Scope data-led ideas
Ask whether a business workflow has useful data and a measurable prediction or classification goal.
DeepLearning.AI
Machine Learning
DeepLearning.AI machine-learning training provides a foundation in supervised learning, neural networks, decision trees, clustering, recommender systems, and model-development practices.
Held by Keegan Justis →Why it matters to your business
Knowledge that supports better decisions.
Useful machine learning starts with a clear problem, suitable data and a measurable outcome. This foundation helps assess where prediction or classification could improve a workflow and design an evaluation before a model becomes part of daily operations.
Skills this credential validates
- Building regression and classification models
- Understanding neural networks and decision trees
- Using clustering, anomaly detection, and recommender approaches
- Evaluating and tuning models against data and intended use
How that knowledge helps your team
Plan a model experiment
Frame the data, evaluation criteria, and limitations to discuss before a model is put into a workflow.
Credential evidence
Keegan Justis
Chief Security Consultant & Cloud Architect
Machine Learning · DeepLearning.AI · Earned December 2023
This training is listed in Keegan’s professional background.
View professional profile →Put this expertise to work
Explore the services where this knowledge supports practical improvements for your business.
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