Syllabus for Prompt Engineering and ChatGPT Skill Enchancement Course

 





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Syllabus for Prompt Engineering and ChatGPT Skill Enchancement Course

  Course Code Category L T P C C.I.E. S.E.E. Exam   SEC 0 1 2 2 - 50 3 Hrs R23 IV Year I Semester, B.Tech PROMPT ENGINEERING (for CSBS) Course Objectives: This course is designed to: 1. Introduce the fundamental concepts of prompt engineering, including proper design principle, interactive refinement and interaction with LLMs 2. Ability to design and apply advanced prompting techniques 3. enable students to build , evaluate, and deploy prompt driven applications Course Outcomes: Upon the completion of the course students will be able to: S.No Outcome Knowledge Level 1. Apply iterative pro...
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1. Introduction

  1. Introduction 1.1 Online Variant Online Large Language Models (LLMs) are accessed through cloud-based APIs or web interfaces. Examples include OpenAI API services. These models provide high-quality responses, scalability, and access to state-of-the-art capabilities. However, they generally require internet connectivity, API credentials, and may incur usage costs. 1.2 Local Variant Local LLMs execute directly on a user's computer using frameworks such as Transformers. Models like DistilGPT-2 and FLAN-T5 can be downloaded and run offline. Local execution improves privacy and eliminates API costs, although performance depends on the available hardware resources. 1.3 Comparison of Online and Local Variants Feature Online Local Internet Required Not required after download Billing Usually required Free Privacy Cloud processing Local processing ...
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