Internet of Things (IoT): Programming for Analytics
Taught by Mr. Ajit Jaokar

Internet of Things (IoT): Programming for Analytics

 

Taught by Ajit Jaokar 

 

Aim of Course:

The "Internet of Things" (IoT) is the massive network of sensors and devices that produce data that can be accessed over the internet.  It is sometimes considered the next big wave of "Big Data," the first being the exploitation of huge organizational databases and the second being the generation of unstructured data by social applications.  

This course will review the flow of IoT data and survey various vertical applications of IoT analytics.  You will then get into hands-on analytics with Python to work with various IoT analytics models like anomaly detection.  Using a case-study approach, Ajit will walk you through pandas, numpy, matplotlib and sklearn.

This course may be taken individually (one-off) or as part of a certificate program.
Course Program:

WEEK 1: IoT analytics: Overview

  • The IoT ecosystem and the role of analytics
  • The flow of IoT data
  • Applying analytics to various points in the IoT ecosystem

 

WEEK 2: IoT analytics – predictive modeling

An end-to-end tutorial using Python libraries to make a prediction


WEEKS 3 and 4:  Case study

An illustrated study of problem solving with IoT, featuring a case study of an IoT vertical (wearables) from device to classification.



Internet of Things (IoT): Programming for Analytics

Who Should Take This Course:
  • Recent Statistics.com PASS (Certificate) graduates who want to apply their learning to IoT
  • Developers who want to transition to a new role as Data Scientists
  • Entrepreneurwho want to launch new products covering IoT and analytics
  • Anyone interested in developing their career in IoT Analytics from a strategic perspective by choosing the Strategic/non programming option
Level:
Intermediate
Prerequisite:
Participants should be familiar with Python programming - see Introduction to Python for Analytics for what's expected (however, an overview of machine learning libraries for Python i.e. pandas, numpy, matplotlib, scikit-learn and others will be covered in the course).

Organization of the Course:

This course takes place online at the Institute for 6 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:

Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Other options - Statistics.com Specializations, INFORMS CAP recognition, and academic (college) credit are available for some Statistics.com courses

Specialization:
Specializations are an easy way for you to demonstrate mastery of a specific skill in statistics and analytics. This course is part of the Intelligence and Security Analytics Specialization which teaches statistical and machine learning methods for detecting anomalies, identifying images, and processing data from sensors. Take all three Statistics.com courses on this topic (this course, plus the courses listed to the right under "related courses," not including conferences). For savings, use the promo code "anomaly-specialization" and register for all three courses at once for $1197 ($399 per course, not combinable with other tuition savings).

INFORMS CAP:
This course is also recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam, and can help CAP® analysts accrue Professional Development Units to maintain their certification .
Course Text:
Content is delivered via video.  You do not have to be online at specific times, unless a hangout or call is scheduled.
Software:
Python
Instructor(s):

Dates:

March 03, 2017 to March 31, 2017 November 03, 2017 to December 01, 2017 November 02, 2018 to November 30, 2018

Internet of Things (IoT): Programming for Analytics

Instructor(s):

Dates:
March 03, 2017 to March 31, 2017 November 03, 2017 to December 01, 2017 November 02, 2018 to November 30, 2018

Course Fee: $599.00

Do you meet course prerequisites? What about book & software? (Click here to learn more)

Group rates: Click here to get information on group rates. 

First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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