In this paper, we explore how large language models (LLMs) can enhance educational practices, highlighting their potential to provide personalized instruction, generate dynamic content, and improve learner engagement. By sharing examples from a business analytics course and an internship class, we offer insights into the practical applications of LLMs in educational environments. In the analytics course, we discuss the integration of a customized OpenAI GPT and examine its effectiveness in clarifying complex analytical concepts, supporting data-driven tasks, and delivering personalized feedback to students. In the second case, we describe the use of NotebookLM, highlighting its role in fostering interactive learning, reflective practice, and a deeper comprehension of concepts among students. Discussions with students indicate that while LLMs provide advantages in clarifying complex concepts, assisting with data tasks, and encouraging reflection, their effective integration necessitates careful implementation to maximize impact across diverse educational contexts.