Avoiding Failure in AI Projects

Best Practices and Strategies, with Case Studies and Real World Applications

Created by: Odin Academy
Process Data Scientists, Industry, Pharma

What Will I Learn?

• Strategies on how to kick-off and manage AI projects
• Tips to obtain business/process understanding to enhance business engagement
• Efficient deployment of AI projects to transform the business
• Application of FMEA and ChatGPT to assess project risks and develop mitigation plans

Requirements

• This course does not directly teach technical skills like programming, machine learning or data engineering concepts. To get the most knowledge from this course, you must already have a certain level of technical knowledge about your role in a data or AI team. It’s recommended to take this course after you are more comfortable with standard prerequisites for data analytics, data management or IT positions.

Target audience

• Anyone who wants to know about challenges of AI projects.
• Team leads and project managers involved in deployment of digital products
• Data Scientists and data engineers who want to to be aware of non-technical challenges to adjust their work
• Students who want to learn about real-world challenges of deploying an AI product
• IT professionals who support data science projects