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
- Augmented Analytics Concept: Augmented Analytics 3m
- How Augmented Analytics Work 2m
- Augmented Analytics Benefits and Relevance in Decision-making 5m
- Augmented Analytics Industry Applications 3m
- Augmented Analytics Implementation Best Practices: Aligned to KPIs, Prove Success 4m
- Augmented Analytics Implementation Best Practices: Transparency and Culture 5m
- Use Case: Identification of Augmented Analytics Implementation Best Practices 6m
- Significance of Investing in Augmented Analytics 4m
- Considerations in Scaling Investments for Augmented Analytics: Consideration 1 to 4 4m
- Considerations in Scaling Investments for Augmented Analytics: Consideration 5 to 8 5m
- Use Case: Identification of Considerations in Scaling Investments for Augmented Analytics Implementation 7m
- Data Literacy Definition and Cornerstones 7m
- Relevance of Investing in Data Literacy 4m
- Understanding Organizational Data Literacy Needs - Data Literacy Levels 5m
- Understanding Organizational Data Literacy Needs - Data Roles 4m
- Understanding Organizational Data Literacy Needs - Correlate Roles, Levels, and Data Literacy Gaps 3m
- Addressing Data Literacy Needs for Augmented Analytics Implementation 6m
- Use Case: Understanding and Addressing Organizational Data Literacy Needs 7m
- Data Access and Control Concept 5m
- Data Access and Control Relevance 4m
- Evaluating and Setting-up Data Access: Step 1 to 3 6m
- Evaluating and Setting-up Data Access: Step 4 to 5 2m
- Use Case: Evaluating and Setting-up Data Access – Case Scenario 3m
- Use Case: Evaluating and Setting-up Data Access - Answer 5m
- Course Summary 1m
About the author
She is the Co-founder as well as Strategy Lead of AtoANI (sustainable agriculture) and AtoANI BioPack (biodegradable packaging). She is passionate about Social Innovation and using it to contribute to the UN Sustainable Development Goals. With a Chemical Engineering and MBA Degree, her corporate experience in multinational companies involves working on various topics in the areas of Strategy, Digitalization, Innovation, Finance, Material Management, Quality Assurance, Program and Project Managem... more