TGS 4C Offshore
Produce a report and presentation comparing AI models and recommending how to use them to improve data accuracy.
Evaluating AI for Market Intelligence in Offshore Wind
To keep providing the most up to date, accurate and reliable data to our customers, TGS 4C needs to check the quality of data it processes about ports, vessels, or offshore wind farms. These Quality Control (QC) processes could be made more streamlined using AI.
Aims:
- Understand the role AI can play in processing large amounts of data.
- Use AI models to ensure accurate and consistent data relating to ports, vessels, or offshore wind farms.
- Evaluate different AI models (e.g.,OpenAI vs. DeepSeek) to identify the best solution for improving Quality Control (QC) processes.
- Use Python to update and maintain large datasets related to ports, vessels, or offshore wind farms.
To do this you will:
Produce a report and presentation comparing AI models and recommending how to use them. These recommendations will help improve data accuracy and streamline QC processes for the company.
Key skills and interests
- Research
- Problem solving
- Data analysis
- Teamwork
- Self-motivation
- Independent working
Company information
Address: Lakeside 300, Broadland Business Park, Norwich.
Key contact: Luke Rushbrook
Visit TGS 4C Offshore’s website for more information on the company
CREST Awards
This project has been designed to help students achieve a GOLD CREST Award. Download the CREST project guide to help you.
| File Name | File Type | File Size | File Link |
|---|---|---|---|
| CREST Project Guide | 459 KB | Download |