I taught this course to corporate clients for three or four years before developing my own materials.
The course materials for this course and the introductory course (“Practical Python”[1]) are quite thorough, but I've always found the portfolio analysis example very hokey.
There's enormous, accessible depth to these kinds of P&L reporting examples, but the course evolves this example in a much less interesting direction. Additionally, while the conceptual and theoretical materials is solid, the analytical and technical approach that the portfolio example takes quickly diverges from how we would actually solve a problem like this. (These days, attendees are very likely to have already been exposed to tools like pandas!) This requires additional instructor guidance to bridge the gap, to reconcile the pure Python and “PyData” approaches. (Of course, no other Python materials or Python instruction properly address and reconcile these two universes, and most Python materials that cover the “PyData” universe—especially those about pandas—are rife with foundational conceptual errors.)
Overall, David is an exceptional instructor, and his explanations and his written materials are top notch. He is one of the most thoughtful, most intelligent, and most engaging instructors I have ever worked with.
I understand from David that he rarely teaches this course or Practical Python to corporate audience, instead preferring to teach courses direct to the public. (In fact, I took over a few of his active corporate clients when he transitioned away from this work, which is what led me to drafting my own curricula.) I'm not sure if he still teaches this course at all anymore.
However, I would strongly encourage folks to look into his new courses, which cover a much broader set of topics (and are not Python-specific)! [2]
Also, if you do happen to be a Python programmer, be sure to check out his most recent book,“Python Distilled”[3]!
The course materials for this course and the introductory course (“Practical Python”[1]) are quite thorough, but I've always found the portfolio analysis example very hokey.
There's enormous, accessible depth to these kinds of P&L reporting examples, but the course evolves this example in a much less interesting direction. Additionally, while the conceptual and theoretical materials is solid, the analytical and technical approach that the portfolio example takes quickly diverges from how we would actually solve a problem like this. (These days, attendees are very likely to have already been exposed to tools like pandas!) This requires additional instructor guidance to bridge the gap, to reconcile the pure Python and “PyData” approaches. (Of course, no other Python materials or Python instruction properly address and reconcile these two universes, and most Python materials that cover the “PyData” universe—especially those about pandas—are rife with foundational conceptual errors.)
Overall, David is an exceptional instructor, and his explanations and his written materials are top notch. He is one of the most thoughtful, most intelligent, and most engaging instructors I have ever worked with.
I understand from David that he rarely teaches this course or Practical Python to corporate audience, instead preferring to teach courses direct to the public. (In fact, I took over a few of his active corporate clients when he transitioned away from this work, which is what led me to drafting my own curricula.) I'm not sure if he still teaches this course at all anymore.
However, I would strongly encourage folks to look into his new courses, which cover a much broader set of topics (and are not Python-specific)! [2]
Also, if you do happen to be a Python programmer, be sure to check out his most recent book,“Python Distilled”[3]!
[1] https://dabeaz-course.github.io/practical-python/
[2] https://www.dabeaz.com/courses.html
[3] https://www.amazon.com/Python-Essential-Reference-Developers...