A few notes from Andrew Ng’s “AI For Everyone”

https://www.coursera.org/learn/ai-for-everyone

AI Strategy

• Strategic data acquisition
• Unified data warehouse
• New roles (e.g. Machine Learning Engineer)

ML tends to work well when:

• Learning a “simple” concept
• Lot of data available
• Think about automating tasks rather than automating jobs. (What are the main drivers of business value? What are the main pain points in your business?)

Key steps of a Machine Learning project:

1. Collect data
2. Train model (iterate many times until good enough)
3. Deploy model (get data back; maintain/update model)

Key steps of a Data Science project:

1. Collect data
2. Analyse data (iterate many times to get good insights)
3. Suggest hypotheses/actions (deploy changes; re-analyze new data periodically)