The complex world of artificial intelligence (AI) covers many areas of computing, and it is driving digital disruption across the globe. New technologies are helping to redefine most industries, and many organisations are looking to take advantage of recent AI advances, which is creating demand for skilled professionals.
Introduction to Artificial Intelligence is a professional development course that will explain how artificial intelligence can help solve real-world problems in the context of artificial environments.
In this artificial intelligence course, you will discover how artificial intelligence is used in business, from marketing to customer relations, and about the critical ethical and economic dilemmas that underpin decisions on machine learning.
You will also learn about deep learning and its significance in artificial intelligence, as well as the three types of machine learning – supervised, unsupervised and reinforcement – and its application in business, industry and the environment.
On completion of this course, you will understand the valuable underpinnings of AI and machine learning and leverage AI techniques across a broad range of innovative industries.
Unit - Artificial intelligence
Unit 1 – Introduction to Artificial Intelligence
Meaning of AI
The history of AI
Two prerequisites for deep learning
Theory of mind
Types of artificial intelligence
Three branches of AI
Reasons AI matters
Introduction to natural language processing
Glossary of terms
Unit 2 – Ethical, economic, and other concerns
Ethics and artificial intelligence
AI ethics principles and guidelines
STEM (Science, Technology, Engineering and Mathematics)
Unit 3 – Neural networks
Structure of the human nervous system
Cells of the nervous tissue
Parts of a neuron
Main anatomical features of neurons
Intelligence and adaptability
Artificial neural networks
Applying artificial neural networks
Digital worm brains
Artificial brain cells
Unit 4 – Deep learning
Solving problems logically
Abstraction and function
Training a deep neural network
All in one data training
Pitfalls of deep neural networks
Unit 5 – Machine learning
Three types of machine learning
Supervised machine learning
Unsupervised machine learning
Reinforcement machine learning
Unit 6 – Business applications
Customer relationship management
Machine learning and social media ads
Content Generation and Curation
Unit 7 – Application in environmental & primary industries
Agriculture and horticulture
Environmental industries and climate change
Unit 8 – Industrial and other applications
Travel and transportation
Self-driving cars or automated driving systems (ADS)
Transport, freight, and logistics
Individual health and personalised health care
Training and education
Tutoring and coaching
Plagiarism detection and authorship
Environment monitoring and management
Predicting fire and analysis (emergency management)
Estimated duration 50 hours
Course Delivery and Start
Start anytime, self-paced and 100% online
Assessment will be comprised of written exercises, including short-answer questions, reflective tasks, short reports and/or projects. There are no examinations or due dates for assessment. As a result, you can complete training in your own time and at your own pace with the assistance of unlimited tutor support.
Excellent course material with plenty of opportunity to research around the topic.
S. Nazaretian, Carnegie, VIC | Introduction to Artificial intelligence
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