of implementing Data Engineering Solutions, which makes Databricks Associate certification incredibly valuable to have and pass. Rest assured, I've passed it myself with a score of 90%.
This is going to be a long journey, but passing the Databricks Certified Associate Developer for Apache Spark exam will be worth it!
This Databricks Certified Associate Developer for Apache Spark is different from the other ones you'll find on Udemy. You are the better judge.
First, we will make sure we have the right environment based on Databricks to practice. If you do not have the environment don't worry, you will be guided to set up the environment using Azure
Once the environment is ready you will be guided to upload the material and also data sets for practice
It covers in-depth all the new topics on the Databricks Certified Associate Developer for Apache Spark exam using Pyspark.
It's packed with practical knowledge on how to use Pyspark Data Frame APIs inside and out as a Data Engineer using Databricks Platform
It teaches you how to prepare for the Databricks exam AND how to prepare for the real world leveraging Pyspark Data Frame APIs.
It's a logical progression of topics, not a laundry list of random services
It's fast-paced and precise to the point
All the material will be made available as a Databricks Archive. Just upload it into your platform and start using it
Concretely, here's what we'll learn to pass the Databricks Certified Associate Developer for Apache Spark exam:
Setup of Databricks Environment using Azure
The Databricks CLI and important commands to interact with DBFS. It will be used to quickly set up the data for practice.
In-Depth Data Frame APIs using Pyspark that are relevant for the exam.
All Important and Commonly used Data Frame APIs for selecting, renaming, and manipulating columns leveraging Pyspark
Pyspark Data Frame APIs for filtering, dropping, sorting, and aggregating rows
Pyspark Data Frame APIs for joining, reading, writing, and partitioning DataFrames
Working with UDFs using Pyspark and Spark SQLFunctions
Apache Spark Architectural Concepts which are very important for the exam
Adaptive Query Execution which been introduced in recent times.
Tips and Key Strategies to ROCK the exam
This Databricks Certified Associate Developer for Apache Spark course is full of opportunities to apply your knowledge:
There are many hands-on lectures in every section
There's a Databricks Certified Associate Developer for Apache Spark tips and strategies using Mock Test provided by Databricks at the end of the course
We'll be using the Databricks single node cluster most of the time. It will cost you some money based on your usage.
I'll be showing you how to go beyond the Single Node for some sections (you know... the real world!)
