Prompt Engineering Masterclass: Ai & Llms
Published 3/2026
Created by CyberAI Learning Lab
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 109 Lectures ( 8h 47m ) | Size: 10.5 GB
What you'll learn
✓ Master every major prompting technique - from zero-shot and few-shot to chain-of-thought, tree of thought, ReAct, and metacognitive prompting
✓ Write high-quality, structured prompts that produce precise, reliable outputs across text, code, data, summaries, classifications, and creative content
✓ Apply domain-specific prompting across legal, HR, finance, marketing, operations, and customer service workflows using real-world examples
✓ Design secure, production-grade prompt systems including system prompts, prompt chains, agentic loops, and multi-agent architectures
✓ Build, test, and maintain a scalable prompt library with version control, documentation standards, quality metrics, and governance policies
Requirements
● No prior programming experience required - this course is accessible to both technical and non-technical professionals
● Basic familiarity with any AI tool (such as ChatGPT, Claude, or Gemini) is helpful but not mandatory
● A willingness to practice: the most value comes from applying the techniques hands-on as you progress through the course
Description
This course contains the use of artificial intelligence.
AI tools are only as powerful as the prompts that drive them. While organisations race to adopt large language models, most professionals are still relying on guesswork - typing vague instructions and hoping for the best. This course changes that. Whether you work in business, technology, legal, finance, HR, or operations, prompt engineering is the skill that determines how much value you actually get from AI - and this masterclass gives you the full picture, from first principles to production-grade systems.
What This Course Covers
• How large language models work - tokens, context windows, attention mechanisms, and how leading models like GPT-4o, Claude, and Gemini interpret your prompts
• The anatomy of a high-quality prompt - roles, context, task, constraints, format, and examples - and how inference parameters like temperature and top-p affect output
• Every major prompting technique: zero-shot, few-shot, chain-of-thought, self-consistency, tree of thought, ReAct, least-to-most, metacognitive prompting, and more
• Format control, negative prompting, and structured data output - including JSON, CSV, and XML without hallucinated fields
• Domain-specific prompting workflows across legal and compliance, HR and recruitment, marketing and sales, finance and audit, customer service, and operations
• System prompt design, prompt chaining, conditional prompting, and multi-turn conversation management
• Agentic AI prompting - planning, task decomposition, tool and function calling, memory management, and multi-agent orchestration
• Security essentials: prompt injection, jailbreaking, adversarial manipulation, injection-resistant design, and system prompt confidentiality
• Prompt quality metrics, A/B testing, automated evaluation, iterative refinement, and a structured optimization cycle
• Building an organisational prompt library: architecture, taxonomy, documentation standards, version control, governance, and responsible prompting policy
• Platform-specific guidance for GPT-4o, Claude, Gemini, and open-source models including LLaMA, Mistral, and Mixtral
Who Will Benefit
• Business professionals in any function who use AI tools and want to produce consistently better outputs
• Developers and AI/ML practitioners building prompt-driven products, pipelines, or agentic systems
• Product managers and team leads responsible for deploying AI tools across their organisation
• Legal, compliance, HR, finance, and operations professionals using AI for document analysis, drafting, and workflow automation
• Anyone moving from casual AI use to a structured, professional approach to prompting
Prerequisites
No programming background is required for the majority of this course. A basic familiarity with any AI tool - such as ChatGPT, Claude, or Gemini - is helpful but not essential. The technical modules covering agentic AI, function calling, and API-level prompt design will benefit developers and technical practitioners most, though they are explained clearly enough for motivated non-technical learners to follow. All you need is curiosity and a willingness to practice.
By the end of this course, you will have a complete, systematic approach to prompt engineering - applicable to any model, any platform, and any professional context. You'll write better prompts, build better AI workflows, and bring skills to your organisation that most professionals simply don't have yet.
Who this course is for
■ Business professionals, analysts, marketers, HR teams, lawyers, and operations managers who want to use AI tools more effectively and confidently in their daily work
■ Developers, product managers, and AI practitioners looking to design robust, production-ready prompt systems and agentic AI workflows
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