Recently we kicked off a TWIML study group so that folks interested in taking the IBM AI Enterprise Workflow courses on Coursera could collaborate and support one another.
Each of the courses in the six-course series is two weeks long (plus another two weeks at the end for a capstone project), and we just completed the second week of the first course. Woohoo! In this post, we’ll recap some of the key concepts we discussed in the first couple of study group sessions and share various resources including the videos and slides from the sessions.
The first week of the course focused on reviewing the course structure and discussing some high-level introductory topics like:
- Design thinking
- Data collection
- Prioritizing opportunities
- The scientific method
- Gathering data
We had a lively discussion about these concepts, which you can check out here:
You can also download the slides.
The second week of the course dug a bit deeper into what is undoubtedly one of the first steps of any machine learning project--data ingestion. Other topics discussed include:
- ETL, etc.
- Data science vs data engineering
- Sparse matrices
- Data testing
- Automation of data ingestion pipelines
If you missed the live session, the video is below:
Slides for the week 2 discussion are here.
While we’ve completed the first course in the sequence, it’s not too late for you to join in the fun! Visit twimlai.com/aiew for details on joining the study group. We'd love to have you with us!