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Fundamentals of Scalable Data Science, IBM

383 ratings
84 reviews

About this Course

The value of IoT can be found within the analysis of data gathered from the system under observation, where insights gained can have direct impact on business and operational transformation. Through analysis data correlation, patterns, trends, and other insight are discovered. Insight leads to better communication between stakeholders, or actionable insights, which can be used to raise alerts or send commands, back to IoT devices. With a focus on the topic of Exploratory Data Analysis, the course provides an in-depth look at mathematical foundations of basic statistical measures, and how they can be used in conjunction with advanced charting libraries to make use of the world’s best pattern recognition system – the human brain. Learn how to work with the data, and depict it in ways that support visual inspections, and derive to inferences about the data. Identify interesting characteristics, patterns, trends, deviations or inconsistencies, and potential outliers. The goal is that you are able to implement end-to-end analytic workflows at scale, from data acquisition to actionable insights. Through a series of lectures and exercises students get the needed skills to perform such analysis on any data, although we clearly focus on IoT Sensor Event Data. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link After completing this course, you will be able to: • Describe how basic statistical measures, are used to reveal patterns within the data • Recognize data characteristics, patterns, trends, deviations or inconsistencies, and potential outliers. • Identify useful techniques for working with big data such as dimension reduction and feature selection methods • Use advanced tools and charting libraries to: o Automatically store data from IoT device(s) o improve efficiency of analysis of big-data with partitioning and parallel analysis o Visualize the data in an number of 2D and 3D formats (Box Plot, Run Chart, Scatter Plot, Pareto Chart, and Multidimensional Scaling) For successful completion of the course, the following prerequisites are recommended: • Basic programming skills in any programming language (python preferred) • A good grasp of basic algebra and algebraic equations • (optional) “A developer's guide to the Internet of Things (IoT)” - a Coursera course • Basic SQL is a plus In order to complete this course, the following technologies will be used: (These technologies are introduced in the course as necessary so no previous knowledge is required.) • IBM Watson IoT Platform (MQTT Message Broker as a Service, Device Management and Operational Rule Engine) • IBM Bluemix (Open Standard Platform Cloud) • Node-Red • Cloudant NoSQL (Apache CouchDB) • ApacheSpark • Languages: R, Scala and Python (focus on Python) This course takes four weeks, 4-6h per week...

Top reviews


Sep 10, 2017

A perfect course to pace off with exploration towards sensor-data analytics using Apache Spark and python libraries.\n\nKudos man.


Feb 08, 2019

Good course content, however, some of the material especially the IBM cloud environment setup sometimes confusing

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84 Reviews

By Shubham Shree

Mar 10, 2019

The course is quite good. However, its not meant for absolute beginners. One needs to have a decent understanding of Python and SQL in order to follow the course and complete the programming assignments. However, the extra effort put towards learning how to program is well worth it

By Mohanad Qusay Atta Abu-Naula

Mar 10, 2019

Fuzzy, outdated, low quality course, according to the instructor; he is very busy "TRAVELLING" so that he cannot improve the quality of this course.

My problem is that the programming assignment of week 2 has no meaningful doc-string inside the functions that require coding, I do not know how I can deduce that my implementation is right before submitting to the auto grader.

By Ahmed Tealeb

Mar 10, 2019

Excellent :)

By Igor Eydman

Mar 04, 2019

Good course, but some of the later videos and assignments refer to data generation on Cloudant and NodeRed that made the videos confusing since the Cloudant videos were removed. This caused me to jump between the course and youtube videos to learn about data generation, only to find out it wasn't necessary.

By Rohan Saha

Feb 24, 2019

This course takes you on a very structured path. It starts with the core concepts of spark and how is it important in the industry. The material along with the IBM cloud platform is a total bonus.

The assignments are challenging for a reason. They test your entire knowledge and makes sure that you pay careful attention to the material being delivered. In fact, while completing the assignments, you will find yourself looking through official library documentation for support; this is a good thing. Moreover, you also find yourself writing good quality code.

Romeo teaches the content in the simplest way possible. He explains the concepts with utmost care with adequate examples. The content on statistics is also very well laid out which helps you become a better decision maker.

Overall, the course was excellent and should suffice for anyone willing to learn spark and get familiarity with cloud technologies and Apache Spark.

By alamelumuralidaran

Feb 18, 2019

Wonderful course

By Gusti Rahmat Ashari

Feb 17, 2019

This course is very recommended if you want to bring your Data Science skill to the next level. The instruction is very clear and easy to understand. The assignment is really challenging for me as the new comer in this Data Science world, but yeah, i finally can finished this course. You should take this course.

By Héctor Flores

Feb 11, 2019

Can I get a badge?

By Jonathan Hasan

Feb 09, 2019

Good course, instructor was extremely knowledgeable.

By Matthew Tsoi

Feb 08, 2019

Good course content, however, some of the material especially the IBM cloud environment setup sometimes confusing