Course Description
Managers of data science teams are faced with the difficult task of managing a new and often poorly understood field. They must both understand the nature of their team’s work and translate it into business impact. They are responsible for scoping potential projects and managing the non-deterministic workflow of a data science team. Furthermore, they must be able to translate the details of their team’s work and its impact to nontechnical stakeholders.
In this course we equip data science managers with the ability to manage their team, make nuanced decisions on project direction, and communicate the impact back effectively.
We offer in-person training, as well as remote training via our Live Online technology. We are able to blend these capabilities so we can teach your entire team, even if they’re not all in one place.
Course Outcomes
Upon completion of the course, attendees should be able to:
Identify appropriate projects for a data science solution
Manage the end-to-end life cycle of a data science project, from scoping through monitoring and expiration
Demonstrate the impact of a data science project to external stakeholders
Training Content
DAY 1
Intro to Data Science in Business
- Data science landscape
- Common misconceptions
- Applications in business and your role
Modelling Basics
- Problem formation
- Modeling in practice
- Data
The Algorithms, In English
- Supervised learning
- Unsupervised learning
- Deep learning
DAY 2
Data: Error, Noise, and Spurious Correlation
- Data basics
- Issues arising from sampling and noise
Data Science Project Management
- Project workflow
- Identifying projects
Performance Measurement
- Performance metrics
- Standard data science plots
- Dashboards and suites of metrics
Data Science Project Scoping
- Technical scoping
- Nontechnical scoping
- Collaborative scoping
DAY 3
Post-production Project Life Cycle
- Monitoring
- Maintaining
- Expiring
Communicating Impact
- Storytelling
- Translating metrics and jargon
- Engagement
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