Scala and Spark for Big Data and Machine Learning (Udemy.com)

Overall a nice experience. Maybe some of the videos related to installation and setup using Mac computer needs to be updated, since i had a tough time surfing other internet resource to complete my installation.On the contents, it was easy to understand & also provided links & resources incase you need a wider depth of knowledge. Maybe the project exercise courses could be dealt more effectively explaining on the dataset, its mission or problem statement & then a walkthrough on the codes. Nevertheless, worth a course to gain some basic knowledge.

It's a good course to expose yourself to Scala and Spark. It provides a good kick start so you have a general idea on what to do, where to go to get the information you need to complete the task. I just wish there was more about Big Data, at least demonstrate a *full cycle* example to show how it's like sending data to the cluster, running the machine learning model on the cluster, and retrieving the result. Overall, good course. Recommended.

It was good and well explained. I'm really new to all of these topics but I do feel much more knowledgeable on the subject. I will definitely be repeating the course to further enhance my understanding. What would be great is some suggestions for some independent projects we can do after the course for beginners so that we can practise what we have learnt otherwise the course was great and I would highly recommend.

Thanks again Jose, I really loved the course. I've learned a lot about Big Data and using Spark and the Scala programming language to create Machine Learning models. But more over, I've learned how to setup a multi-node ML cluster environment on Databricks and AWS.

This is only my third or fourth programming language and he was among the best instructors; I took VB, taught myself php; took SQL and Bi as well previously. There are probably details about the format of the course and content that as a non-expert I cannot gauge as to how comprehensive the course is or how to grade the course. However, I would say it is a four and a half to five star class - perhaps it is perfectly taught though!

The course is well structured and targeted to give you the base knowledge on how to use scala and spark to solve Big Data and ML problems. I feel like I will need to do another course in algebra and calculus to get a more in depth knowledge on the different ML algorithms that exist and when and how to use them.

This course gives a good overview of spark for Big data, basic scala script coding , spark UI in zeppelin and databricks notebooks, and machine learning. Wish there were more sessions explained on using the different MLlib machine learning algorithms in terms of model prediction and evaluation. Recommend to people who wants to get a basic understanding of spark in big data and machine learning fields.

Very good content, well presented and explained. For the Machine Learning parts though, the output generated and Why-and-When to use the output is not very well explained. It would be great if after you explained the exercise solutions that you could help your students understand what the data generated actually means in a real world situation. Generating a "-1.112121" is all well and good, but what is it telling me with relation to my data? THAT is what is missing from this course IMHO. Otherwise its a very very good course. Thanks Jose

I really liked the course from the point of view of learning core Apache Spark concepts without having to dive too deep into statistical learning (although that is very much encouraged). Before this course, I did manage to learn some of the core Spark concepts. However, the effort was too fragmented given that most of the books available on the topic discussed concepts in isolation without following it up with a real-world- like example. This course begins with the theoretical concept of walking through Spark documentation, followed by working with sample data sets to demonstrate the concept discussed. This helped complete the picture for me as far as Spark as a "technology" is concerned. However, the course stops at the edge of technology-business border, although there are several mentions of real world business scenarios throughout this course. This is great for technologists to grasp. But if I've to translate this into terms in order to explain this to the business, that still remains a challenge. Imagine explaining Root Mean Squared Error to my manager! But being business-savvy isn't the intention of this course. That is one reason, I've signed up for a Data Visualization classes (also instructed by Jose) with the intention of taking what I've learned in this course and make it more practical. Overall, this is an awesome course! I give it 4 stars because I'm yet to understand the full implications of topics such as Model Evaluations.

This is THE BEST COURSE I have taken on UDEMY in Spark and Big Data Analytics. I would recommend this for anyone interested in learning Spark, Scala and using them for Machine Learning. Jose Portilla did an excellent job of teaching this class and by pointing to the right resources on apache website and pointing to the chapters to refer to in the other external resources. I greatly enjoyed the teaching style of Jose. I am looking forward to enroll in other courses offered by him in future. Thanks.