Choosing a Project

Focus on Problems First, Then Data

Rather than starting with a dataset and trying to find something interesting to do with it, identify a meaningful problem that could benefit from machine learning. This approach tends to lead to more impactful and realistic projects.

Look for Human Pain Points

Consider processes or tasks that are:

• Time-consuming for humans

• Tedious or repetitive

• Prone to human error

These often make excellent candidates for machine learning solutions.

Project Sources

Bring Your Own Project

If you already have a problem in mind or access to interesting data:

• Present your idea in the course or course chat

• If you have any doubts about the project, formulate specific questions and ask in the course chat

Partner with Organizations

Local companies and academic departments often have real-world problems waiting for ML solutions:

• Reach out to businesses or research groups in your area

• Inquire about data-intensive problems they're facing

• We can help you define project parameters with your partner

• If data confidentiality is a concern, you can use the NDA template provided here

Public Datasets

While convenient, using public datasets sometimes comes with limitations:

• Projects tend to focus more on model optimization than real-world implementation

• You miss valuable experience in data preparation and feature engineering

• The problem may be artificially clean compared to real-world scenarios

However, if you choose this route, consider adding complexity by:

• Combining multiple datasets

• Creating your own validation methodology

• Adding constraints that reflect real-world conditions

Data Resources

If you're looking for public datasets, here are some valuable repositories:

• ChallengeData: Datasets from real-world challenges
• Hugging Face Datasets: Collections ready for NLP and other ML tasks
• UCI Machine Learning Repository: Classic, well-documented datasets
• Kaggle: Competitive datasets with community solutions
• Roboflow Universe: Computer vision datasets
• Papers with Code: Datasets linked to research papers

Examples of Past Projects

To get inspiration for a project, you might also want to review the projects nominated for the past VDE Machine Learning Prize in 2025 presented in the document below.

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VDE Machine Learning Prize 2025.pdf

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Non-Disclosure Agreement (NDA)

If you need an NDA for data you are getting from an organization or partner, you can use the following:

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NDA_Projects_engl_v0.2.pdf

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Non-Disclosure Agreement (NDA)