Databricks Certified Associate Developer - Apache Spark (Udemy.com)

Always a great experience and learning with Durga Sir's courses, and I wanted to share some exciting news here. I recently took the Databricks Certified Associate Developer for Apache Spark 3.0 - Python exam on October 20, 2024, and I passed with a 90% score! Your guidance and the foundational skills you taught me in Spark and SQL during my time at Clairvoyant have been instrumental in my success. The feedback I received from you back then was incredibly motivating, and now, thanks to your excellent courses and support, I’ve achieved this certification with confidence. Thank you so much for all your help and for being such an amazing mentor!

Thank you Durga.. This course helped me clear the certifications. A few recommendations. 1. UDF related topics can have more examples for both SQL and non SQL version. 2. Spark architecture can be covered in detail from exam perspective. 3. Some details about execution framework would be better which involves logical plan, physical plan, cost optimizations etc.

Excellent resource for Databaricks Apache Spark Developer Exam. Have managed to go through all the topics on Spark including Architecture. All the topics were covered with examples in Durga's style and hence it was easy for me to follow along. This course will definitely help people taking the exam as well as in their projects . Looking forward to see updated version of this course soon as per the lastest syllabus from Databricks :-) .

The course is heavily focused on the Dataframe API which forms upto 72% of the certification exam. I would recommend you to take this course for that, however the course has minimal content on the Spark Architecture Concepts which forms about the other 28%(it covers maybe only 10% of that in this course). Moveover, few methods like sample() and first() are missing. Cache() and persist() do not have a video lesson here although I got 3-4 question on that concept alone during the actual exam. These functions are must do as they are present in the practice test and were there in actual exam too.

I will give my honest review. The course content is good and covers all the things related to the certification. Pros: -Everything is covered as a part of Certifications. -Things will stick to your mind as they are covered multiple times. -Lots of scenario based questions are covered. Cons: -The durations of course is too lengthy and repetative which makes it quite boring very often and reduces the interest of learner. -I will give one eg. Reading file and reading file with delimeter they both can be covered in a same lecture but here there are two separate lecture almost same which isnt necessary. -Explanation of similar topic again and again is also not required. -The UDF section could have of longer duration as it very important and it tests ones coding knowledge but this is very short.

The course is good overall. But due to the repetition of many things the course is extended to many hours. Instead, the repetition could be in form of some projects. Edit: The course lacks the theoritical concepts that needs to be covered for the exam like shared variables, mode of execution, memory handling, etc which covers 10-20 ques in certification. I had to read them from outside the course. But for DF API this course is good.

I have achieved the databricks pyspark certification by going through this course. Thnk you Durga Sir. Definitely this course will be helpful for clearing the exam. Now I am planning for preparing "Databricks Certified Data Engineer Associate". Please let me know if there are any materials to prepare for this exam.

After completing this course videos and doing the practicals alongside, I was able to score 53% in my first practice test from Florian Roscheck. Then I had to read the Learning Spark edition 2.0 book. And then I had to do multiple rounds of the practice tests to clear the exam. However the coverage of different syntaxes and ways to do the same thing like filtering using Python construct, SQL construct, using column name as string, using column names in dataframe format etc., is really commendable in this course. This helped in the exam a lot. Architectural concepts could've been explained a bit more. TLDR, this course can be used for the 43/60 questions which targets the applications of Spark APIs whereas to attend the remaining 17, you must go through either the Spark Definitive Guide book or the Learning Spark 2nd Edition book and take multiple practice tests. One more feedback is the redundant statements during in the video could be removed, this probably is the author's way of emphasising things, but that was a little time consuming overall.

Overall, the course was average. Pros: 1. It focused well on the API's part and that is good. That is major portion of the real exam. Cons: 1. Should have better content in architecture part. 2. Garbage collection related topic is missing. There are couple of questions related to that also in the exam . 3. Should have explained the answers in the practice paper. 4. Should have additional practice papers for practice.

The instructor has good knowledge about spark and the method is also very simple. It's still lacking practice questions, summaries of the sections, one grand test at the end, some design discussion about when which method should be used. Since the exam is focused on spark and not data bricks environment, the course content should be based on Jupyter notebooks which can be run locally and datasets should be used which are available \. publicly.