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I have been using CloudxLab for last 3 months for learning Hadoop and Spark, and I can vouch for it.

It’s a platform where you can learn from the tutorial videos and then practice in the lab they provide on cloud. The study materials are well-planned and I would be lying if I say its not great.
The video lectures explains the technical stuffs in very simple ways which makes it easier to grasp the concepts. Also, the customer service is great.
So, thumbs up for the team associated with CloudxLab.
To conclude my views, I would just say that, if you are willing to learn Big Data related stuff, I strongly recommend CloudxLab.

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This is one of the best-designed course, very informative and well paced. The killer feature of machine/deep learning coursed from CloudxLab is the live session with access to labs for hands-on practices! With that, it becomes easy following any discourse, even if one misses the live sessions(Read that as me!). Sandeep(course instructor) has loads of patience and his way of explaining things are just remarkable. I might have better comments to add here, once I learn more! Great Jobs guys!

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I think I can give some points on this . Am using cloudxlab for more than an year… my intention is for continuous learning.
For Students and technology change professionals :
In General Big data hadoop, (a) you can learn on your personal PC, but for that the minimum configuration of 12 GB Ram with good processing speed, still when you execute jobs it will take more time for processing jobs as it will be acting as single node.(b) If you try to install each and every components, it will take hell a lot of admin work , and some thing happens , you have to invest lot of time for debugging.
The main advantage of using cloudxlab,
a) Get 6 node production cluster with all installed components, just getting user and password, you can start working on it.
b) You have almost all the access.
c) Good amount of components installed.
d) You can play around with each of them with 5gb of test data.
e) So far I didnt experience any down time.
f) You can Practice in your college lab, on free time.
g) Good email support on technical perspective.
h) They have couple of test data, I use my own.
i) vi and nano editor supported.
j) Some of the components which I remember are HDFS,MapReduce2, YARN, Tez, ZooKeeper,Falcon,Storm, Kafka,Spark,Jupyter Notebook, Hive,HBase, Pig, Sqoop, Oozie, Flume,Accumulo,Ambari.

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I have been using CloudxLab for sometime and based on my usage experience I can say that they have done a fabulous job.

The first problem anyone faces while learning Big Data technologies is running the VMs on his/her laptop. VMs require a good amount of dedicated RAM and so most of the times we end up spending in hardware upgrade. But even after an upgrade the requirement of a cluster is never met. The examples we try alaways runs on a single node setup.

To try this on a production like cluster setup we have something like AWS, but there is a good amount of cost involved in that. Also, they keep the credit card details with them which I feel not everyone feels safe to share.

And this is where I feel CloudxLab seems to be a better bet.Their pricing is very much competitive compared to the other offerings and also it doesn’t require any specific hardware requirement. Any desktop/laptop with any configuration which has connectivity to net is good for getting started.

No need to do any setups.Their clusters are fully loaded with all the latest Big Data packages.You can access them from anywhere.

The only thing you need to concentrate is on your learning :)

Hope this helps to anyone who is looking for an option beyond VMs.

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It has been a wonderful learning experience with CXL. This is one of the courses that will probably stay with me for a significant amount of time. The platform provides a unique opportunity to try hands-on simultaneously with the coursework in an almost real-life coding example. Besides, learning to use algebra, tech system and Git is a good refresher for anyone planning to start or stay in technology. The course covers the depth and breadth of ML topics. I specifically like the MNIST example and the depth to which it goes in explaining each and every line of code. Would definitely recommend the instructor-led course.