EXPERT COURSE

Certificate in AI Training: LLM Specialization for Language Professionals

The Future Needs Human Experts to Train AI, Become One of Them!

As large language models (LLMs) become central to industries from localization and content creation to customer service and legal tech, the need for trained human experts to guide, correct, and improve these systems is skyrocketing.

According to LinkedIn’s 2024 Jobs on the Rise report, AI-related roles, including Prompt Engineers and AI Trainers, are among the fastest-growing in tech, with demand increasing by over 45% year-on-year.

Language professionals with specialized knowledge of how LLMs function are uniquely positioned to take on these roles, yet very few have formal training.

A Certificate in AI Training Designed to Offer Solutions

Whether you work in language, AI, or technology, this course will equip you with the theoretical understanding and hands-on skills to effectively evaluate, guide, and train LLMs using human-centered methods like reinforcement learning from human feedback (RLHF). You'll be ready to help shape AI systems that are not just intelligent, but accurate, fair, safe, and aligned with human values.

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 panellist: Almira Zainutdinova, AI Trainer and Linguistic Services Lead
  •     Live activities
  •  Lifetime access to the course and extra contents
  •  In English
  •  Certificate of completion
  •  Course duration: 6 h (approximately)
  •  When: 
     16 September (16.00 - 18.00 CET)
     17 September (18.00 - 20.00 CET)
     18 September (18.00 - 20.00 CET)
  • Downloadable webinar program

Certificate in AI Training: LLM Specialization for Language Professionals

Learn to effectively evaluate, guide, and train LLMs
using human-centered methods

Session 1: Understanding LLMs & Their Implications
Session 2: RLHF and the Human Role
Session 3: Becoming an LLM Trainer
SESSION 1

Understanding LLMs & Their Implications

Session 1

1.1 What is an LLM and how it differs from traditional models

1.2 Agents vs. LLMs

1.3 Hallucinations: causes, business risks, legal implications

1.4 How Retrieval-Augmented Generation (RAG) mitigates hallucinations

1.5 Ethical and societal considerations of LLM use

1.6 LLMs’ broad impact on humankind
Session 2

RLHF & the Human Role

Session 2

1.1 Introduction to RLHF and its technical components
1.1.1 Pre-training, reward models, policy optimization

1.2 Comparison between machine and human learning

1.3 Evaluation metrics: BLEU, BERTscale, ROUGE, BARTscale

1.4 The critical role of human linguists in LLM development

1.5 Case study: Comparing popular chatbot models
SESSION 3

Becoming an LLM Trainer

Session 3

1.1 Human-in-the-loop systems and trainer profiles

1.2 Key skillsets: clarity, bias awareness, linguistic precision

1.3 Practical tasks:
1.3.1 Crafting effective prompts (constraint-based, adversarial, etc.)
1.3.2 Classifying prompts
1.3.3 Evaluating responses using criteria: truthfulness, tone, localization, and safety
1.3.4 Preference ranking and rewrite decisions

1.4 Addressing bias in feedback and ensuring fairness

1.5 Challenges in scaling RLHF and current open questions in AI training

Course and panellist description

This course will equip you with the theoretical understanding and hands-on skills to effectively evaluate, guide, and train LLMs. The main points covered in the course are:

  • Foundations of LLMs: What they are, how they differ from traditional AI models, and their societal and business impact

  • RLHF (Reinforcement Learning from Human Feedback): Why it's essential, and how linguists play a critical role

  • The Role of the LLM Trainer: Skills, ethics, and tasks—from creating prompts to evaluating LLM outputs using precise rubrics

  • Advanced Tools & Challenges: Preventing hallucinations with RAG, case studies, bias and fairness management, and the future of scalable AI training


The course is delivered by Almira Zainutdinova, a leading expert in AI training and linguistic quality, with extensive experience in managing LLM evaluation projects across diverse industries. Her work bridges the gap between technical precision and linguistic nuance, and she is known for her engaging teaching style and real-world insights.

With Almira as your guide, you'll gain not only cutting-edge knowledge, but also practical strategies used by professionals working on some of the world’s most advanced LLMs.

Who is this course for?

This program is tailored for:
  • Linguists, translators, localizers and language professionals seeking to transition into AI-focused roles
  • AI professionals and computational linguists who want to deepen their understanding of human feedback systems
  • Tech-savvy language professionals aiming to future-proof their careers
  • Project, Program, Localization Managers and QA specialists involved in AI model development, content validation, or linguistic evaluation

If you’ve ever wondered how to apply your language expertise to AI, this course will show you how.

Resources

Linguistic skills:
  • A good English level is required.

IT resources:
  • A computer with speakers as well as a stable internet connection are necessary

Availability:
  • Life access to the recording of the webinar and extra contents when you acquire your place.
Meet

Almira Zainutdinova

Almira brings over 20 years of expertise in corporate communications, multilingual project leadership, and AI training, having collaborated with industry leaders such as Microsoft, Airbus, Caterpillar, Gazprom, Talgo, and the Democratic Institute for Human Rights.

She holds an MA in Neuroscience of Language and regularly shares insights on responsible AI, LLM safety, human bias, and the evolving human‑AI interaction, emphasizing the importance of human verification despite advancing model capabilities.

She empowers professionals, especially linguists and content creators, to bridge the gap between human nuance and machine intelligence. Her approach combines technical depth, linguistic acumen, and ethical foresight, shaped by hands‑on experience and thought‑provoking contributions in AI ethics and human‑in‑the‑loop systems.
Almira Zainutdinova - Course host
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