BCS Essentials Certificate in Artificial Intelligence
Take your first steps in AI training to understand the principles of AI, its benefits and risks, and the processes behind machine learning.
Take your first steps in AI training to understand the principles of AI, its benefits and risks, and the processes behind machine learning.
Artificial Intelligence (AI) is a methodology for using a non-human system to learn from experience and imitate human intelligent behaviour.
The BCS Essentials Certificate in Artificial Intelligence tests a candidate’s knowledge and understanding of the terminology and the general principles. This syllabus covers the potential benefits; types of Artificial Intelligence; the basic process of Machine Learning (ML); the challenges and risks associated with an AI project, and the future of AI and humans in work.
European students can purchase this course in Euros. Please allow 1 working day for enrolment.
Section One Overview
Section 1 Contents
What Is Artificial Intelligence (AI)?
What Is Human Intelligence?
IQ & EQ
Aristotle
The Scientific Method
Timeline of AI & Machine Learning (ML)
Industrial Revolutions
Universal Design
Machines Learn From Data
Tom Mitchell's Definition of ML
Heuristic
A Human is More Than IQ & EQ
Identifying Objects
The Digital Human
Human Brain Inspired AI 'Deep Learning' (DL)
Test Your Learning - Part One
Summary
Section Two Overview
Section 2 Contents
3 Steps/Components in a ML Project
Research and Development - R&D
Benefits of Using AI and ML in Engineering
Benefits of Using AI and ML in Health and Social Care
Benefits of Using AI and ML in Logistics
Benefits of Using AI and ML in Entertainment
Benefits of Using AI and ML in Sales and Marketing
1970's - Optical Character Recognition (OCR)
ML Enabling IoT and Big Data
ML Enabling Cloud High Performance Computing (HPC)
ML Enabling Deep Learning Artificial Neural Networks
ML Enabling Deep Reinforcement Learning
Funding for ML Projects
ML Classification Examples
Ethics
What Humans Do Well
Humans and Machines Working Together
ML Challenges and Risks 1/3
ML Challenges and Risks 2/3
ML Challenges and Risks 3/3
Test your learning - Part Two
Summary
Section Three Overview
Section 3 Contents
Tom Mitchell's Definition of ML
Engineers Build Models Everyday
Schematic of an AI Program
Features of an Agent
Types of an Agent
Russell and Norviq - A General Learning Agent
Typical Agent Functionality
State of the Agent World
Machine Learning - Part of the AI Toolkit
Types of ML
Test your learning - Part Three
Summary
Section Four Overview
Section 4 Contents
Batch and Offline Learning
Online Learning
Instance Based and Model Based Learning
ML is Multi-Disciplinary
ML - Good Data and Algorithms
ML - Good Data and Algorithms: Overfitting
ML - Good Data and Algorithms: Underfitting
ML - Good Data and Algorithms: Underfitting
Test Your Learning - Part Four
Summary
Section 5 Contents
Humans and Machines Working Together (further reading)
Ethics - Challenge
Robotics Guidelines - EPSRC
Ethics in AI
Super AI - Consciousness
Human Roles
How Humans Complement Machines
How AI Enhances Humans
Asilomar Principles
Test Your Learning - Part Five
Summary
Section Five Overview