At a Glance

Name: Compare DeepSeek-R1 vs OpenAI o3-mini on Data Science tasks
Price: Free CAD
Rating: 5.0 (7 reviews)
Author: hailey_quach, karan_goswami, victoria_nadar, ricky_shi, wojciech_fulmyk

This project compares OpenAI o3-mini versus DeepSeek-R1 across key data science workflow tasks like feature engineering, model selection, and error correction—evaluating cost, speed, and accuracy. Find the best model for your needs in under 30 minutes! No credit card, no hassle—just hop into our AI Classroom and start running your own experiments instantly. Test, compare, and refine insights for free!

Imagine you’re working on a data science project, and you need AI assistance—whether it’s for data cleaning, feature engineering, or debugging your code. You turn to large language models (LLMs) like OpenAI o3-mini and DeepSeek R1, but how do you know which one is the best fit?

AI reasoning models are a hot topic in today’s world, with claims of superior problem-solving abilities and efficiency. But are they really all the same? Do some models think faster? Are others more accurate or cheaper to use? In this hands-on tutorial, we’ll put these models to the test across key stages of the data science workflow to help you decide which AI model can best support your work.

With our AI Classroom, you can find out for yourself—quickly, easily, and at no cost. No credit card, no setup, no guesswork. Just log in, test models side by side, and make data-driven decisions in minutes.

Project Overview

This project is designed to compare the reasoning abilities of OpenAI o3-mini and DeepSeek R1 in practical data science tasks. Instead of learning data science itself, you’ll focus on how well these AI models understand, process, and assist with different steps in a data workflow.

You'll evaluate both models based on:
✅ Speed – Which model generates responses faster?
✅ Cost – Which model is more cost-effective to use?
✅ Accuracy – Which model provides better and more correct answers?

Using the AI Classroom, you’ll conduct side-by-side comparisons of how these models perform in error correction, feature engineering, model selection, and more.

By the end, you'll have a data-driven perspective on which model is better suited for AI-assisted data science.

What You’ll Learn

By completing this project, you will:

Understand how different reasoning models perform across real-world tasks.
Learn how AI can assist in data science workflows (but also its limitations).
Compare cost, accuracy, and efficiency of LLMs in a structured way.
Gain hands-on experience using the AI Classroom for model benchmarking.

Who Should Do This Project?

This project is for anyone curious about AI’s role in data science and wants to compare different reasoning models before integrating them into their workflow. It’s especially useful for:

Data scientists & ML engineers evaluating LLMs for their work.
AI enthusiasts & researchers interested in model comparisons.
Tech professionals & developers looking to incorporate AI into data-driven projects.
Students & learners wanting to understand how AI reasoning models differ.

No extensive programming experience is needed, as this project focuses on prompt engineering and AI reasoning, rather than coding from scratch.

What You Need

Before starting, make sure you have:
✅ No setup required – Just open the AI Classroom and start testing!
✅ Basic knowledge of data science workflows – No need to be an expert, but familiarity helps!
✅ Curiosity & willingness to experiment – The best way to learn is by testing and drawing your own conclusions!
✅ A current version of web browers: Chrome, Edge, Firefox, Internet Explorer, or Safari for the best experience.

By the end of this project, you’ll have a clear understanding of how OpenAI o3-mini and DeepSeek R1 compare, allowing you to choose the best model for your AI-assisted data science tasks.

Offered By: IBMSkillsNetwork

Compare DeepSeek-R1 vs OpenAI o3-mini on Data Science tasks

At a Glance

Project Overview

What You’ll Learn

Who Should Do This Project?

What You Need