Is big data easy to learn?
I’d say that most big data jobs have a ton of technical requirements which might present a couple of challenges when it comes to learning big data, than when learning say web development.
However, with the right big data learning resources and tools, you can easily get a firm handle on a variety of industry languages and applications in a record time.
In this article we are going to look at the best big data courses and certifications online to get you started with a career in big data.
Once you take these courses you’ll be able to detect trends and spot patterns in data that you can use for business benefit.
Some of the skills that you’ll pick up include data engineering and machine learning using tools like Hadoop, Spark and Python, among others.
Let’s get started.
Now let’s get this ship off the shore and look deeper into these courses.
In these courses, we are going to look at what you will learn, the duration, and the ratings.
1. Big Data Course: The Big Picture
This Big Data course on Pluralsight teaches you about companies, concepts, and technologies that make up the Big Data world…
And how to devise a strategy for adopting Big Data in your organization.
In this course, you will learn all about Big Data, as it will get you up and running with the definitions and technologies that you need to know, and the vendors you need to know about.
And by the end of this course, you’ll know what Big Data is, how it can integrate with conventional database and Business Intelligence (BI) technologies, and how to invent a strategy for adopting Big Data in your organization.
This course is aimed at executives and business decision-makers and is actionable for technologists as well.
No Big Data or NoSQL knowledge is required.
This is an intermediate course that goes for 1 hour and 28 minutes.
It was updated on 31, October 2012 and has been rated 4 stars by 1567 learners.
2. SQL on Hadoop – Analyzing Big Data with Hive
In this Pluralsight course on Big Data, you will learn the Hive query language and how to apply it to solve common Big Data problems.
That’s why it’s one of the best Pluralsight courses.
This course includes an introduction to distributed computing, Hadoop, MapReduce fundamentals, and the latest features released with Hive 0.11.
This course tackles a few big questions about big data like:
- Why does this technology exist?
- Why do I need it?
- How can I get the best out of it utilizing something familiar like SQL? (check out my other review of the best SQL courses. )
- How does this all fit together in an ever-evolving ecosystem?
But that’s not all, this course will introduce the concepts of distributed computing, Hadoop, and MapReduce.
After that, it gets deeper into Apache Hive which is an SQL-like query language that can be used with Hadoop and NoSQL databases like HBase and Cassandra.
This course presents some of the challenges that you might experience solving real production problems, and how the Hive makes that task easier to accomplish.
It’s an intermediate course that takes 4 hours and 16 minutes.
Up to the time of writing this article, it has been rated by 569 learners and stands at a 4.5 rating.
3. Big Data Analytics with Tableau
Do you want a easy way to learn how to develop insights from your Big Data?
Well, this course is meant for you.
This is also the best Big Data course on Pluralsight that covers all the basics of Big Data systems including, functional examples using Tableau Software’s powerful analytics platform.
Analyzing terabytes of data can be daunting, and you must be thinking about what to do with petabytes.
Well, in this new genre of systems and technologies, it is upon us to sharpen up the toolbox and that is why in this course…
Ben explains the evolution of Big Data systems, as well as, the various architectures and popular vendors in this space.
After you go through the fundamentals of Big Data systems, you will learn how to access these systems using Tableau Software (I reviewed the best Tableau courses on this article.)
Using Tableau Software, he covers how to work with your Big Data and visualize in ways that will leave your boss singing your praise.
This course is suitable for intermediate learners and takes 3 hours and 44 minutes.
It was last updated on 22, July 2013 and has been rated 4.5 by 300 learners.
4. SQL Big Data Convergence – The Big Picture
In this best selling course on PluralSight, you will mostly focus on an investigation into the convergence of relational SQL database technologies from several vendors and Big Data technologies like Apache Hadoop.
This course will also explain to you what Big Data, Hadoop and Massively Parallel Processing (MPP) data warehouse technologies are, and how the latter two are converging technologically.
You will also see how products from:
… all of which are integrated with Apache Hadoop, are investigated.
This is an intermediate course that goes for 1 hour 22 minutes,
It was last updated on 7, March 2013 and has been rated 4 stars by 281 learners.
5. Big Data & Reporting with MongoDB
This is another best Big Data course on PluralSight that covers aggregation, reporting, and big-data issues with MongoDB.
You will learn key techniques and methods for reporting and aggregating data in the world of NoSQL.
Did you know that NoSQL databases may pose unique challenges?
Indeed, when it comes to large scale data analysis, NoSQL databases may pose unique challenges. Especially with reporting and aggregation.
In this course, you will learn how to go beyond simple queries against collections.
This course will also cover key techniques and strategies for digging up and aggregating data in a Big Data world using MongoDB.
It’s an intermediate course that takes 2 hours and 25 minutes.
It was last updated on 28, April 2014 and has been rated 4.5 stars by 198 students.
6. Real-World Big Data in Azure
Azure’s Big Data components let you build solutions that can process billions of events, using technologies that you already know.
In this best Pluralsight course on Big Data, you will build a real-world Big data solution in two phases, starting with just .NET technologies and then adding Hadoop tools.
How do you make sense of Big Data?
Picture yourself receiving 100 million events per hour and you need to save all of them permanently, but also you will process key metrics to show real-time dashboards.
Now you must be thinking of what technologies and platforms to use, right?
If your answer is yes, then today is your lucky day, this course answers all your questions by using Microsoft Azure, . NET, and Hadoop technologies:
- Event Hubs
- Cloud Services
- Web Apps
- Blob Storage
- SQL Azure HDInsight.
This course will teach you how to build a real solution that can process ten billion events every month, store them for permanent access, and distill key streams of data into powerful real-time visualizations.
This course is suitable for intermediate level students and takes 5 hours 21 minutes.
It was last updated on 17, June 2015 and has been rated 4.5 stars by 191 students.
7. Big Data on Amazon Web Services
This course on PluralSight contains an overview and demonstration of numerous components in the Amazon Web Services (AWS) Big Data Stack.
It provides you with a tour through Amazon Web Services’ (AWS) Big Data stack components, namely:
- Elastic MapReduce (EMR)
- Data Pipeline
- Jaspersoft BI on AWS
Additionally, AWS Kinesis is also discussed and this is why I added it in this list as the best Big Data course on PluralSight.
This course will even go further by taking you through all the steps for creating an AWS account, setting up a security key pair, and working with AWS Simple Storage Service (S3) as well.
In this course, numerous demos are provided that demonstrate interaction through AWS components via Web browser user interfaces, command line, and desktop tools.
This is an intermediate course that goes for 3 hours 54 minutes.
It was updated on 30, January 2015 and stands on a 4.5-star rating by 175 students.
8. Understanding the MapReduce Programming Model
Did you know that the MapReduce programming model is the de facto standard for parallel processing of Big Data?
This course on PluralSight introduces you to MapReduce, explains how data flows through a MapReduce program and guides you through writing your first MapReduce program in Java.
Processing millions of records, usually requires that you first understand the art of breaking down tasks into parallel processes.
The MapReduce programming model, which is part of the Hadoop ecosystem, gives you a framework to define your solution in terms of parallel tasks, which are then combined to give you the final desired result.
In this course, you’ll get an introduction to the MapReduce paradigm.
First, you will learn how it helps you visualize data flows through the map, partition, shuffle, and sort phases before it gets to the reduce phase and gives you the final result.
Then, this course will guide you through your very first MapReduce program in Java.
To summarize, you will learn to extend the framework Mapper and Reducer classes to plug in your own logic, and then run this code on your local machine without using a Hadoop cluster.
By the end of this course, you will be able to break big data problems into parallel tasks to help tackle large-scale data munging operations.
After a long wait, here is a course for beginners.
This course takes 1 hour 48 minutes and was last updated on 22, September 2016.
It has been rated 5 stars by 157 students.
9. Statistics Course: Probability & Distributions
We live in a world of big data, and it is only right if someone makes sense of all this data.
That’s the main reason why I included this course as one of the best Big Data courses on Pluralsight because you will learn to efficiently analyze data, formulate hypotheses, and generally reason about what the ocean of data out there is telling you.
This course will also teach you the fundamental topics essential for understanding probability and statistics.
First, you will have an introduction to set theory, a non-rigorous introduction to probability, an overview of key terms and concepts of statistical research.
Then, you will discover different statistical distributions, discrete and continuous random variables, probability density functions, and moment generating functions.
To conclude, you will use key distribution measures such as mean and variance to explore topics of covariance and correlation.
By the end of this course, you’ll be able to look at data and reason about it in terms of its descriptive statistics and possible distributions.
This is also another beginner’s level course that takes 4 hours 23 minutes.
It has been rated 4 stars by 54 students and was updated on 28, March 2018.
10. Building Your First Amazon Redshift Data Warehouse
Amazon Redshift is a low-cost cloud data platform that can scale from gigabytes to petabytes on a high-performance column-oriented SQL engine.
Join data pro Russ Thomas on a demo-heavy dive into Redshift and build your first data warehouse on AWS.
Amazon Redshift brings the power of scale-out architecture to the world of traditional data warehousing.
In Building Your First Amazon Redshift Data Warehouse, you will explore this low cost, cloud-based storage that can be scaled up or down to meet your true size and performance needs.
First, you will learn to stand up and configure a sample data warehouse.
Next, you will explore the internal workings and architecture of Redshift and what makes it so fast.
And to sum up, you will get hands-on experience connecting, querying, and building BI and data viz products as well as learn how to secure, maintain, and administer your new platform.
By the end of this course, you will be able to scale from gigabytes to petabytes on this high-performance column-oriented SQL engine… and that’s why this course is part of the best Big Data courses on PluralSight.
This is a course suitable for intermediates and takes 2 hours 40 minutes.
It is rated 5 stars by 42 students and was last updated on 9, March 2018.
11. Using Spark 2 To Train Machine Learning Models
Training ML models is a compute-intensive operation and is best done in a distributed environment.
This Big Data course on Pluralsight will teach you how Spark can efficiently perform data explorations, cleaning, aggregations, and train ML models all on one platform.
Did you know that spark is possibly the most popular engine for big data processing these days?
In this course, you will learn to build and train Machine Learning (ML) models such as regression, classification, clustering, and recommendation systems on Spark 2.x’s distributed processing environment.
This course starts by introducing the 2 ML libraries available in Spark 2; the older spark.MLlib library built on top of RDDs and the newer spark.ml library built on top of data frames.
You will also get to see the two compared, to help you know when to pick one over the other.
After that, this course will show you a classification model built using Decision Trees the old way, and see how you can implement the same model on the newer spark.ml library.
The course also covers many features of Spark 2, including going over a brand new feature in Spark 2, the ML pipelines used to chain your data transformations, and ML operations.
At the end of this course, you will be comfortable using the advanced features that Spark 2 offers for machine learning.
This course proves why it’s one of the best Big Data courses on PluralSight because you’ll learn to use it…
And components such as Transformers, Estimators, and Parameters within your ML pipelines to work with distributed training at scale.
This course is an intermediate level course that takes 3 hours 26 minutes.
It was updated on 19, June 2018 and has been rated 4.5 stars by 26 students.
More companies are now realizing the importance of data scientists and this propels the growth of the market, as Big Data is predicted to grow at a high Compound Annual Growth Rate (CAGR) of 18.45%.
This is why I compiled the best Big Data courses on PluralSight for you.
Check them out and gain your entrance into the Big Data market.
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Lerma is our expert in online education with over a decade of experience. Specializing in e-learning and e-courses. She has reviewed several online training courses and enjoys reviewing e-learning platforms for individuals and organizations.