Chevron Left
Retour à Fundamentals of Scalable Data Science

Fundamentals of Scalable Data Science, IBM

341 notes
79 avis

À propos de ce cours

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...

Meilleurs avis

par HS

Sep 10, 2017

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

par MT

Feb 08, 2019

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

Filtrer par :

79 avis

par alamelumuralidaran

Feb 18, 2019

Wonderful course

par 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.

par Héctor Flores

Feb 11, 2019

Can I get a badge?

par Jonathan Hasan

Feb 09, 2019

Good course, instructor was extremely knowledgeable.

par Matthew Tsoi

Feb 08, 2019

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

par Waleed Mohammed Saeed Al Amshi Al Ghamdi

Feb 08, 2019


par Nikhil Pramod Palaskar

Feb 08, 2019

It was difficult to follow the IBM cloud setup since it was constantly changing, I couldn't understand the reason for using python2.7 since its only 10 months before it wont be supported by the community. Sometime instructors' pronunciations were not clear and and thus added extra confusion. However, instructor do actively participate in helping with discussions. Audio and video quality were also not very good. This course is a very basic introduction to IBM cloud and general stats. Prior knowledge of spark is useful. Overall the course is nice introduction to IBM cloud if one is interested.

par Andrés

Feb 07, 2019

Assigments needs to be better defined and explained

par Matthijs Keep

Feb 06, 2019

Sets you up well for working with Spark within the IBM Environment.

par Daniel Brandenburg

Feb 06, 2019

This course needs work. There needs to be more of a challenge, being an advanced course I expect a certain level of difficulty. I think the knowledge is too high level. There also needs to be more of a hands on approach. Let me connect to the Cloudent service, and more practice using spark and map functions.