How to stay competitive in a world of data and algorithms
Learn how to stay competitive in an environment where data and algorithms will make the big difference.
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What will you learn:
Description
1) Analytical evolution: Big Data + Artificial Intelligence:
- Data: why are they so valuable?
- Analytical Evolution: Business Intelligence, Big Data, Artificial Intelligence
- Importance of a Data Governance policy
- What is Artificial Intelligence and Machine Learning
- What AI can and cannot do
2) How to Choose a Project for Artificial Intelligence:
- Prioritizing possible projects: business value matrix and technical feasibility / effort required
- Do a Technical Diligence: is it possible to achieve the intended objectives? We have the data What is the schedule?
- Establish success criteria
3) Workflow of an Artificial Intelligence / Machine Learning project:
- Organize data - Train the model - Test
- Seeking help: Own resources and External resources
4) Building a team for an AI project:
- Examples of required responsibilities: Software Engineer, Data Scientist, ML Specialist, CDO, CAIO
5) Setting up a cross-functional team with Business specialists:
- Training: Executive - Management Team - Technical Team
- Hackatons and Garages
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