This intensive crash course introduces learners to Large Language Models (LLMs) and modern prompt engineering techniques in a condensed 5-hour format. It is designed for beginners and intermediate learners who want a practical understanding of how generative AI systems work and how to use them effectively.
The course begins with an overview of Large Language Models, explaining what they are, how they are trained on massive datasets, and why they are central to today’s AI applications such as chatbots, content generation tools, and intelligent assistants.
A major focus is placed on prompt engineering, which is the process of designing effective instructions for LLMs. Learners explore how different prompt structures influence model outputs and how to improve results by refining queries, adding context, and controlling output style.
The course also covers practical use cases of LLMs across industries, including automation, writing assistance, coding support, customer service, and data analysis.
Additional sections explain key limitations of LLMs, such as hallucinations, bias, and reasoning errors, along with best practices to mitigate these issues when building real-world applications.
Learners are introduced to advanced prompting techniques, including role-based prompting, few-shot learning, and iterative prompt refinement to improve model performance.
By the end of the course, learners will und
