Course at a Glance
Code: CMQ
Course Length: 3 Months

In this interactive 3 month LIVE ONLINE course, you will learn how to:

  • Demonstrate an understanding of machine learning and its basic techniques
  • Solve problems using search algorithms
  • Examine and discuss Simultaneous Localization and Mapping (SLAM)
  • Solve problems using supervised learning methods
  • Use WEKA software for data analysis and machine learning
  • Solve problems using mathematical optimization
  • Use MATLAB for machine learning

 

 

Course Details

Overview

Machine learning is a field of computer science that programs computers with the ability to learn from data and make informed, adaptive dynamic predictions and decisions using algorithms. It is related to computational statistics, mathematical optimization and Artificial Intelligence (A.I.).

The last decade has witnessed exciting developments in machine learning that led to impressive consumer applications such as virtual assistants and speech recognition. This remarkable development results from increasingly powerful computers and the proliferation of smart objects' data.

Machine learning will probably revolutionize every industry. Some applications already exist, but many are to come especially with the advent of Internet of Things (IoT) and Industrial Internet of Things (IIoT). Autonomous vehicles, predictive maintenance, fault diagnosis, smart alarm processing, and advanced process control are few domains where machine learning could be applied in the industry.

Over 12 weeks, this course will aim to introduce you to basic techniques used in machine learning. You will learn how techniques such as neural networks or decision trees can solve real world problems. You will learn how to use MATLAB and WEKA software tools to apply machine learning in practice.

Course Outline

MODULES 1 & 2: INTRODUCTION TO MACHINE LEARNING

  • Definitions
  • Introduction to algorithms
  • Basic statistics and probability concepts
  • Introduction to MATLAB and WEKA

MODULES 3 & 4: PROBLEM SOLVING BY SEARCH PART 1

  • Problem-solving agents
  • Problem types
  • Example problems
  • Basic search algorithms

MODULES 5 & 6: PROBLEM SOLVING BY SEARCH PART 2

  • Best-first search
  • A* search
  • Hill-climbing search
  • Genetic algorithms

MODULES 7 & 8: SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM)

  • Robot localization techniques and principles
  • Mathematical optimization
  • Overview of Kalman filters and particle filters
  • SLAM

MODULES 9 & 10: MACHINE LEARNING: DECISION TREES AND NAÏVE BAYES

  • Problems solved by machine learning
  • Decision trees
  • Naïve Bayes

MODULES 11 & 12: MACHINE LEARNING: NEURAL NETWORKS AND RULES

  • K-NN
  • Neural networks
  • Association rules

 

Learning and Teaching

Benefits of eLearning to Students

  • Cost effective: no travel or accommodation necessary
  • Interactive: live, interactive sessions let you communicate with your instructor and fellow students
  • Flexible: short interactive sessions over the Internet which you can attend from your home or office. Learn while you earn!
  • Practical: perform exercises by remotely accessing our labs and simulation software
  • Expert instructors: instructors have extensive industry experience; they are not just 'academics'
  • No geographical limits: learn from any location, all you need is an Internet connection
  • Constant support: from your instructor(s) and a dedicated Learning Support Officer for the complete duration of the course
  • International insight: interact and network with participants from around the globe and gain valuable insight into international practice 


Benefits of eLearning to Employers

  • Lower training costs: no travel or accommodation necessary
  • Less downtime: short webinars (60-90 minutes) and flexible training methods means less time away from work
  • Retain employees: keep staff who may be considering a qualification as full time study
  • Increase efficiency: improve your engineering or technical employees’ skills and knowledge
  • International insight: students will have access to internationally based professional instructors and students

 

How Does it Work?

EIT eLearning courses involve a combination of live, interactive sessions over the Internet with a professional instructor, set readings, and assignments. The courses include simulation software and remote laboratory applications to let you put theory to practice, and provide you with constant support from a dedicated Learning Support Officer.


Practical Exercises and Remote Laboratories

As part of the groundbreaking new way of teaching, our online engineering courses use a series of remote laboratories (labs) and simulation software, to facilitate your learning and to test the knowledge you gain during your course. These involve complete working labs set up at various locations of the world into which you will be able to log to and proceed through the various practical sessions.

These will be supplemented by simulation software, running either remotely or on your computer, to ensure you gain the requisite hands-on experience. No one can learn much solely from lectures, the labs and simulation software are designed to increase the absorption of the materials and to give you a practical orientation of the learning experience. All this will give you a solid, practical exposure to the key principles covered and will ensure that you obtain maximum benefit from your course.

 

Brochure

Brochure

To access the detailed program brochure, please complete this form.

 

Endorsed by ISA