Udemy WIP Courses

A list of Udemy Courses currently enrolled in. Various levels of completion and priority.

Udemy won't let me rank my open courses based on my priority so I will detail them here:

1 - Vue JS 2:
I want to be operable in a "Full Stack" programming paradigm. My research, temperament and interest has led me to choose Vue JS as the Front End SPA to complete my JavaScript Stack.

2 - Isomorphic JavaScript with MEVN Stack:
**Note I have not completed this course. The 100% is based off me skimming through it**
I hope this course will have the missing link to piece together all the different parts of JavaScript to wire together that full stack.

3 - Develop a Shopping Cart Website with Django 2 and Python 3:
After taking Nick Walter's Django 2.0 course, I really enjoyed working in Django. Its "Batteries Included" Philosophy and ease of dynamic control is a tempting alternative to working in JavaScript exclusively. I would like to learn more about ecommerce, especially in payment authentication and the backend accounting side of things.

4 - Beginning C++ Programming:
Is one languageenough? I've dabbled in a few casually over the years. Python and JavaScript were my first 2 deep dives. I am feeling more confident in looking under the hood and am mapping out future language learning possibilities. The debates I read about regarding C and C++ were interesting. One of the more striking comments for me was "Learn C++ first. Then you can go back to C. You'll pick up bad habits if you do it the other way around." C++ is a bigger and more powerful language, hence my priority over C for now.

5 - Python for Data Science and Machine Learning Bootcamp:
As I detailed in another post, my foray into data science and machine learning came more from buzz and hype than genuine interest. I don't have a formal statistical background and feel a bit like a fraud for trying to learn "data science" without really understanding the fundamentals of the formulas and theories of advanced probability.

I'm 62% finished with this course though the first half is more about data cleaning and data visualization. Put another way, my work in excel helped me navigate this section quite easily, as it's basically working in a spreadsheet and visual graph-like format. I hope to eventually have more grounded knowledge in statistical probability to truly understand these advanced algorithms and be able to write more informed code.

6 - C Programing for Beginners:
After I tackle some basic to intermediate C++, I think C will become a breeze. Whether I program low level clocks and Xerox machines remains to be seen...

7 - The Ultimate Hands-On Hadoop - Tame Your Big Data!:

I like Frank Kane's teaching style. I am almost finished with his Machine Learning/Data Science course (not pictured on this blog). His presentation has helped me to understand the lingo of data science/ML and not be so intimidated by it. I still want to become more fluent in statistical probability before I deep dive but his overview of various machine learning algorithms has helped me take the next step in organizing and planning my expansion of data science knowledge.

His Hadoop course looks great for becoming familiar with the expansive ecosystem of NoSQL Databases and Big Data Management and Analysis. The only reason I place this course so low on priority is because I do not have the system specs to be able to run some of these nodes and clusters. Once I upgrade machines, I believe I'll be able to go through this course at a moderate pace.

8 - Java Programming Masterclass for Software:

I currently work at a company that is 100% Oracle based, thus having Java knowledge lingers in the back of my mind. I chose Python and JavaScript to focus on for my intro to intermediate knowledge base. This course is a whopping 75+ hours of material. Tim Buchalka's and Programming Academy have quality that can be condensed to less than 75 hours. That said his Python Masterclass was invaluable. Depending on where my job search goes, I may raise the Java priority, especially as I hear it's faster than Python. But with C++ and C# on the horizon as well, it's a tough call.

I have some other courses enrolled in but those are even lower priority that I don't find them worth mentioning right now. The trend is definitely Python and Web Development focused. I believe Big Data and NoSQL will be useful as well (I will need to review old courses on regular SQL). Then it's just a matter of deciding how fast I want to dive into a new programming language and explore data science/machine learning.