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Opiniones y comentarios de aprendices correspondientes a Introduction to Linear Algebra and Python por parte de Universidad de Howard

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This course is the first of a series that is designed for beginners who want to learn how to apply basic data science concepts to real-world problems. You might be a student who is considering pursuing a career in data science and wanting to learn more, or you might be a business professional who wants to apply some data science principles to your work. Or, you might simply be a curious, lifelong learner intrigued by the powerful tools that data science and math provides. Regardless of your motivation, we’ll provide you with the support and information you need to get started. In this course, we'll cover the fundamentals of linear algebra, including systems of linear equations, matrix operations, and vector equations. Whether you’ve learned some of these concepts before and are looking for a refresher or you’re brand new to the ideas we’ll cover, you’ll find the materials to support you. Let's get started!...
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1 - 2 de 2 revisiones para Introduction to Linear Algebra and Python

por Mohanapriya B

15 de dic. de 2022


por Miranda T

23 de dic. de 2022

True story: I owned a tiny bit of stock in Coursera, and I sold it after all the issues with this course. I'd like to note that I have taught college, so I know a fair amount about pedagogy and course design. I realize some of these problems may have more to do with the platform than the instructors. But these problems are extremely bad.

I could tell from the videos that these instructors were really knowledgeable. But there were so many serious problems with this course: First, they never gave the Python code. Ever. It was almost impossible to tell what a specific line of code was. To see the exact code, I had to pause the videos and squint. This was especially bad because the content related to Python was so rushed and weirdly paced. A whole module was devoted to just explaining Github, but only about 8 minutes of the whole course was related to the actual matrix operations necessary for the final project. The bulk of the content on which we were supposedly evaluated was barely explained and was not documented in a way that it was even possible to efficiently review it.

This next thing is not the instructors' fault, but the auto-generated transcripts were terrible for one instructor, which added to the issues with Python since I could not look at the transcripts and get a clear sense of what the coding syntax was.

In addition, the quizzes were full of many sloppy typos and formatting errors; it doesn't seem like anyone has bothered to go back and improve them or resolve those errors. It was just so unprofessional.

I struggled a lot with the final project, and I was even more disappointed to see that almost every other peer submission was just irrelevant screenshots. I felt like the instructions for the project were very poorly presented and confusing, and there was no real help out there. So to an extent, I guess I see why others might have just given up. From a pedagogical standpoint, the content was not well-scaffolded or integrated. It didn't seem like the professors worked together so much as they just threw together two related topics without thinking about how the content built on itself or how the math flowed into the Python, and vice versa.

It is a shame because I don't know what went wrong here. Did the professors just give up? Was the administration of this course delegated to someone who didn't care? Is Coursera not supporting them? How is it that just this course has such lousy implementation of coding basics like letting students see code or using Latex coding for mathematical notation in quizzes? Or... are all the classes on the platform like this?! ...That's where my thought process was and why I sold my Coursera stock. It's really sad.