One of the reasons this blog has been a bit quieter than usual these last few months is that I was teaching a Data Science class at General Assembly, which was rewarding but rather exhausting.
- GA is busy and dynamic. I remember back in the late 1990s at HP when every company was deploying SAP on HP-UX to avoid Y2K problems: there were classes constantly; you might discover that the class you were teaching was going to be held in the boardroom using some workstations borrowed from another city. GA was like that: every room packed from early morning until late at night.
- No-one in the class had a job as a data scientist at the beginning of the course, but there was a lot of movement within 10 weeks: job changes, promotions, new career directions. The only time in my teaching career where I saw the same wow-this-person-is-trained-now-let's-poach-them was in the early days of the Peregrine -> Service Manager transition.
- The course is mainly about machine learning but there is flexibility for the instructor to add in a few other relevant topics based on what the students want. Right now, Natural Language Processing is white-hot. Several students did some serious NLP / NLU projects. The opportunities for people who have skills in this area are very, very good.
- Computer vision is an area where there is a lot of interest as well.
I suspect by the time I've finished blogging about my past students' projects that there will be a new round of student projects to cover, so this might become a bit more of a feature on my blog.