Improve your project’s chance of success by avoiding common failures in AI and data science projects
The focus of this one day workshop is on the key concepts that are required to avoid common failures in AI and data science projects and initiatives. The workshop is aimed at current or aspiring leaders and managers of AI and machine learning teams and functions. The workshop includes basic hands-on exercises, as well as interactive, facilitated discussion, and an opportunity to spend time with Eugene Dubossarsky, who has two decades of practical, commercial experience in the field.
Topics covered include:
- What is, and isn’t AI, machine learning and data science.
- The KPI of data analytics: what it is, why it matters and how “if you can’t measure it, you can’t manage it” applies to AI. Plus you will gain basic, hands-on experience in working with this method.
- The management of data science projects and functions, and how it differs from regular IT, BI and other projects.
- Key differences in the activity, work style, personality and required management of developers/engineers and data scientists.
- The role of the sponsor, manager, team leader in AI and data science functions.
- You can avoid common failures in AI and data science projects – this workshop allows you to benefit from the experience of countless others’ failures, improving your chances of success.