Artificial Intelligence Essentials For Businesses
Course Info
Day 5 of each course is reserved for a Q&A session, which may occur off-site. For 10-day courses, this also applies to day 10
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Course Summary
In the modern world, technology is constantly improving all areas of society. Newer technologies that have risen in popularity are artificial intelligence and machine learning. Many businesses and organisations increasingly rely on artificial intelligence systems to improve productivity.
Artificial intelligence (AI) is 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. 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, an understanding of the basic principles of a system must be understood, including the common types of systems, various intelligence agents and the limitations of an AI system. Once this knowledge has been established, further development can be made into the specific purpose of the system and the datasets it will utilise.
Upon completion of this course, participants will be able to:
- Understand the importance of artificial intelligence in business.
- Identify ways in which artificial intelligence can benefit a business.
- Assess various types of artificial intelligence.
- Explain the advantages and disadvantages of using artificial intelligence and machine learning applications.
- Find the balance between utilising artificial intelligence and human employees.
- Carefully innovate, plan, design, implement and measure the performance of artificial intelligence and machine learning systems.
- Develop knowledge of the concepts and principles of artificial intelligence.
- 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 participate 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 be able to begin planning and designing an AI system concerning 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.
Certificate Description
Upon successful completion of this training course, delegates will be awarded a Holistique Training Certificate of Completion. For those who attend and complete the online training course, a Holistique Training e-Certificate will be provided.
Holistique Training Certificates are accredited by the British Assessment Council (BAC) and The CPD Certification Service (CPD), and are certified under ISO 9001, ISO 21001, and ISO 29993 standards.
CPD credits for this course are granted by our Certificates and will be reflected on the Holistique Training Certificate of Completion. In accordance with the standards of The CPD Certification Service, one CPD credit is awarded per hour of course attendance. A maximum of 50 CPD credits can be claimed for any single course we currently offer.
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