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2000+ Courses · 15+ Technology Domains
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New Data Science & AI Course

Prompt Engineering for Generative AI

Learn how to design, test, and improve prompts for ChatGPT, Gemini, Claude, and enterprise LLM tools. This course focuses on practical AI workflows for content, research, coding, automation, data analysis, and business productivity.

Prompt
Act as a senior AI workflow designer. Create a reusable prompt framework that turns vague business requests into clear, testable LLM tasks.
Output: role, context, objective, constraints, examples, evaluation checklist, and revision loop.
Skills: zero-shot, few-shot, structured outputs, prompt testing, RAG-ready instructions, and AI safety.
ChatGPT Gemini Claude Prompt Patterns Few-shot Prompting Chain-of-Thought Structured Output AI Agents RAG Prompts Prompt Testing Automation AI Ethics
What You Master

Practical AI Prompting Skills

Build prompts that are clear, reliable, reusable, and measurable across real workplace use cases.

Prompt Foundations

Understand how LLMs respond to instructions, context, examples, constraints, and output formats.

Prompt Frameworks

Create reusable frameworks for business analysis, content creation, coding, research, and customer support.

Testing and Evaluation

Compare prompt versions, reduce hallucination risk, and measure answer quality using checklists and rubrics.

Structured Outputs

Generate JSON, tables, summaries, SOPs, email templates, scripts, and technical documentation.

Agentic Workflows

Design prompts for AI assistants that plan tasks, ask clarifying questions, and use tools responsibly.

Responsible AI

Apply privacy, safety, bias-awareness, and human review practices for professional AI usage.

Syllabus

Prompt Engineering Curriculum

The course is built around hands-on practice. Students write, test, compare, and improve prompts for common AI tools and business scenarios.

01. Generative AI and LLM Basics
  • How LLMs interpret prompts
  • Tokens, context windows, temperature, and model limits
  • Choosing the right AI tool for the task
02. Prompt Structure and Patterns
  • Role, task, context, constraints, and format
  • Zero-shot, few-shot, and iterative prompting
  • Prompt templates for repeatable workflows
03. Business and Productivity Prompts
  • Emails, reports, proposals, and SOPs
  • Meeting notes, summaries, and action plans
  • Market research and competitor analysis
04. Data, Coding, and Technical Prompts
  • Spreadsheet and SQL assistance
  • Code explanation, debugging, and documentation
  • Data analysis prompts with clear assumptions
05. Advanced AI Workflows
  • Prompt chaining and multi-step reasoning
  • RAG-friendly prompts for document Q&A
  • Agent prompts for planning and tool use
06. Prompt Testing and Responsible AI
  • Evaluation rubrics and quality checks
  • Reducing hallucinations and ambiguity
  • Privacy, bias, safety, and human review
Course Outcomes

What Students Can Do After This Course

By the end, students can confidently use AI as a professional work assistant and design prompts that produce dependable results.

1
Outcome 1 Create reusable prompt templates for daily workplace tasks.
2
Outcome 2 Improve AI responses through examples, constraints, and revision loops.
3
Outcome 3 Design prompts for content, research, coding, data, and automation.
4
Outcome 4 Evaluate outputs for accuracy, clarity, bias, and business usefulness.

Start Learning Prompt Engineering

Build the AI communication skill that helps every role work faster, think clearer, and create better outcomes with modern LLM tools.