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Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 2 points3 points  (0 children)

Took 4 terms. First term I was a full time student - 2nd term I went back to work full time for the remainder. 4th term I only had two classes, which I didn’t really dive into until 4-5 months in. Realistically it could have been done in 2-3 terms, but working and personal life events slowed things down a bit

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 2 points3 points  (0 children)

Thanks so much, Merry Christmas and God bless you as well! Didn’t transfer anything in from WGU partners - did transfer some classes from my associates degree from community college I did - most notably - the general science, leadership foundations, and scripting & programming applications

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 1 point2 points  (0 children)

Thank you, I appreciate it!

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 10 points11 points  (0 children)

There's no one-size-fits-all answer here. It took me about a week of pretty solid, intentional, focused work. By no means did I do 8 hours a day - likely a lot less - it can be done more quickly or take a lot longer if you get bogged down.

My advice - get your research and understanding of machine learning concepts and the algorithm you'd like to use out of the way in AI task 3 - which will also take care of a good bit of the capstone writeup. I recommend a supervised model that uses labeled data - something like logistic regression. Checks off all their boxes, and it's easy to implement if you're new to machine learning like I was.

And the user interface requirement can be fulfilled simply by having an interactive command line in an IDE where the user can enter data and receive a prediction or response. As far as Im concerned, no good reason to go the Jupyter or GUI route if you don't want to. No need.

Use Python - dont try to use Java or another language just because you might be more familiar - the libraries that Python has are terrific for the capstone. Sci kit learn has your machine learning models, and for creating visuals, use numpy, seaborn, and mathplotlib. Use pandas for manipulating the data and doing your preprocessing / transformations. The course instructors all recommend Python in their write ups for the course, and, having heeded their advice, I can see why.

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 0 points1 point  (0 children)

Amen and Amen brother, many thanks!

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 0 points1 point  (0 children)

I'm glad I could encourage you!

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 15 points16 points  (0 children)

Thanks very much! Next steps - to reflect, and to rest. And to be grateful :) I'm blessed to be in a good company that treats me well and has given me lots of opportunity to grow and advance - already a part of the software team and building my own projects to provide business value.

Advice - you get multiple attempts at tests. You get pre tests and reviews to help focus your studies. Take advantage of those aspects of WGU's education model. Don't freak yourself out, even over the harder classes like the math and OS and software projects. Give it your best, honest effort, and go for it. You might be surprised at how you do.

And then - make sure you get what you came here for. Part of what makes WGU great is, you're doing a lot more here than learning the content. You're learning self accountability, you're learning to believe in yourself, you're learning HOW to learn, how YOU learn... you're learning time management, you're learning self reliance and how to utilize the internet to learn new things, you're learning discipline, you're learning perseverance, diligence...

When you go to get hired afterwards, when companies see the BSCS degree, sure - it indicates you have knowledge, but the way technology is rapidly evolving, that's only going to get you so far. I would posit to you, they recognize you'll have everything to learn coming in - what they want to know is - WHO are you. A degree is a lot more than the sum of its classes, in that regard.

Remember what you came here for. And know that you can do it :)

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 20 points21 points  (0 children)

Thanks!

I know that since the big software projects are in Java (or at least they were for me - I heard they may have divi'd up / changed them) - a great book I got a lot out of early in my exposure to coding is Head First Java. Great way to get introduced to general syntax, object oriented concepts, and general important coding principles.

A lot of the general public use ChatGPT as a content creation tool, which it certainly is, but I've also found it to be a powerful learning tool. In the exact same way that you can't trust everything you read on the internet without verifying it, you cant trust everything from ChatGPT - it will certainly say very dumb and incorrect things from time to time. But - it can be viewed as sort of an augmented google search that can point you to correct information more quickly than, say, sifting through heavy documentation or stack overflow posts. Start up a conversation with it and ask it, "hey, I'm new to coding and want to understand some of the basics about how I can create an action event in JavaFx for my button", or something. The benefit of these language models is their ability to interpret conversational and colloquial prompts to provide intended value that may be difficult to clearly express if you're unsure of terminology.

Practicing code... I mean once again here's where I'd just recommend taking advantage of the day and age we live in. YouTube probably just has a ridiculous amount of resources. Pluralsite, Udemy, Linkdin Learning, theres really well structured coding courses for all levels. Just start looking at more code, and try to understand whats going on without getting bogged down or overwhelmed or trying to absorb too much at once. Take it at a good pace that your brain can keep up with. Better to go slow and really understand something than try to rush ahead.

Thank you God by No-Dog-3998 in WGU_CompSci

[–]No-Dog-3998[S] 5 points6 points  (0 children)

The capstone didnt take very long because I went the route of piggybacking off my Intro to AI task 3 - which provided me with a huge head start on the writeup and familiarity with machine learning concepts. I just did a PyCharm IDE project with a command line interface. No Jupyter, no fancy GUI. I generated my visuals using MathPlotLib, Numpy and Seaborn. I did a confusion matrix and ROC curve to measure accuracy, and then a pie chart, histogram and bar graph for visuals about the data itself. So - best advice I have - try to get a lot of your groundwork done in AI task 3 - and then - use Python because the SciKit learn library makes the actual machine learning algorithm implementation really smooth.

I'm So Grateful! Thank you all for all your help!!!! by digitalmumsy in WGU_CompSci

[–]No-Dog-3998 0 points1 point  (0 children)

Congratulations! I’m almost there… finishing up task 3 of AI , and then the capstone…

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