Practical Methodology and Ethics in AI
Completed by William Noble McKinney
August 16, 2025
6 hours (approximately)
William Noble McKinney's account is verified. Coursera certifies their successful completion of Practical Methodology and Ethics in AI
What you will learn
Learners will gain hands-on experience training and debugging deep learning models while considering deployment challenges and best practices.
Students will understand and evaluate ethical concerns in AI, including bias, fairness, and the societal impact of deploying neural networks.
Learners will explore how to integrate structured probabilistic models with deep learning, reducing uncertainty and improving model decision-making.
Skills you will gain
- Category: Artificial Neural Networks
- Category: Responsible AI
- Category: Deep Learning
- Category: Bayesian Network
- Category: Model Evaluation
- Category: Machine Learning Methods
- Category: Artificial Intelligence
- Category: Ethical Standards And Conduct
- Category: Data Ethics
- Category: Bayesian Statistics
- Category: Model Training
- Category: Model Deployment
