01-20-2020, 02:39 AM
It sounds like we're mostly on the same page, but I wanted to quickly expand on the last couple of points you made...
I'd say most, if not all of the MOOC courses are college courses. At least all the ones I've taken have been. However, the courses that I am referring to are generally higher-level or deep subject-matter courses that you will not see in a competency-based CS program like those that people on this forum are looking for. Sure, if you pay top dollar to attend a top-rated CS program you'll find some of those courses available as electives, others are graduate-level courses where going deeper into theory is part of the journey.
But my point here is that if someone is interested in learning that stuff, and they don't want to spend 4-5 years and 6 figures to complete their degree, then they can always focus on getting the degree using a competency-approach and then go back and learn this stuff for free from a MOOC. If they then want to earn credit for that, they can do it with a graduate degree for less time and [probably] less money.
Most good programmers can pick up new technologies and learn new tools and techniques pretty rapidly. They have to in order to be able to grow alongside the requirements of their jobs. I know self-taught people who never took a math course above algebra who have used online resources to teach themselves everything they needed to be able to transition into roles working with AI and ML. At the same time, there are people who are abstracting the concepts necessary to implement these technologies to libraries and toolkits which allows the next generation to build applications that leverage the technologies without needing to understanding the details of how they work under the hood.
Yes, understanding the concepts and building blocks behind the technology makes better engineers, but it isn't required for everyone on the team. It depends a lot on the job. As an employer, if I need specialized knowledge I can always hire SME's to handle the heavy lifting and leave the rest of the code to the rank and file members of the software dev team. In many cases, that subject matter expertise is one key difference between a software architect and a programmer on a project team.
(01-20-2020, 01:00 AM)armstrongsubero Wrote: Its funny you mention MOOCs though. Cause many MOOCs are based on college courses. Go figure...wont it be better to take your time and learn from the course you are spending money to take in college from the get go rather than half ass it to pass, then pay money to do it again in a MOOC which is a collegs course? Waste not want not?
I'd say most, if not all of the MOOC courses are college courses. At least all the ones I've taken have been. However, the courses that I am referring to are generally higher-level or deep subject-matter courses that you will not see in a competency-based CS program like those that people on this forum are looking for. Sure, if you pay top dollar to attend a top-rated CS program you'll find some of those courses available as electives, others are graduate-level courses where going deeper into theory is part of the journey.
But my point here is that if someone is interested in learning that stuff, and they don't want to spend 4-5 years and 6 figures to complete their degree, then they can always focus on getting the degree using a competency-approach and then go back and learn this stuff for free from a MOOC. If they then want to earn credit for that, they can do it with a graduate degree for less time and [probably] less money.
(01-20-2020, 01:00 AM)armstrongsubero Wrote: The truth is software is now so complex that "esoteric knowledge" isnt so esoteric anymore. I mean few people knew what "linear regression" or "artificial neural network" was, but with AI becoming so common use, these are now very common terms and people have had to become proficent in statistics overnight. Its very hard to do anything innovative in that space without some 'esoteric' CS knowledge other than use a library of two.
Most good programmers can pick up new technologies and learn new tools and techniques pretty rapidly. They have to in order to be able to grow alongside the requirements of their jobs. I know self-taught people who never took a math course above algebra who have used online resources to teach themselves everything they needed to be able to transition into roles working with AI and ML. At the same time, there are people who are abstracting the concepts necessary to implement these technologies to libraries and toolkits which allows the next generation to build applications that leverage the technologies without needing to understanding the details of how they work under the hood.
Yes, understanding the concepts and building blocks behind the technology makes better engineers, but it isn't required for everyone on the team. It depends a lot on the job. As an employer, if I need specialized knowledge I can always hire SME's to handle the heavy lifting and leave the rest of the code to the rank and file members of the software dev team. In many cases, that subject matter expertise is one key difference between a software architect and a programmer on a project team.
Working on: Debating whether I want to pursue a doctoral program or maybe another master's degree in 2022-23
Complete:
MBA (IT Management), 2019, Western Governors University
BSBA (Computer Information Systems), 2019, Thomas Edison State University
ASNSM (Computer Science), 2019, Thomas Edison State University
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Complete:
MBA (IT Management), 2019, Western Governors University
BSBA (Computer Information Systems), 2019, Thomas Edison State University
ASNSM (Computer Science), 2019, Thomas Edison State University
ScholarMatch College & Career Coach
WGU Ambassador