COURSE OVERVIEW:
Artificial Intelligence (AI) Fundamentals is the study of the core concepts, tools, and practical applications of artificial intelligence in modern society and business. It explores how intelligent systems are designed to simulate aspects of human thinking such as learning, reasoning, decision-making, and problem-solving. As AI technologies increasingly influence industries, workplaces, and everyday life, understanding how to use these tools effectively has become an essential skill.
This course is designed for both individuals with little or no technical background and those already familiar with information technology who wish to begin actively using AI tools. It provides an accessible introduction to AI concepts while progressively introducing more technical insights for learners who wish to deepen their understanding.
Students will learn what AI is, how it works at a foundational level, and how to apply modern AI tools in real-world scenarios. Emphasis is placed on practical usage, responsible deployment, and critical evaluation of AI outputs. Non-technical learners will gain confidence in using AI tools for productivity, research, business tasks, and creative work. Technically inclined learners will develop a clearer understanding of the underlying mechanisms such as machine learning models, data training processes, and system limitations.
The method for accomplishing this includes guided demonstrations, practical exercises using widely available AI platforms, real-world case studies, and structured discussions on ethical and responsible AI use. Learners will engage with generative AI systems, automation tools, and intelligent assistants while developing the ability to assess reliability, bias, and risk.
Among the topics included in this course are: introduction to artificial intelligence, history and evolution of AI, types of AI systems, generative AI and large language models, machine learning fundamentals, data and algorithms, practical AI tool usage, AI for productivity and business, automation basics, prompt design principles, AI ethics and governance, bias and fairness in AI systems, and evaluating AI outputs.
LEARNING OUTCOMES:
Upon completion of this course learners will be able to:
Describe the fundamental concepts and terminology of Artificial Intelligence.
Explain the differences between AI, machine learning, and generative AI.
Confidently use common AI tools for research, writing, data analysis, automation, and productivity tasks.
Apply effective prompting techniques to improve AI-generated results.
Describe how data is used to train and influence AI systems.
Identify the strengths, limitations, and risks associated with AI technologies.
Evaluate AI outputs critically for accuracy, bias, and reliability.
Apply AI tools appropriately within business, educational, and professional environments.
Explain ethical considerations and responsible AI usage principles.
Communicate AI concepts clearly to both technical and non-technical audiences.
