Sunday, October 30, 2016

Udacity Machine Learning Nanodegree Udacity Connect Intensive Review PROS CONS

  • This blog post is a work in progress
  • Industry ready. Pandas, Numpy, Python are industry standards. The course gets your hands dirty right away in industry-standard competitive software packages and libraries.
  • Online contents are made by folks who actually work professionally in the field, invented things, and are top of their field. Being a good tutor is different from being a good professional. Udacity tends to have professional engineers from top tech firms. 
  • Great motivation, easy to stay on track. Past experience with Nanodegrees is that it was hard to stay on track and easy to get stuck. When a class of people is moving ahead together in person, and the classes are day long, it becomes easier to for me personally to stay on track. There are classmates who move faster as well as slower. It's easy to find help and engage in discussions before falling behind too much. 
  • Amazing in-person instructor. I have Nick Hoh. He is an experienced instructor who has a lot of teaching experience. His material supplement and even exceeds the online videos, making it very helpful study material. During his sessions he also talks about how he would approach a problem and break it down. It's helpful to get a new perspective from the online videos and it's very helpful to be able to chat in person, ask questions and chat on Slack occasionally. The help makes a big difference.
  • Offline instructor as a point of contact and a great mentor. Having that one point of contact is really reassuring. While plenty of work needs to be done through extra research and online forums like StackOverflow, having that one point of key contact makes all the difference for me. 

  • Course work seems patched together from existing Udacity courses. The content is not always cohesive. Some contents are out of date or inaccurate. Students may be stuck without additional help. For example, the Boston Housing project has a data attribute called PTRATIO. One section calls it ratio of students to teachers, another calls it pupil-student ratio. Pupil is a British word for young students in secondary schools. The actual name is pupil-to-teacher ratio. One section wants us to import a python library from a newer release using a new API call, but the Python installed on Udacity server is of an older release. Beginners will be stuck here forever trying to understand the bug is from the configuration not their code. The courses are constantly improving but the quality of the content needs to be better: more cohesive, consistent and accurate.
  • I find myself Googling a lot for external materials to study. A lot like way above 50%. While it is a common "industry practice" to google and learn additional information, above 50% also means that the course is not doing its job.
  • Lots of implicit prerequisites. While not mandatory, the course actually implicitly requires previous course work in Statistics, Probability, Linear Algebra, data analysis and Python coding. Basic statistics will be used a lot. Linear Algebra is a big part. Python coding is a must. Experience in data analysis and pivot tables. I found doing a massive and comprehensive review beforehand was very helpful. Most of my classmates are engineers. I come from an Economics background from Stanford, which thank goodness, forced me to take linear algebra

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