Practical Modern AI: Understanding and Using Neural Networks

Artificial intelligence is transforming how we work and solve problems, but truly leveraging its power requires understanding what happens under the hood. To get the best results, you need to move beyond trial-and-error and learn how these models actually process information. This text-based course guides you from the absolute basics of neural networks to advanced prompting strategies. You will gain a clear, conceptual understanding of modern AI systems and learn how to write precise instructions that yield high-quality, reliable outputs. What you'll learn: Understand the foundational mechanics of neural networks, machine learning, and large language models; Apply structured prompt engineering frameworks to get accurate and relevant responses from AI assistants; Explore the basics of modern AI architectures, including semantic search and retrieval-augmented generation concepts; Identify and mitigate common AI limitations, such as hallucinations, biases, and data privacy concerns; Create efficient text-based workflows to automate routine tasks, summarize complex information, and brainstorm ideas. The course starts with essential terminology and the history of AI development, establishing a solid theoretical foundation. You will then progress through structured text-based lessons detailing practical interaction patterns, iterative prompting, and real-world application scenarios. Designed specifically for beginners with no prior programming or technical background who want to confidently navigate and utilize modern AI tools. Start reading today to unlock the true potential of modern artificial intelligence.