AI Capstone Project with Deep Learning

IBM’s capstone moves from data handling into convolutional-model development and integration with vision transformers. The final submission brings those stages together. The provider expects completion of its preceding AI Engineering or Deep Learning certificate courses, making this a substantial consolidation project.

What you will learn

• Prepare data for a deep-learning project.
• Develop a convolutional-network model.
• Evaluate a project combining CNN and vision-transformer ideas.

Who this suits

Advanced learners who have completed the preceding courses in IBM’s AI Engineering or Deep Learning Professional Certificate program.

Before you enroll

Preview the mathematics, coding framework and exercise environment. Compare results on held-out data and investigate failure cases before deciding that a more complex network is useful.

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Put it into practice

Document the dataset split and compare the final architecture with a simpler baseline. Explain which errors remain after the additional modeling complexity.

Source and review

This overview is based on the provider's published information, checked on 12 October 2026. It is an editorial assessment, not a claim that we completed the resource. Time filters are approximate study ranges; projects and exercises can take longer.

View the curriculum and current access options at Coursera.

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