About the Training

AI agents are changing how engineers and scientists work: reading datasheets and papers, analyzing measurement data, interpreting images and writing up results. But getting reliable, verifiable results at a reasonable cost takes more than typing a prompt. In this full-day, hands-on training, Dr. Satya Mallick, CEO of OpenCV, shows you how to put AI agents to work on real technical tasks, and how to check that they got it right.

The course follows one connected example from start to finish. Starting from a datasheet or test procedure, measurement data and images, you’ll see an agent produce a technical report backed by evidence. Computer vision examples feature throughout.

What You’ll Learn

• Getting started with AI agents: provide files, define a task, specify outputs and set clear completion criteria
• Technical documents: work with manuals, papers and datasheets, and support answers with evidence from the source
• Measurement and data analysis: generate and run Python analysis, check units, calculate results and create plots
• Images and multimodal workflows: combine images, measurements and procedures into an inspection or experimental report
• Verification and reproducibility: check calculations, citations and image-based claims against known answers, and keep reusable scripts
• Understanding and reducing costs: choose models and reasoning levels, keep context focused, reuse scripts, and limit retries and agent count
• Delegating to subagents: split independent tasks, write clear assignments, inspect the results and reconcile findings
• Integrated capstone: complete a full technical workflow, then compare a single agent with delegated work on quality, time and usage

Who Should Attend

Engineers, scientists, developers and technical managers who want to use AI agents productively on real technical work: documents, data, images and reports. Basic familiarity with Python is helpful; no prior experience with AI agents is required.

Why Attend?

AI agents can save hours on routine technical work, or produce confident-sounding mistakes. This course focuses on the practical habits that make the difference: clear task definitions, evidence-backed answers, verification and cost control. You’ll leave with techniques you can put to work right away.