AI Strategy Foundations for Data Scientists and Team Leaders
1h 8mAdvanced2024-06-13
Authors
Matthew Blasa
Course details
As AI is integrated into our world, how can experienced team leaders and data scientists level up? This course lays out AI strategy fundamentals that team leads need to succeed: the essential skills, focus, and mindsets.
Discover what AI strategy means for a team leader, and how they can align their work, teams, and drive change. This will equip you with a foundation to align with business AI strategy, scope AI problems, and execute AI projects to produce lasting value. By the end of this course, you’ll be ready to unleash your new skills to become a partner in AI strategy at your organization.
Discover what AI strategy means for a team leader, and how they can align their work, teams, and drive change. This will equip you with a foundation to align with business AI strategy, scope AI problems, and execute AI projects to produce lasting value. By the end of this course, you’ll be ready to unleash your new skills to become a partner in AI strategy at your organization.
Skills covered
Data Science FoundationsBusiness StrategyArtificial Intelligence FoundationsArtificial Intelligence for BusinessArtificial Intelligence (AI)Data ScienceBusiness Analysis and StrategyLeadership and ManagementOne-Off
Concepts
0. Introduction
- 01 - Builder to partner - Taking a strategic role in AI
1. What Is AI Strategy
- 02 - What is AI strategy
- 03 - What is your role in AI strategy
- 04 - AI strategy vs. AI plan
- 05 - Understanding the AI strategy lifecycle
2. Foundations of AI Strategy for DS
- 06 - Why the business strategy matters
- 07 - Data and technical strategy
- 08 - Why AI strategy is product focused
- 09 - Partnerships - Building to innovate
- 10 - Risk management and governance
- 11 - Handling competition
3. Planning and Operations
- 12 - Problem scoping
- 13 - Managing trade-offs
- 14 - Building teams and culture
- 15 - Continuous transformation
4. Executing AI Projects
- 16 - Bridging strategy and execution
- 17 - Setting and measuring impact
- 18 - Development the right way
5. Putting it Together - AI Strategy in Practice
- 19 - Tailoring AI strategy to industry
- 20 - AI strategy across the business
- 21 - Change management
Conclusion
- 22 - Continue to step up as a strategic partner
Related courses
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- AI Product Foundations: Planning Strategies for Data Scientists
- Data Science Foundations: Knowledge Graphs
- Data Science Foundations: Data Assessment for Predictive Modeling
- Applied AI for Human Resources
- Enhancing Your Productivity as a Data Scientist with Generative AI
Related learn paths
- Mastering Executive-Level Data Analytics
- Build Essential Data Skills
- Introduction to Fundamental Skills for Data Work: Data Strategy and Planning
- Become a Data Scientist
- Technical Literacy and Future Readiness for Senior Executives
- Moving from Data Scientist to Data Analyst
- Create a Future-Proof Organization
- Building AI Products: Understanding the Workflow Professional Certificate