PROMPT ENGINEERING

Prompt Engineering Course Syllabus and Content Delivery Plan
By Vigor EdTech

Course Overview

This course is designed to equip learners with a deep understanding of prompt engineering for Large Language Models (LLMs). It provides foundational concepts, hands-on techniques, and advanced strategies to effectively utilize and optimize LLMs for various applications, including text generation, summarization, sentiment analysis, and creative AI workflows. This course is ideal for professionals, developers, and students looking to enhance their AI skills.

Course Duration

• Total Duration: 8 weeks


• Weekly Commitment: 6-8 hours (including lectures, assignments, and projects)


• Delivery Mode: Online (live + recorded sessions) and optional offline workshops

Syllabus

Module 1: Introduction to Prompt Engineering

Duration: 1 Week

Topics Covered:

• What is Prompt Engineering?


• Overview of Large Language Models (LLMs): GPT, ChatGPT, PaLM, and others


• Applications of Prompt Engineering in real-world scenarios


• Introduction to tools and platforms (OpenAI, Hugging Face, and LangChain)

Hands-On: Exploring basic LLM APIs and generating text using simple prompts

Module 2: Crafting Effective Prompts

Duration: 2 Weeks

Topics Covered:

• Prompt Design Principles: Clarity, specificity, and relevance


• Prompt Types: Instruction-based, open-ended, and zero-shot prompts


• Iterative Prompt Refinement


• Common Challenges in Prompt Design (e.g., ambiguity, bias)

Hands-On: Experimenting with prompt variations to generate desired outputs

Module 3: Advanced Prompt Engineering Techniques

Duration: 2 Weeks

Topics Covered:

• Few-shot and One-shot Prompting


• Chain-of-Thought Prompting (CoT)


• Prompting for Multi-turn Conversations


• Using Context and Constraints Effectively

Hands-On: Building complex workflows using few-shot and CoT techniques

Module 4: Applications of Prompt Engineering

Duration: 2 Weeks

Topics Covered:

• Text Summarization and Paraphrasing


• Sentiment Analysis and Classification


• Creative Content Generation (storytelling, poetry, scripts)


• Knowledge Extraction and Data Augmentation


• Integration with Low-Code/No-Code Platforms

Hands-On: Designing use-case-specific prompts for applications in different domains

Module 5: Ethics, Limitations, and Future of Prompt Engineering

Duration: 1 Week

Topics Covered:

• Ethical Considerations in Prompt Design


• Bias Mitigation in LLM Outputs


• Limitations of Current LLMs and Prompting Techniques


• Emerging Trends and Research in Prompt Engineering

Hands-On: Identifying ethical concerns and designing unbiased prompts

Capstone Project

Duration: 2 Weeks (Runs Parallel to Modules 4 and 5)**

Deliverables:

• Real-world problem statement


• Solution design using advanced prompt engineering techniques


• Comprehensive project report and presentation

Examples:

• Designing an AI assistant for customer support using prompt engineering


• Developing a knowledge retrieval system for domain-specific queries

Content Delivery Plan

1. Learning Methodology

• Live Sessions: Weekly interactive sessions with experts (1-2 hours/session)


• Recorded Content: Pre-recorded video tutorials for self-paced learning


• Hands-On Practice: Assignments and interactive coding notebooks


• Discussion Forums: Dedicated Q&A forums for peer and mentor support

2. Assignments and Quizzes

• Weekly quizzes to reinforce learning


• Prompt crafting assignments with real-world scenarios

3. Practical Use Cases

• Real-world datasets and APIs for practical applications


• Guided exercises on integrating prompts into workflows

4. Mentorship and Support

• Dedicated mentors for personalized guidance


• Feedback sessions to improve prompt design techniques

5. Certification

• Certification of Completion from Vigor EdTech


• Portfolio-ready capstone project to showcase expertise

Target Audience

• Developers and engineers working with LLMs


• Students and researchers interested in AI and NLP


• Professionals seeking to upskill in AI-driven workflows


• Enthusiasts aiming to explore creative applications of LLMs

Pre-requisites

• Basic programming knowledge (Python preferred)


• Familiarity with APIs and JSON


• Understanding of NLP concepts is helpful but not mandatory

Tools and Technologies

• OpenAI API (ChatGPT, GPT-4, and GPT-3.5)


• Hugging Face Transformers


• LangChain and other LLM integration frameworks


• Collaborative Platforms: GitHub, Jupyter Notebook, Colab

For inquiries and enrollment, visit vigoredtech.in