Course Outline
Introduction to Prompting and ChatGPT for Government
- Basics of Prompting - Prompt Structure & Prompt Styles
- Pitfalls of Large Language Models (LLMs)
- Open AI Models – Definitions & Types
- Need and Functionality of ChatGPT
- Capabilities of ChatGPT
- Key Concepts of GPT-3.5
- Demonstration: Account Creation (PaaS / SaaS)
Applications of Effective Prompting Using ChatGPT for Government
- Daily Tasks - Summary Generation, Proofreading, Language Translation, Email Writing, Blog Writing, Cold Sales Emails, etc.
- Technical Tasks – Excel Formula Creation, Code Writing, Code Debugging, etc.
- Creativity Tasks – Headline/Tagline Creation, Content Creation, Blog Writing, etc.
Different OpenAI Applications for Government
- GPT-3.5 Playground – Fine-Tuning of ChatGPT
- DALL.E 2 – Image Creation / Image Editing
- Codex – Natural Language to Animation Creation
Techniques of Image Prompting for Government
- Need for Image Prompting in Government Workflows
- Advanced Techniques - Style Modifiers, Quality Booster, Repetition, Weighted Terms, Fix Deformed Generations, etc.
- Use Cases - DALLE.2, Stable Diffusion & Midjourney
Enhancing Prompt Reliability for Government
- Promoting Debiasing and Ensemble Learning in Government Applications
- Addressing Transparency and Privacy Concerns in Public Sector Use
- Use Cases of Prompt Reliability in Government Operations
Requirements
1. Python Programming: Proficiency in Python is essential, as it is the primary programming language used by most deep learning libraries such as PyTorch and TensorFlow.
2. Machine Learning: A solid understanding of fundamental machine learning concepts, techniques, and algorithms is crucial for grasping the foundational principles of ChatGPT.
3. Deep Learning: Knowledge of neural networks, particularly recurrent neural networks (RNNs) and transformers, is beneficial for fine-tuning and managing models like GPT.
4. Natural Language Processing (NLP): Familiarize yourself with common NLP techniques and libraries such as NLTK and Spacy, and gain an understanding of context generation and text generation algorithms.
5. Reinforcement Learning: Since GPT-3 incorporates reinforcement learning from human feedback, a basic understanding of reinforcement learning and reward systems is valuable.
Additional experience with cloud platforms like Google Cloud, Microsoft Azure, or AWS, as well as foundational skills in data storage, manipulation, and processing (SQL, pandas, NumPy), can significantly enhance the ability to work with large datasets and deploy models effectively for government applications.
