Chevron Left
返回到 Fundamentals of Scalable Data Science

Fundamentals of Scalable Data Science, IBM

4.3
446 個評分
96 個審閱

課程信息

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 ibm.biz/badging. 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...

熱門審閱

創建者 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.

創建者 MT

Feb 08, 2019

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

篩選依據:

99 個審閱

創建者 Paulo Renato Rodrigues

Apr 26, 2019

Awesome course!

創建者 Jamiil Touré ALI

Apr 26, 2019

Excellent. I highly recommend it, jump in and enjoy learning the foundations.

創建者 Uzwal Gutta

Apr 26, 2019

Thank you

創建者 Pawel Piela

Apr 23, 2019

Too easy to be called advanced. I look forward to seeing what's next.

創建者 Daniel Thompson

Apr 21, 2019

Be careful when signing up for your IBM Cloud Instance and remember to shut it down when you're not using it. I ran out of free hours and unfortunately they're no longer free after the first 30 days which either makes it impossible or expensive to finish this course. Also, 30 days might mean an arbitrary 30 day billing cycle, perhaps starting on the 1st of the month.

創建者 ASHISH JOHNSON

Apr 15, 2019

awesome course, got a good understanding of statistics in an intuitive manner.

The main strength of this course is that, this course will help you to develop intuition of the whole data science concepts into the real world scenario.

創建者 Marcin Sowanski

Apr 14, 2019

not enough additional materials

創建者 Ahmed Emad Ahmed Taha Elmasry

Apr 10, 2019

the content is really good but I don't understand the Indian accent well although this guy really did his best

創建者 EMMANUEL NDAHIMANA

Apr 10, 2019

Nice course with good tutorials

創建者 Xiang Yang Ni

Apr 10, 2019

I was just wondering, is the content a bit short? Are there any more details on practising writing functions and text rather than an hour videoing and quiz? I believe intense programming skills practise is more efficient