MASTER PROMPT ENGINEERING AND BUILD INTELLIGENT AI AGENTS FOR MARKETING,
BUSINESS, AND BEYOND
The future of work is here — and it’s powered by artificial intelligence. In
today’s world, mastering the shift from prompt engineering to agent engineering
is no longer just a trend — it’s a critical skill that separates
forward‑thinking professionals from those left behind.
If you’ve ever wondered how AI goes beyond static prompts to operate
autonomously — making decisions, executing multi‑step strategies, and generating
highly relevant outcomes — this is the definitive course for you.
Led by AI educator and digital marketing expert Anton Voroniuk, this Udemy
program guides you through every step of the journey: from crafting precise
prompts for large language models (LLMs) like GPT‑4, Claude, Gemini, and
DeepSeek, to building fully functional AI agents that save hours every day,
reduce costs, and multiply productivity across marketing, design, business, and
customer service.
Today, knowing how to use AI tools is no longer enough. To stand out, you must
learn how to design AI agents that operate autonomously across platforms. This
course will give you that competitive edge.
WHAT YOU WILL LEARN
In this hands‑on, comprehensive training, you’ll gain mastery across both prompt
engineering and agent engineering, including:
1. Prompt Engineering Skills
high‑quality responses
results
Self‑Ask prompting, RACE Framework prompting for tackling complex tasks
2. Frameworks for Precision and Consistency
Framework for reliable AI responses
desired outcomes
3. Explore AI Models and Techniques
including chain‑of‑thought rollouts
answer
4. Build Fully Functional AI Agents
and SWOT analyses
highly relevant output
5. Real‑World Use Cases and Applications
optimization
accurate responses and expected results
6. Evaluate AI Responses and Minimize Errors
7. Designing AI Agents That Save Time and Resources
enhanced reasoning
WHAT YOU’LL ACHIEVE AFTER THIS TRAINING
customer service
multi‑step reasoning
TOOLS USED IN THE COURSE

• Best practices for creating prompts that reliably produce accurate,
• Why certain prompts fail and how to fix them for better output and relevant
• Advanced methods like chain‑of‑thought prompting, few‑shot prompting,
• The RACE Framework, ReAct Framework, Tree‑of‑Thought Framework, and Self‑Ask
• How do these approaches represent prompt engineering best practices and drive
• Work with GPT‑4, Claude, Gemini, DeepSeek, Copilot
• Design prompts for large language models (LLMs) for multi‑step reasoning,
• Integrate external tools, existing code, and user inputs to produce a final
• Evolve from static prompts to intelligent, multi‑step AI Agents
• Create Agents for question answering, campaign planning, trend forecasting,
• Leverage artificial intelligence and natural language processing (NLP) for
• Agents for marketing strategy, trend spotting, and customer service
• Agents that use user inputs to build multi‑channel campaigns, delivering
• Cross‑platform Agents using ChatGPT, Claude, Gemini, DeepSeek, Copilot
• Assess AI results for accuracy, relevance, and context
• Fix errors for better output and minimize generic results
• Focus on tailored, context‑aware outcomes
• Build Agents with Make, N8N for multi‑platform automation
• Automate repetitive tasks, multi‑stage workflows
• Use fine‑tuning, knowledge bases, and advanced prompting techniques for
• Build and operate AI Agents that work autonomously
• Automate routine and complex tasks across marketing, design, sales, and
• Evaluate AI outputs with precision
• Enhance strategies using AI-driven analytics
• Stay ahead with generative AI tools, advanced prompting frameworks, and
• Be positioned as an AI and Agent Engineering expert
• GPT‑4, Claude, Gemini, DeepSeek — prompt engineering, agent building
• Copilot — automating writing, coding
• DALL‑E — image and video storyboard creation
• Make, N8N — AI Agent ecosystems, automation
• ElevenLabs, Elsa, MyGPTs — voice‑driven AI Agents
• RACE, ReAct, Tree‑of‑Thought, Self‑Ask frameworks — AI agent reasoning