The objective of this training program is to re-skill data scientists. The volume of data is rapidly increasing with proliferation of IoT devices. IoT has turned everything into potential source of data. Data in its raw form is not always useful.  Data need to be processed to transform into information. The volume, velocity and variety of data have made conventional processing and analytical approaches obsolete.

The course introduces participants to fundamental understanding of sensor data, systems, and innovative and novel analytical approaches. Machine learning methods are used for data analysis, this is where they are similar to data mining, but the main goal of machine learning is to automate decision models. Algorithms are the heart and soul of machine learning and they help computers to find hidden insights. So in essence machine learning algorithms need to be learnt. The machine needs to learn from data. Data will have multi dimensions- Type (quantitative or qualitative), amount (big or small size) and number of variables available to solve a problem. Learning algorithms should also be as general purpose as possible. We should be looking for algorithms that can be easily applied to a broad class of learning problems.

R and Python are leading programming languages that have an array of packages for IoT data analytics. This course introduces R, python and various advance python packages being used in IoT analytics. Standard R & Python IDEs are going to be used to perform hands-on sessions/programming exercises.

Pre-requisites

Computer fundamentals, IoT basics, Programming fundamentals and knowledge of statistics

Understanding Data, Information, knowledge and Wisdom (DIKW Pyramid), Types of Data, Physical and logical representation of Data, Natural languages – Symbolic representation, Computer languages – Data Encoding, Storage and interpretation

Handling of sensor data, data pre-processing and integration of different data sources, Heterogeneity and distributed nature, Selection of sensor to capture right set of data, Analog to digital conversion, Time and frequency domain analysis, Sampling theorem, Aliasing, Selection and cleaning, Edge analytics

Statistics is about extracting meaning from data, Techniques for visualizing relationships in data and systematic techniques for understanding the relationships, Exploring data – visualization, Correlation and Regression, Probability distributions.

Concept of machine learning, Introduction to R programming, Regression- Linear and non linear, Algorithms- MLR, Logistics and nonlinear regression, Classification, Algorithms- SVM, decision trees, boosted decision trees, Naïve bayes, Quality of classification – Concepts of ROC, hit rate, kappa statistics and K-S statistics, Feature selection – Learn feature selection methods for regression- Ridge and LASSO

Feature selection methods for classification methods- Information value based, filter based and wrapper based, Algorithms and techniques for marketing analytics – Conjoint analysis, Hidden Markov models

 

The duration of course is 48 hours which includes 30 hours of hands-on sessions and case studies.

This is the most suitable course for data scientist and IoT developers.

The kit includes:  Arduino Mega (ATMega2560) Sensors – Analog temperature sensor, Humidity sensor,  IR Proximity Sensor, Switches – Push Button (10), Breadboard, LEDs (10), Resistors (10), , Connecting leads (25), WiFi – ESP8266 ESP01,

Yes, The you will get a life-time access to LMS.

There will be a post-training online MCQ based evaluation test to award you grade and certificate of proficiency.

Course Reviews

4.7

9 ratings
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  1. Profile photo of Sunny Shah

    Manish Patadia, Vadodara, India

    The trainer was thorough with the concepts of IOT Analytics and explained the concepts in a very detailed manner.

  2. Profile photo of Sunny Shah

    Jayesh Rathod, Mumbai, India

    This course is everything I was looking for

  3. Profile photo of Sunny Shah

    Harsh Bhogle, Jharkhand, India

    I am so happy I took this online course. I am clear with all the concepts of IOT Analytics.

  4. Profile photo of Sunny Shah

    Nirmit Mann, Ahmedabad, Gujarat

    Awesome training, awesome trainer, awesome experience

  5. Profile photo of Sunny Shah

    Shiva Giri, Chennai, Tamil Nadu

    This is a very well crafted online training course. Highly recommended

  6. Profile photo of Sunny Shah

    Madhavan Mahadevan, Cochin, Kerala

    Not just the online training was perfect, the offline support was also tremendous

  7. Profile photo of Sunny Shah

    Kapil Madhav, Mangalore, Karnataka

    The best course I have attended online

  8. Profile photo of Sunny Shah

    Jordan Morgan, London, England

    The best training experience. This course is designed in a very systematic manner. Even for a beginner like me, it was not difficult to understand the concepts.

  9. Profile photo of Sunny Shah

    Swaminathan Reddy, Bangalore, India

    I am completely satisfied with the training. The trainer was the best trainer ever.

TAKE THIS COURSE
  • 29,999.00
  • 10 Hours
1245 STUDENTS ENROLLED

    Upcoming Batches

    India Sat-Sun (8 Weeks)

    29-APR-17 07:00 AM – 10:00 AM IST

    USA Fri-Sat (8 Weeks)

    28-APR-17 10:30 PM – 01:30 AM EST

    UK Sat-Sun (8 Weeks)

    29-APR-17 03:30 AM – 06:30 AM BST

    Enroll Now

     

    Course Features

    We provide 48 hours of live online training including live POC & assignments.

    It would be live & interactive online session with Industry expert Instructor.

    Expert technical team available for query resolution.

    We provide lifetime Learning Management System (LMS) access which you can access from across the globe

    We strive to offer the Best Price to our customers with the guarantee of quality service levels

    Post completion of the course, you will appear for assessment from Collabera TACT. Once you get through, will be awarded as a course completion certificate

    Drop us a query

    Collabera TACT, 25 Airport Road,Morristown, New Jersey 07960 Phone: (973)-598-3969 Email: jointact@collaberatact.com

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