Complete Prompt Engineering Bootcamp - Learn Features of AI
Master Practical Prompt Engineering for ChatGPT, API to Build Smarter AI Workflows and Real-World Applications
★★★★★ 5.0
(4 reviews)
2 hours of content
What you'll learn
- Understand how prompt design influences ChatGPT outputs
- Master key LLM controls (system messages, temperature, top_p, max_tokens, penalties).
- Learn the different types of prompts (instruction, few-shot, chain-of-thought, role, etc.).
- Grasp tokens, cost, and latency trade-offs for efficiency.
- Design, test, and iterate prompts across multiple use-cases (summarization, coding, data extraction, customer support, content generation).
- Build a library of reusable prompt templates.
- Apply chaining methods to connect multiple AI steps into workflows.
- Use tools and APIs (ChatGPT Playground, LangChain, PromptLayer) to automate workflows.
- Measure prompts with qualitative and quantitative metrics (accuracy, F1, BLEU/ROUGE, user satisfaction).
- Run A/B testing to compare prompt variations.
- Optimize for cost and latency in real deployments.
- understand why hallucinations happen and how to mitigate them.
Covers prompt design, LLM controls such as temperature and top_p, token cost and latency trade-offs, prompt types, chaining, and evaluation metrics. Learners can design, test, and iterate prompts for applications like summarization, coding, and customer support.
Who this course is for
Developers and AI practitioners who want to build and optimize LLM workflows.
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