Human Computer Interaction & Machine Learning
4.1 (29 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
10,746 students enrolled

Human Computer Interaction & Machine Learning

Learn all basics of HCI with real word examples & Machine Learning
New
4.1 (29 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
10,746 students enrolled
Last updated 6/2020
English
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Current price: $13.99 Original price: $19.99 Discount: 30% off
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This course includes
  • 7.5 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • All aspects from basic to advance linked with Human Compute Interaction
Course content
Expand all 22 lectures 07:30:44
+ HCI Fundamentals
14 lectures 05:09:35
Introduction to Prototyping
21:28
Introduction to Evaluation Strategies
21:16
Interviews and Participation Observation
23:51
Evolution of the Graphical User Interface - GUI
11:58
Longitudinal & Sporadic Fact Collection Techniques
31:52
Storyboarding
14:16
More on Prototyping
24:30
Heuristic Evaluations
28:02
Mental Models & Cognitions
26:55
Typography
09:51
HCI-Scent
25:33
Layouts and basics of SWING
28:04

Two External Youtube demo videos are included for clarity.

1. Augmented Reality Zoo by Go Magic

2.  Virtual Roller Coaster Ride by 3D VR 360 Videos

Acknowledge the creators of all those videos.

AR Vs. VR
20:41
+ Introduction to Machine Learning
8 lectures 02:21:09
Setting up the Environment for Machine Learning:-Downloading & setting-up
04:13
How to Work With Google Collabs ?
07:25
Supervised Learning Techniques:-Regression techniques,
13:51
Naïve Bayer’s
16:39
Support vector Machines - Concept
15:39
Support Vector Machines - Hands - On with Google Collabs
48:38
ANN - KERAS Tutorial : Developing an Artificial Neural Network in Python [Step b
29:35
Unsupervised Learning Techniques:- Clustering,
05:09
Requirements
  • N/A
Description

Welcome to Human-Computer Interaction Course - (HCI). This course will elaborate almost all the basics of Human-Computer Interaction principals with real-world examples. Following are the list of Learning Objectives (LO) covered in this module.

To understand what is Human-Computer Interaction - HCI

To understand requirement collection techniques in HCI

To understand how to design HCI experiments

To understand how HCI evaluations are taking place.

To understand the   evolution of the Graphical User Interfaces - GUIs

To understand the difference between Virtual Reality and Augmented Reality

Machine Learning

Setting up the Environment for Machine Learning:-Downloading & setting-up Anaconda, Introduction to Google Collabs

Supervised Learning Techniques:-Regression techniques, Naïve Bayer’s, Artificial Neural Networks

Unsupervised Learning Techniques:- Clustering, K-Means clustering

Who this course is for:
  • All undergraduate and postgraduate students following computer science, software engineering, information systems, information technology