PySpark Essentials for Data Scientists (Big Data + Python) (Udemy.com)

I have been trying to learn pyspark, but most of the material makes you believe that there is something mysterious about it, until I started with this course where the comparison between python and pyspark shows the why and makes the mystery to become something simple to understand. Great course.

I found it hard as a beginner to follow the course. Many things regarding the workflow and approach were not explained but rather just being coded. Some times it felt like just showing code. There is a lot of supporting material provided but i firmly believe that some time of the course showing code could be replaced by providing explanations. (i.e lot of spark documentation links but not a single video going on it and showing how to look). Still very good course!!!

Good: I like the teaching, feel homey also the Q&A is pretty active so far if you're really a beginner in Python, you should watch a few videos first about Python and Pandas in freecodecamp then go back here, you'll probably have a smoother journey, if you already have that programming mindset before you try this course. Also don't update to Java 8 291. It doesn't go well with the latest Pyspark version as of June 22 2021, so probably stay at 281.

I have completed the Dataframe Essentials sections that are needed for my job at the present moment. The course is fantastic and because of it, I got quickly familiar with the concepts needed to do my job and adjust in no time to Apache Spark framework. Soon, I will also watch the MLlib sections and update the rating accordingly.

The course is incredibly comprehensive and after finishing most of it, I feel like I can use PySpark really well. I especially enjoyed the projects - they were interesting and quite challenging. The instructor is not only knowledgeable, but also likable and unpretentious. Overall, a great course.

I just finished going through most of this course. I knew I was on a good start with this course when I could install and work with PySpark without any issues following the video. I think Layla has put in a lot of work in this course which clearly shows. Well done. One note of caution though. This is not a beginner's course unless you are well motivated and resourceful. I have experience with Both Spark and Machine Learning (Sci-kit Learn, NLTK), so I was fine. People who are rank beginners will do well to supplement this course with other courses. This course is well suited for intermediate to advanced students.

This course by Laila is the most exhaustive course that covers all aspects of machine Learning in PySpark. The course is very well organized: starting from fundamentals to advance concepts and then coding exercises. I learnt a lot in this course. The projects are very well designed and practical. She has provided functions which are very useful and can be used as such in your company’s projects. The course got a bit fast paced during the ML part and lots of concepts were covered in short videos. I had to look for additional resources to understand them completely. That happens with courses even in the college. Another thing worth mentioning is that she was very prompt in responding to my questions. Overall, it is a great course, and I would recommend it to anyone who wants to learn machine learning using PySpark.

This has been a wonderful class. The PySpark piece has been excellent and allowed me to review my Data Science group's DataBricks notebooks, and clean them up significantly to become nightly "production" runs. The material is complete, concise and very well presented. I am skipping over the ML stuff for now as I don't have a need for this at the moment but look forward to getting back to them as soon as possible. Thanks!

The course starts off extremely well and contains a great collection of useful tips, tricks, and functions. The lecture quality decays rather rapidly and by the time one is onto the machine learning portion of the course one would be better served by standing over the shoulder of a data scientist and watch them code instead. Tonnes of unintuitive pyspark syntax is glossed over with no attempt at explanation, typos are plentiful and the encoding choices are quite frankly just wrong in places which would lead to some fairly devastating losses in industry. If you are happy to pay to have kaggle solutions verbalised for you with no explanation then this is the course for you, else if you came here to learn PySpark, you will probably be hard pressed to learn any of the machine learning portion.

The instructor is very easy to listen to. I also like the design of the course. It's much more practical than other courses that just go through each algorithm individually and don't show how to compare them. Actual data scientists usually compare several algorithms against each other and that is exactly how the instructor approaches the ML portion of the course. You can tell she (YES SHE! - also great) has a lot of experience and designed the course very thoughtfully. Hand clap for this one! I hope she adds more lectures in the future about using MLflow... that part was awesome!