Machine Learning Essentials (MLE)


DateTimeVenueAction
8 Dec 2017
9:30am - 5:30pmSingaporeRequest for Information
 
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Machine Learning is revolutionizing the world by allowing computers to learn as they progress forward with large data sets, overwriting overcoming all programming pitfalls and impasses. Machine Learning builds algorithms, which when exposed to high volumes of data, can self-teach and evolve.
When this technology powers Artificial Intelligence (AI) applications, the combination can be powerful. Smart robots can already be found around us doing all our jobs with more speed and accuracy, and continuously improving themselves at every step.
COURSE OBJECTIVE
Machine Learning Essentials (MLE) is designed to allow participants acquire all essential knowledge on Machine Learning.
COURSE DURATION
1 Days
COURSE OUTLINE
Introduction to Machine Learning

  • What is Machine Learning and its importance?

  • How Businesses Can Take Advantage of Machine Learning


Different Techniques in Machine Learning

  • Regression Method

  • Case Study on regression methods

  • Application of Regression Method

  • Hands-On on the Application of Regression Method


Logistic Regression

  • Case Study on Logistic Regression

  • Application of Logistic Regression

  • Hands-On on the Application of Logistic Regression

Pre-Requisites
NA
Examination
Participants are required to pass an examination upon completion. This exam tests a candidate’s knowledge and skills related to Machine Learning based on the syllabus covered in the course
Certification
Participants will be awarded a Certificate of Competency in Machine Learning Essentials (MLE) upon meeting the requirements of the course and passing the examination.
WHO WILL BENEFIT FROM THIS COURSE?
Machine Learning Essentials (MLE) is designed for anyone who have little or no understanding, knowledge of, or experience in Machine Learning and would like the opportunity to learn in a supportive and encouraging environment.

Class is limited to 20 participants as hands-on sessions and real-time demonstration is expected.