Yes - I 100% agree about your point at minute 14 where you talk about "front-loading" each class. I just finished my bachelors (and will be starting this masters program in a month) and I did this for every course. I'd start each course by spending several hours researching the course materials, chatter, instructor notes, Reddit posts about the course, etc. I'd gather all that data together and create my "study plan" listing out what resources I'd focus the most on, then include supplemental resources if I was still struggling as I got to the final exam/project for each course. This process alone sped up my completion time AND my completion clarity IMMENSELY. I no longer felt like I was wandering aimlessly through a seemingly never-ending series of resources waiting to get to the test.
Great video. Was really considering and wanted to do the university of Texas Austin computer science. But went with data analytics at WGU. Started this month already almost done with my second class. Plan to finish within the first 6 month term.
Thanks Gabe. That means a lot. Why does it matter that you said thanks? In a word: "motivation". Only about 1 in every 800 viewers respond. After 645 hours across 161 days creating 56 videos + 2 freeware tools, I've only garnered 67 subscribers, 229.9 hours viewed, < 100 tool downloads, and of course $0 of income. So looking at those sad numbers, you can understand why I appreciate your positive feedback. That is why I do this (and to build a portfolio to lock in the back half of my career). Anyhoo, back at it. Deep into installing and configuring Oracle Express, followed by My SQL, Postgresql, and free editions of SQL Server. Queuing up for several videos and articles on SQL scripts I've used over the years, plus gonna re-release to open source some old freeware titles I build years ago for WinTestGear. Cheers, - Matt Pierce
Thank you for making this video. This video is very informative and it made my decision in pursuing WGU Master’s in Data Analytics a lot easier. I am planning on pursuing this degree after my undergraduate.
I’m looking into Environmental Data Science - the WGU program is a solid foundation and speedy way to get in data analytics and I will apply within my already environmental background
IN A NUTSHELL. Tuition is charged by the term so it would benefit you if you could cram extra courses in that term. Note: Tuition is due on the first of the term. However, they will charge you $55 dollars to set up a payment plan. My strong advice is not to pay the set-up fee and just make the payments. Having not paid the full tuition will put you on financial hold which means absolutely nothing. WGU is competency-based, where once you complete and pass the assignment called performance assessment(PA), you move onto the next course. Each PA follows a rubric, has writing requirements, and goes through an evaluation process. There were 2 objective assessments which are monitored via webcam. (not kidding) Here's the crappy part, if you have questions about the rubric or the course, they insist you make an appointment with the course instructor (CI), who is usually not immediately available. There is an alternative group who you can schedule an appointment with one of them. More times than not, it has been my experience the CI is someone off in la la land and not worth the wait. Get a mentor that will call you every week and talks about you.
Question: - Is this program STEM designated? - How advanced is the math requirements for this program? Also, I don't think DA is equivalent to DS. DS is a lot more advanced and includes a lot more mathematics/statistics.
Interesting questions and points you make. Important for others to see and consider. 1. Although the WGU MS in Data Analytics touches many STEM (Science, Technology, Engineering, and Mathematics) topics (statics course, 2 data mining courses, predictive modeling course, etc.), I do not see the word STEM mentioned in the website, let alone STEM designation. Thus, I believe the answer is "no". 2. Must possess a bachelor's degreen in a STEM field or any bachelor's degree with 2+ years work experience in the STEM field. 3. DS (data science) is maybe more of an umbrella that encompasses DA (data analytics - to uncover specifics of extracted insights), but also ML (machine learning), DM (data mining), and several other disciplines. So, yeah, I agree DS can involve more math and statistics for ML and DM. I was focusing on the overlap and treating each the same for simplicity, but you are right...they are different.
Glad it was helpful. And congratulations on the BS DMDA acceptance. I am sure you will do great given that you are out putting in the effort up front to get ready by watching videos like this.
@@UnityofSpiritCommunity The WGU BS DMDA definitely will not hurt. I'd recommend signing up for all the online meet & greets, internship opportunities, resume reviews, job boards, job notifications, and other opportunities that WGU offers; right out of the gate on day 1 that you have access (I did not for various reasons). Get those little engines working for you and percolating along in the background while you are learning. Any time those "poles in the water" show a fish strike, pause and pursue that lead. If one lands you an interview and you're not yet done with school, go for it. You can always slow down or even pause your WGU school to make room for a new job / career shift because that after is the end goal. Also, suggestion - the entire time you are taking courses, try to find internships for experience (same advice if you get an internship...pause or slow down your schooling if you need to in order to get that internship on the resume...chances are they will hire you on completion and/or possibly hire you at the end of the internship then pay for your remaining schooling). Life never happens like we plan it...is always a windy road to wherever you are going. Keep your eye on that goal of career change and just ebb and flow with life to get their. Am sure you will make it as you've already lined up the schooling and are reading material and making plans. Stick to it and you'll be fine. :)
Awesome! are there any transferable credits from certificates that count as classes? if so, which ones? I heard there are two but no one has told me which ones lol
This was extremely helpful! Thank you! I am starting the program May 1st. Hoping to get it done in 2 terms but more realistically it will probably be 3. Anyways, I am curious what laptop/computer you used? I have an old mac book air and plan on buying a new laptop next week. I am having trouble trying to decide what kind to buy. Just want to make sure I have one with enough power to run programs like SQL, R and Python without any major hiccups. Any info greatly appreciated!
Thank you Wesley, I am glad the video was helpful. In 2020 when I took the courses, I was using a fairly powerful Dell PC laptop (from work) with a lot of RAM. Can't remember the specs now. I do remember that R likes a lot of RAM. I'd guess that SQL would prefer faster drives (I think all laptops come with solid state drives now). Python and R would prefer faster CPU's too. "Dr. Google" had some links that might help: * Reddit Discussion: www.reddit.com/r/WGU/comments/tnwwvp/laptop_recommendations_for_data_analytics/ * WGU MSDA Hardware Requirements: www.wgu.edu/admissions/computer-requirements.html
Great video! Can I get your opinion about this degree for someone switching careers? I have some experience working in IT but my bachelor's is in Biology. I want to do a master's degree because I would be applying for financial aid. Do you think employers would take me seriously as a Data Analyst if my undergrad isn't really relevant? Thanks!
After 13 years, my husband with an MBA is making barely more than a teacher salary. He has a great deal of experience analyzing data, but a lot that he doesn't know in the computer programming section. Would this help him pivot careers?
Thank you. I just downloaded the WGU program guide (10 pages), and a search on the keywords "SAS" no longer finds anything. I believe the SAS courses (and the difficult proctored certification) is no longer part of the program. Poked around the WGU Masters in Data Analytics website and do not see SAS there either.
Thanks for this video. I'm a math teacher with a bachelors in mathematics and considering pursuing this program. What programming and mathematical pre-requisite knowledge do i need before I enroll?
Hello Alfred, sorry on the late response (am about a month behind now on comments). Being a math teacher will give you a nice advantage for the statistics related courses. You will sail right through those. Regarding the programming courses, you should do fine on those too. All the material you need exist in the course materials, plus you can Google snippets of code and ideas as you go along. The projects are also a great way to learn the programming as you go. Bottom line, I believe you have all the pre-requisites met as a math teacher with a bachelors already done.
#1 - Agree UT Austin or Georgia Tech are more prestigious #2 - Agree cost of those two is not that much higher than WGU. For me, it came down to the flexibility of Pace. I could complete classes as fast or slow as my life obligations would allow. Many online courses synch up with regular classes where you are on a 10-11-12 week schedule, must attend or view lectures multiple times per week and must turn in homework Sunday nights. I wanted to be separate from all that and just work alone at my own pace. WGU''s flexible pace allowed me to stop all studies for a 4 week period due to an urgent work project that came up...after which picked right back up without any impact.
GTech is one of the hardest course online. They don't teach you what you are trying to learn, they expect you to know it already. You could do WGU MSDA by studying 10 hours per week; GTech expects you to do 30 hours per week. Level of effort is night and day.
Thank you Matthew! I am currently taking this course at WGU. I like the course so far. I was curious to the market value of the course. Your video helped answer some of them. You seem to be an independent entrepreneur and the course seems to have helped you in your independent projects. Just curious, did the course help you in your 40 hour work life?
Hi Maya. Thanks for watching. 1. Not really an entrepeneur. :) I do have a day job / active income to pay the bills and provide health insurance for the kids. 2. I do the DataResearchLabs as a hobby (not yet getting ad revenue from RU-vid, and even when I eventually do, it won't come close by a factor of 100x to 1000x vs. real estate passive income)...so I do it for fun and to share best practices and as a portfolio to complement the resume. 3. So happy to hear that you are enjoying the WGU course(s). I really enjoyed them too. 4. Ahh, the work-life-balance question. It is much less external factors like the WGU course, or the degree, or demands from your current job or boss. It is much more about your own internal priorities and decisions. That has been a bitter and complicated pill for me to swallow and accept. So I worked on average 65 hour a week from 1995 thru to 2019 (24 years). I got paid $0 for those extra 25 hours a week. If you run the math, 25 extra hours a week is easily 1,000+ extra hours a year times 24 years is about 24,000 uncompensated hours. Ouch. On the plus side, it yielded a good salary to put the kids thru college, buy a house, etc. On the negative side, that was time lost forever that could have been beter spent getting a masters degree (1,200-2,000 hrs), getting a PHd (8,000hr?), toodling around with the family more (priceless), etc. So yeah, in 2019 I said enough and dropped back down to a more reasonable 43-45 hr/week with occasional upshifts to 55 hr/wk or so if a project needed it. Then I spend the reclaimed time doing non-work stuff, or work stuff to sharpen my skilld like supplemental training, or learning by doing at my own pace where I can drill down until am satisfied without any time pressure (the best way to learn), or DataResearchLabs projects. I wish I'd cut back to 40-ish hr/wk a decade or so earlier. It is fine when you are young and novice and need to grow fast. It is not so good when you are older and the body doesn't like to sit for 12hr straight. Oh well, live and learn I guess. :)
Would it be *more* difficult for someone without any tech/data analytics experience? Answer = Yes. Would it be "too" difficult ... Answer = it depends, but in general No. If you really want it, and put in the time and effort you can successfully complete the degree. Other viewers have updated me that since I completed the degree, it has changed up the course plan, fewer exams and more big projects. This should reduce some of the anxiety you feel (I understand...when 50% of the courses required proctored online exams, those were all or nothing big deals).
Thank you for asking. I went ahead and posted to Github (link below) all of my detailed Study Guides for the 11 courses I took. It includes links to all the lectures, online sources, and books or other study materials. A couple of caveats though: these links may have aged out (written between Feb 2020 - Nov 2020); some of the links may be behind a paywall (eg: must be MDAC student); and since the degree courses have changed some of the links may no longer be relevant. Here's a link to the PDFs. Open each course PDF and click the "Link" word on any given bulleted line to jump to that study material. Hope this helps. :) github.com/DataResearchLabs/wgu_msda_course_study_plans
Thank you, and good question. 1. The program did cover the big 3 languages: Python, R, SAS. Was mostly focused on these and consuming files for ML work. Not much focus on database platforms nor preference in OS. 2. OS was mostly up to the individual. I used a Windows laptop, but am sure someone could just as easily have used Mac and probably even Linux if they chose. You just need to be able to submit projects in PDF many times, but sometimes in Excel which might limit OS choices to Windows and Mac. Also, the proctored exams require a small software install...I believe it favors Windows but also works on Mac...not sure there is a Linux option available for test taking. 3. Regarding data platforms, when I took the program most courses used R or Python to process data from large files; or SAS which is its own data platform the way we used it. The only course using a database was the SQL course and if I remember correctly the labs were MySQL (or maybe Oracle was an option). They definitely cover in the Oracle, SQL Server, and MySQL in the training. So this program does not require you to use one data platform over another...you really don't use databases here much (at least for the courses I took 1+ years ago--it might be different now).
@@DataResearchLabs thank you, that helps with context. Regarding Consumption: does the curriculum go over consumption of structures , specifically API JSON, or do you think that diverges into Computer science field?
No the curriculum didn't go into API calls using JSON, although I vaguely remember one or two projects making calls to publicly available APIs using JSON to fetch information. So you may at least get tangential exposure...but it is not built into the training that I recall.
How would you compare this to Eastern University's Master in Data Science program? For context, I'm looking to mostly do this for fun and supplemental learning in a growth marketing career. I mostly just want a structured path with some sort of deadlines to finish classes and having it in the form of an official degree at the end is really a bonus that I do like having. However, I don't know that it's useful to go overly in depth in every topic. I'm really just looking for a foundation to see things I couldn't see before. I admittedly like that EU ha a 10 month program as opposed to WGUs 2 year program and therefore is also cheaper.
WGU is as long or short as you want to make it, some finish in 6 months, others in 2 years or more. They are able to finish in less that 6 months because of prior courses or knowledge that enable to go much faster...Good Luck 🙂
Had to write it all from scratch. However, between the course study reading materials, suggested videos, and a bit of googling, you can find all the bits and pieces needed. Then just put it all together and test as you go along.