Artificial Intelligence Essentials for Businesses

Course Info

Code IND02-113

Duration 5 Days

Format Classroom Online

Course Summary

Within the modern world, technology is making constant advancements in all areas of society. A newer technology that has risen in popularity is artificial intelligence and machine learning. Many businesses and organisations are becoming increasingly reliant on artificial intelligence systems to improve productivity.
Artificial intelligence is a computer technology designed to interpret data and act independently to carry out business functions, complete tasks or provide accurate information or results. These systems are often created to mimic human intelligence and behaviour. The use of AI is greatly desired as it can reduce business costs, remove the possibility of human error, and increase productivity. 
To effectively implement an artificial intelligence system, there must be an understanding of the basic principles of a system, including the common types of systems, various intelligence agents and the limitations of an AI system. Once this knowledge has been established, there can be further development into the specific purpose of the system and the datasets it will utilise.

During this course, you’ll learn:
To understand the importance of artificial intelligence in business.
To identify ways in which artificial intelligence can benefit a business.
To assess various types of artificial intelligence.
To explain the advantages and disadvantages of using artificial intelligence and machine learning applications.
To find the balance between utilising artificial intelligence and human employees.
To carefully innovate, plan, design, implement and measure the performance of artificial intelligence and machine learning systems.
To develop knowledge on the concepts and principles of artificial intelligence.
To assess how artificial intelligence can adapt and improve the productivity of business functions.
This course is designed for anyone who wishes to utilise artificial intelligence and machine learning to optimise business functions. It would be most beneficial for:
  • Business Owners
  • Senior Executives
  • Operations Managers
  • Project Managers
  • Artificial Intelligence Engineers
  • Planning and Strategy Managers
  • Machine Learning Engineers
  • Data Analysts
This course uses a variety of adult learning styles to aid full understanding and comprehension. Participants will investigate an existing artificial intelligence system to highlight key features, classifications, and processes.
They will be provided with the highest quality equipment to effectively partake in the arranged learning exercises. Combined with presentations, practical demonstrations, discussions and practical activities, participants will have ample opportunities to fully develop their knowledge and related skills. To guarantee full comprehension, participants will also have the opportunity to begin planning and designing an AI system in relation to their specific role.

Course Content & Outline

Section 1
  • Introduction to Artificial Intelligence
  • Defining artificial intelligence (AI) and machine learning (ML).
  • The concepts and principles of AI and ML.
  • Established organisations that have successfully integrated AI functions into daily practice.
  • The standardisation of AI and ML in various industries and sectors.
  • Common AI systems and their roles in business.
  • Assessing the limitations of AI.


Section 2
  • Intelligent Agents
  • Understanding what intelligent agents are.
  • The various types of intelligent agents – simple reflex, model based, goal based, utility agent and learning agent.
  • The advantages and disadvantages of each type of intelligent agent.
  • Examining what functions would be most suitable for each intelligent agent.
  • How AI functions differentiate based on whether they are knowledge based or data based.
  • Logical reasoning and deduction processes.


Section 3
  • Machine Learning
  • Situations where supervised and unsupervised systems would be used.
  • Classification and clustering of machine learning datasets.
  • How the artificial neural networks mimic human brains to process data.
  • Developing methods of object recognition in systems.
  • Identifying classes of data.
  • Reviewing the types of features – independent and individual variables.


Section 4
  • Fuzzy Logic
  • Defining what fuzzy thinking is.
  • The vitality of fuzzy logic for effective AI and ML.
  • The concept, principles, and purpose of fuzzy logic.
  • Analysing fuzzy sets and fuzzy rules.
  • Comparing fuzzy logic with probability.


Section 5
  • Genetic Algorithm
  • The method of genetic algorithm.
  • How genetic algorithms solve internal issues based on the natural selection process.
  • The business needs of optimisation, maximisation and minimisation and how genetic algorithms aid in meeting that goal.
  • Genetic algorithm processes and evolution.
  • Typical characteristics of a genetic algorithm – chromosomes, genes, selection, mutation, and crossover.

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