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Education in our world today has undergone a massive shift due to COVID-19. There hasbeen a noticeable shift in the places where students learn, which affects how they learn and theirunderstanding of difficult content. A large field which has adopted this transition to virtuallearning environments is Computer Science. Here we have seen that traditional methods ofteaching and learning have struggled to translate to online platforms. To respond to thesechallenges, my capstone project was to create VidQuest, a dynamic learning solution to helpstudents comprehend content better in an online learning world.This solution is designed to build effective online learning experiences to make computerscience accessible to everyone. Looking back on completed research and pedagogical theorybased on computer science education, VidQuest aims to introduce a new solution. Our goal withVidQuest is to bridge the gap between our traditional learning environments and our new e-learning world. VidQuest creates a learning environment for individual students and uniquelearning styles by integrating video content, forum pages, and playlist content. VidQuest has arange of multimedia content: videos of lectures, examples, and code walkthroughs; forum pageswith question-and-answer functionality to allow students to engage better; and worksheets, studyguides, and practice exercises to reinforce learning concepts.Overall, VidQuest starts on the path to build a creative approach to learning computersciences in the online world. VidQuest can potentially revolutionize the way students engagewith course materials, collaborate with peers, and inspire others to take this goal even further.

Large Language Models (LLMs have the potential to revolutionize clinical medicine by enhancing healthcare access, diagnosis, surgical planning, and education. However, their utilization requires careful, prompt engineering to mitigate challenges like hallucinations and biases. Proper utilization of LLMs involves understanding foundational concepts such as tokenization, embeddings, and attention mechanisms, alongside strategic prompting techniques to ensure accurate outputs. For innovative healthcare solutions, it is essential to maintain ongoing collaboration between AI technology and medical professionals. Ethical considerations, including data security and bias mitigation, are critical to their application. By leveraging LLMs as supplementary resources in research and education, we can enhance learning and support knowledge-based inquiries, ultimately advancing the quality and accessibility of medical care. Continued research and development are necessary to fully realize the potential of LLMs in transforming healthcare. [ABSTRACT FROM AUTHOR]