Build practical AI literacy with Amelia Roberts. Learn core concepts, strengths/limits, and hands-on skills: better prompts, verifying outputs, spotting bias/hallucinations, and using AI safely and responsibly at work.
Cut through the hype and learn what AI really is—and isn’t. In AI Literacy, Amelia Roberts builds a clear, practical foundation: core terms (machine learning, large language models), how these systems work at a high level, and where they shine vs. where they struggle. You’ll leave with a realistic mental model you can use to make smart, everyday decisions about AI.
Then we get hands-on. You’ll practice writing effective prompts, checking and improving AI outputs, and using AI for common tasks like brainstorming, summarizing, drafting, and simple analysis. We’ll also cover responsible use at work—privacy, bias, hallucinations, data sensitivity, and basic compliance—plus a simple checklist you can apply before you hit “send.”
Course Outline ( Free Preview)
Module 01 - Introduction
In this module, Amelia Roberts introduces learners to the foundational concepts of generative AI, demystifying common buzzwords like ChatGPT, AI art, and deepfakes. The course focuses on explaining how generative AI works, the types of tools available, and the content they create, without delving into prompt writing or responsible AI use. By the end, students will gain a clear understanding of generative AI basics and be prepared to consider its applications in their personal and professional lives.
Module 02 - Foundations of Artificial Intelligence
In this module, Amelia introduces the foundational concepts of artificial intelligence (AI), explaining how machines simulate human intelligence to perform tasks like language understanding, pattern recognition, decision-making, and learning. The course highlights AI’s presence in everyday life, from personalized recommendations to voice assistants, emphasizing its practical relevance. Students will gain a clear overview of AI’s key principles, terminology, and real-world applications to build a solid understanding of the field.
Module 03 - Key Milestones in AI History5 min.
In this module, the speaker, Amelia, guides students through the key milestones in the history of artificial intelligence, highlighting its evolution from a novel concept in 1956 to today’s advanced applications like ChatGPT. The course explains the distinction between narrow AI, which excels at specific tasks, and the still-theoretical artificial general intelligence (AGI) that would possess human-like cognitive abilities. By understanding these developments and limitations, students gain a clear perspective on AI’s current capabilities and realistic expectations for its future.
Module 04 - How AI Learns9 min.
In this module, Amelia introduces the fundamental concepts of machine learning, explaining how it enables machines to learn patterns from data rather than relying on explicit programming. She cover the three main approaches: supervised learning, where models learn from labeled examples; unsupervised learning, which discovers hidden patterns in unlabeled data; and reinforcement learning, where agents learn optimal behaviors through rewards and penalties. This overview highlights how these methods empower modern AI systems to adapt and improve across diverse real-world tasks.
Module 05 - Deep Learning and Neural Networks5 min.
In this module, Amelia introduces deep learning and neural networks as brain-inspired machine learning models that have revolutionized AI by automatically learning complex patterns from raw data. She explains how neural networks consist of interconnected layers of artificial neurons that process information and adjust connections through training to make accurate predictions. The module highlights the significance of deep neural networks in powering advanced AI applications such as image recognition, speech understanding, and natural language processing, which have driven recent breakthroughs in the field.
Module 06 - Generative AI: Creating New Content2 min.
In this module, the instructor introduces generative AI, a cutting-edge area of deep learning where neural networks create new content such as text, images, and music using architectures like transformers. The course explains how models like large language models generate human-like language by predicting word sequences based on vast training data, highlighting their impressive capabilities and limitations. Students will gain a clear understanding of how generative AI works as advanced pattern recognition systems rather than true comprehension, emphasizing the importance of AI literacy in this rapidly evolving field.
Module 07 - Real-World Applications of AI3 min.
In this module, the speaker explores the pervasive role of artificial intelligence in everyday life, highlighting how AI powers familiar technologies like virtual assistants, recommendation systems, and facial recognition. Students will learn how AI techniques enable machines to understand language, interpret visual data, and make decisions across various domains, from entertainment to healthcare. This overview emphasizes AI’s integration into common services, illustrating its impact and ubiquity in the modern world.
Module 08 - Class Wrap Up3 min.
In this module, the speaker provides a comprehensive recap of the fundamental concepts of artificial intelligence, emphasizing how AI systems learn from data and excel at specialized tasks through machine learning and deep learning techniques. They highlight the importance of data quality, the distinction between narrow AI and general intelligence, and the pervasive role of AI in everyday life. By mastering these core ideas, students are equipped to critically understand AI’s capabilities and limitations, preparing them for further study or practical engagement with AI technologies.
Amelia Roberts holds a Master's Degree in Education and spent more than a decade teaching students in K-12 classrooms before bringing her passion for learning and technology to Pragmatic Works. Her background as an educator gives her a unique ability to break down complex topics, connect with learners of all skill levels, and help people feel confident adopting new technologies.
Today, Amelia specializes in Microsoft Copilot, Copilot Studio, AI adoption, and custom agent development. She works with organizations to help them move beyond the hype of AI and focus on practical ways to increase productivity, improve business processes, and solve real-world challenges. Whether she's leading an executive workshop, building a custom AI solution, or teaching a hands-on training course, Amelia is focused on helping people find meaningful ways to use technology in their everyday work.
In addition to her AI expertise, Amelia has extensive experience with Microsoft Power Platform and Power BI, helping organizations automate processes, connect systems, and turn data into actionable insights. She enjoys partnering with both business and technical teams to identify opportunities for innovation and create solutions that deliver lasting value.
Known for her energetic and engaging teaching style, Amelia believes learning should be practical, interactive, and immediately applicable. Her goal is simple: help people leave every session feeling empowered, inspired, and ready to put what they've learned into action.
Outside of work, Amelia enjoys reading, trying new foods, exploring new places, and spending time with family and friends.
