تطبيقات الذكاء الاصطناعي ومستقبل تكنولوجيا التعليم

كود البرنامج : KL-16018

تطبيقات الذكاء الاصطناعي ومستقبل تكنولوجيا التعليم

OUTLINE

Module 1 : Artificial intelligence ecosystem

Explore the history and potential of AI within the context of the digital ecosystem.

Define AI

Review the history and development of AI, and contextualise the technology in the emergent ecosystem

Illustrate the nature of the different types of technologies and where AI fits in

Analyze the trajectory and impact of different types of technologies in the digital ecosystem

Module 2: AI and machine learning: Understanding the black box

Module 1 Artificial intelligence ecosystem

Explore the history and potential of AI within the context of the digital ecosystem.

Define Artificial Intelligence.

Review the history and development of AI, and contextualise the technology in the emergent ecosystem

Illustrate the nature of the different types of technologies and where AI fits in

     Analyze the trajectory and impact of different types of technologies in the digital  ecosystem

Evaluate the benefits and limitations of machine learning approaches within different contexts

  Module 3 :Understanding deep learning and neural networks

Understand what deep learning is and how it is powering the modern approach to AI.

Identify the functionality of errors and weights in neural networks

Determine the impact of backpropagation on neural networks

Investigate different use cases of deep neural networks

Assess the mechanics of machine learning algorithms, such as neural networks

Module 4 : Gesture recognition technology

What is gesture recognition?

Use gestures to interact with the computer instead of the keyboard and mouse.

Deep learning definition.

Deep Learning Employment Areas

The difference between machine learning and deep learning

Choosing between machine learning and deep learning

How to create and train deep learning models

Deep learning applications.

Module 5: Big Data

Big data concept

data classification

Big data features

Big data sources

The importance of big data

Big data extraction and analysis

Basic steps for working with data

Data mining utilities

Big Data Analytics Methodology

Big data analytics tools 5

Module 6 the ethics of Artificial Intelligence

Explore the hierarchy of ethical and legal considerations around AI.

Categorize the three pitfalls of AI

Investigate the regulatory considerations of using AI

Debate the sources of algorithmic bias

Develop ethical principles for your organization or an organization of your choice to instill for its AI applications and plan for preventing bias

Module 7 :Eye movement tracking in humans and computers

Eye movement analysis to understand aspects of human learning

Eye movement technique definition

The historical development of eye movement tracking technology

Eye movement tracking devices

Interaction in eye-tracking technology research

Eye movement tracking software and devices

Steps to implement eye movement tracking technology