EXPERT COURSE

Prompt Engineering, Evaluation, & Refinement
(Edition II)

A $4.4 Trillion Business

Large Language Models (LLMs) and other generative AI systems are transforming how professionals create, translate, analyze, and manage content. According to research from McKinsey, generative AI could contribute up to $4.4 trillion annually to the global economy, largely by improving productivity in knowledge work.

However, obtaining consistent, reliable, and high-quality outputs from LLMs requires more than simply writing prompts. Professionals must learn how to design structured prompts, evaluate results, and refine outputs systematically.

The Prompt Engineering, Evaluation and Refinement – II Edition course is a focused training designed to help language and content professionals master the techniques required to guide AI systems effectively. Over three intensive sessions, participants will learn how to structure prompts, test outputs, evaluate model performance, and iteratively improve results.

This program goes beyond basic prompting and introduces evaluation frameworks, testing methodologies, and refinement strategies that enable professionals to move from casual AI use toward repeatable, high-quality workflows powered by LLMs.

Why Prompt Engineering Skills Are Essential Today

As AI becomes deeply integrated into content creation, localization workflows, and knowledge work, prompt engineering has emerged as a critical professional skill.


Research from Microsoft and LinkedIn shows that AI literacy and prompt engineering are among the fastest-growing digital skills required in modern workplaces.


Professionals who understand how to design prompts systematically and evaluate AI outputs rigorously can significantly increase productivity while maintaining quality standards.


Conditions: Please read our course and subscription plans terms and conditions carefully. With your registration, you confirm that you have read, understood and accepted our conditions and agree with them. 

If you have any questions, please visit the FAQ section (for courses or subscription plans) or get in touch with us.

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  • This course includes:
  • Expert coach:
    Andrés Romero Arcas, Language Technology Expert at Acolad
  •  Interactive activities
  •  Life access to contents 
  •  In English
  •  Completion certificate
  •  Money back guarantee
  • Acquire A-Z knowledge about AI Translation
  • When: 20-22 April 2026 (18.00 CET)
  • Duration: 6 h approx.

Course and Instructor Description

This course will teach participants how to:

✔ Design prompts that guide LLMs toward specific and structured outputs

✔ Implement prompt evaluation pipelines for reliable results

✔ Apply iterative refinement strategies to improve performance

✔ Use LLMs as evaluation tools within structured testing frameworks

✔ Balance automation, quality control, and human judgment


By the end of the course, participants will be able to work with LLMs more strategically, efficiently, and reliably in professional environments.


Instructor: Andrés Romero Arcas
Andrés Romero Arcas is an AI and Language Technology Specialist with strong experience in NMT, LLMs, MTQE, and automated translation workflows. He focuses on practical, scalable AI solutions for localization teams and is known for explaining complex technology in a clear, actionable way.
Session 1: Prompting Foundations and Advanced Strategies
Session 2: Prompt Creation, Evaluation, Iteration and Refinement
Session 3: Prompt Evaluation
Session 1

Prompting Foundations and Advanced Strategies

Session 1. Prompting Foundations and Advanced Strategies

1.1 Definition and Purpose
1.2 Core Principles for effective Prompt Engineering
1.3 Standard Prompt Structure
1.4 System, User & Assistant Prompts
1.5 Useful Parameters
1.6 Prompt Engineering: Advanced Strategies
Session 2

Prompt Creation, Evaluation, Iteration and Refinement Process

Session 2. Prompt Creation, Evaluation, Iteration and Refinement Process

2.1 Prompt Creation Process
2.2 Prompt Refinement Process
2.3 What can we do to improve the results?
2.4 Prompt Evaluation (intro)
2.4 Prompt Evaluation Elements
2.5 Prompt Evaluation: Building the right test sample
SESSION 3

Prompt Evaluation

Session 3. Prompt Evaluation

3.1 How to Evaluate Prompts Effectively
3.2 Evaluation Pipeline
3.3 Recommendation
3.4 LLM as a Judge
3.5 Metrics for Classification Models (MTQE)
3.6 Risk Balance
3.7 Human Evaluation
3.8 Key Ideas & Recommendations
Meet

Andrés Romero

Andrés is a proficient language technology expert with over a decade of experience in the Localization Industry.
Throughout his career, he has held diverse roles, such as CAT Tool Specialist, Localization Engineer and Operations Technology Coordinator, where he led a team of localization engineers.
Currently at Acolad, Andrés focuses on machine translation evaluation and engine training. He is also deeply involved in prompt engineering and Generative AI, proposing AI-driven driven solutions to deliver tailored, customer-centric solutions and to tackle challenges in Production.
Andrés is passionate about automating and optimizing processes to enhance productivity and efficiency, improving quality and integrating innovation into localization workflows.
Andrés Romero - Course Creator & Host