Course Overview
Prompt engineering is the most critical skill of the AI era. As large language models like GPT-4, Claude, and Gemini reshape every industry, professionals who know how to communicate with these models precisely—and creatively—will hold a decisive competitive advantage.
In this course, you will learn how AI models interpret language, why certain prompts succeed while others fail, and how to architect prompt systems that produce consistent, high-quality outputs for complex real-world tasks.
Through structured labs and capstone projects, participants will master advanced techniques including Chain-of-Thought reasoning, few-shot learning, role prompting, ReAct frameworks, and prompt chaining — equipping them to build AI-powered solutions that work reliably in production.
By the end of this course, learners will be able to design prompt pipelines that integrate with APIs, applications, and AI agent systems.
Course Distinction
What makes our course unique?
Go Beyond 'Ask and Hope'
Most people treat prompting as guesswork. You will learn the engineering principles behind how models respond — and how to take full control of that response.
Applied to Real Business Problems
Every technique is taught through business-relevant scenarios: drafting legal summaries, generating code, automating content pipelines, analysing data, and building AI workflows.
Expert Instructors from the Industry
Learn from practitioners who have deployed Gen AI systems at scale for enterprises — not just theorists.
Prompt-to-Product Thinking
You will not just write prompts — you will design prompt architectures that plug into real applications, APIs, and AI agent systems.
Course Content
- How LLMs work — tokens, attention, and inference
- GPT-4, Claude, Gemini — model landscape and differences
- The anatomy of a prompt: system, user, context, constraints
- Understanding temperature, top-p, and sampling parameters
- Zero-shot and few-shot prompting
- Role prompting and persona assignment
- Instruction prompting with explicit constraints
- Output formatting: JSON, Markdown, structured data
- Chain-of-Thought (CoT) and Step-by-Step Reasoning
- Self-Consistency and Ensemble prompting
- ReAct: Reasoning + Acting for complex tasks
- Tree of Thought for multi-path problem-solving
- Content generation and marketing automation
- Code generation and debugging prompts
- Data extraction, summarisation, and analysis
- Customer service and chatbot prompt design
- Building multi-step prompt pipelines
- Connecting prompts to APIs and tools
- Handling errors and hallucinations in chains
- Prompt versioning and A/B testing
- Designing system prompts for AI applications
- Context window management
- Building AI-powered internal tools
- Integrating prompts with LangChain and API calls
- Evaluating prompt quality — metrics and frameworks
- Iterative prompt refinement methodology
- Safety, bias, and guardrails in prompt design
- Documenting and scaling prompt libraries
Key Features
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✔ Instructor-led interactive sessions -
✔ Real-world prompt labs -
✔ AI tool access included -
✔ Industry recognised certification -
✔ Prompt library templates -
✔ Capstone project
Skills Covered
- Prompt Architecture Design
- Chain-of-Thought Reasoning
- Few-Shot & Zero-Shot Techniques
- ReAct & Tree of Thought
- Output Formatting & Structuring
- Prompt Chaining & Pipelines
- System Prompt Engineering
- Hallucination Mitigation
- LLM API Integration
- Prompt Evaluation & Optimisation
Advancements
- Prompt Engineer
- Gen AI Developer
- AI Product Manager
- AI Content Strategist
- LLM Integration Specialist
- AI Automation Consultant
Business Impact
FAQ?
Who Should Attend
Software Developers
Product Managers
Data Analysts
Content Creators
Marketing Professionals
Business Analysts
Entrepreneurs
IT Professionals
Your competitors are already prompting smarter.
Don’t fall behind. Master Gen AI prompts engineering and leads the AI-powered future.
✔ Learn from industry experts
✔ Work on real AI projects
✔ Earn certification
Testimonial
What people are say?
















