
An introduction to the course, the topics we’ll cover, and how your expertise can directly contribute to the future of AI. You’ll also learn how micro1 helps connect professionals like you to meaningful data work.
This lecture explores the limitations of raw data and the increasing need for human insight. You’ll see how your domain knowledge contributes to improving AI outputs and why top companies are turning to experts for this work.
You’ll learn how LLMs generate responses, what tokens are, and how models are trained—from pretraining to post-training phases. This lecture also covers tools like chain-of-thought prompting and why expert guidance is needed to help models reason effectively.
This lecture breaks down the types of tasks human contributors perform—from ranking outputs to identifying edge cases—and explains how micro1 ensures quality through structured teams, continuous review, and task accountability.
This lecture explores the real-world risks of poorly trained AI systems and explains why expert feedback is critical in high-stakes industries like law, healthcare, and finance. You'll also learn about micro1’s value proposition and how expert-labeled data supports better AI development.
This lecture offers a forward-looking view of the field, including AGI and its limitations. You’ll explore how expert review remains essential, how regulation is shaping the space, and how your input helps maintain alignment with real-world needs.
A practical walkthrough of what it means to work on expert-in-the-loop projects. You’ll learn how to rank and review model responses, recognize common issues, and communicate your reasoning clearly.
A summary of key concepts and a reflection on your future role in AI development. You’ll be invited to get started on real projects through micro1 and see how your work can influence the next generation of AI systems.
Artificial intelligence systems are only as strong as the data they learn from — and increasingly, that data comes from real people with real expertise. This course explores how domain professionals are helping shape the future of AI by contributing their knowledge to train, evaluate, and guide large language models (LLMs) at scale.
Whether you're a lawyer, researcher, analyst, developer, or financial expert, you'll learn how your skills can be applied to the growing field of human data work. We’ll cover what LLMs are, how they’re trained, and where human input fits into the process, especially during post-training stages like reinforcement learning from human feedback (RLHF). You’ll also explore examples of tasks that require human judgment, what makes this input valuable, and how models learn from it.
Through the lens of micro1, a global platform that connects certified professionals with cutting-edge AI projects, this course also introduces how talent are selected, what certification looks like, and what kinds of opportunities are available.
By the end, you’ll have a clear understanding of how your expertise can help shape the behavior, accuracy, and safety of AI systems used around the world, and how to get involved through micro1.
No prior AI experience required.