Biases in AI
are a significant concern, affecting the accuracy and fairness of machine learning models. This course aims to equip learners with the skills to identify, understand, and mitigate biases in AI systems.
By the end of this program, learners will have gained a deep understanding of the impact of biases on AI decision-making and be able to develop and implement strategies to minimize these effects.
Some key concepts covered in the course include data preprocessing, feature engineering, and model evaluation, as well as techniques for detecting and addressing bias in AI systems.
Developing an awareness of biases in AI is crucial for creating more transparent, accountable, and equitable AI systems.
Join this course to learn how to manage biases in AI and contribute to the development of more reliable and fair AI models.