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Data Literacy Essentials: Augmented Analytics Best Practices
This course will teach you some of the best practices to effectively implement augmented analytics initiatives in your organization.
What you'll learn
The ability to manage and understand data has been an increasingly important skill that is vital to any organization in the present times. However, data nowadays has been increasingly becoming complex and difficult to understand and subject to risk and bias. In this course, Data Literacy Essentials: Augmented Analytics Best Practices, you’ll learn how to ensure ethical implementation of augmented analytics in your organization. First, you’ll explore what ethics in augmented analytics is, its relevance and the key areas to address for a proactive approach in ensuring ethical implementation. Next, you’ll discover data bias, its different types, and corresponding mitigation strategies. Finally, you’ll learn how to understand the concept of Explainable AI, its relevance, considerations to drive desirable outcomes with it as well as the primary concerns that drive the need for Explainable AI. When you’re finished with this course, you’ll have the skills and knowledge that will help you ensure ethical implementation of augmented analytics in your organization.
Table of contents
- Augmented Analytics Concept: Artificial Intelligence, Machine Learning | 7m 7s
- Augmented Analytics Concept: Augmented Analytics | 2m 38s
- How Augmented Analytics Work | 2m 8s
- Augmented Analytics Benefits and Relevance in Decision-making | 5m 16s
- Augmented Analytics Industry Applications | 2m 52s
- Augmented Analytics Implementation Best Practices: Aligned to KPIs, Prove Success | 3m 38s
- Augmented Analytics Implementation Best Practices: Transparency and Culture | 5m 25s
- Use Case: Identification of Augmented Analytics Implementation Best Practices | 5m 46s
About the author
Co-founder & Strategy Lead – AtoANI & AtoANI BioPack Education: Chem. Eng., MBA Corporate Experience: Strategy, Digitalization, Innovation, Finance, Material Management, Quality Assurance
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