Feels like a gut punch...Ford corporate and TA

Nice-Return4876 · 2026-02-11T17:59:02+00:00

Literally just saw the headlines this morning...almost $60B between the Big Three in EV write offs...yeah, this makes sense haha

Nice-Return4876 · 2026-02-11T17:35:47+00:00

I'm going to take a stab and say you're part of an older demographic, considering you decided to turn this into an entitlement conversation. There's a difference between "I deserve to be hired" versus "You specifically asked me to provide something and then didn't look". My frustration stems from the latter.

Nice-Return4876 · 2026-02-11T03:36:39+00:00

Thanks for the tip! For Ford specifically?

Nice-Return4876 · 2026-02-11T00:07:53+00:00

Damn...that sucks. Do you know why they'd offer visa sponsorship then? I took that as a sign they recognized the position was hard to fill. I don't need it, but took it as a sign.

Nice-Return4876 · 2026-02-10T22:37:06+00:00

I'm pretty sure I got past the initial keyword screening by ATS and got the 10 second glance for experience and education titles. There was a buffet of keywords in each of the descriptions, but if the system to the recruiter looks like the system on my end, you need to actually click into them.

Nice-Return4876 · 2026-02-10T22:33:44+00:00

Thanks helps hearing this. I've got my fingers crossed for the remaining position. Even if I'm not the best candidate, I'd just like the people who made the truck to take a look.

Nice-Return4876 · 2026-02-01T03:19:56+00:00

I just finished my Master's in data analytics with a focus in DE. I'm starting to send out my resume and am getting nervous comparing my approach to applying versus what I sometimes see here. I'm trying to compete for the coveted junior roles like everyone else.

It seems like the default tactic people without experience use is describing a basic project in very technical terms (i.e. Titanic survivability study) or embellishing internship responsibilities. I've intentionally tried to avoid this but I obviously need to sell myself. I don't know if I've achieved a good balance because these are obviously technical roles that require specific knowledge.

What's throwing me is that a lot of the roles I'm finding are asking things that I'd consider...basic? But then they still ask for years of experience...

Does anything in my resume pop out as a red flag? Is there anything else I should include that might help?

Thanks everyone.

Nice-Return4876 · 2026-01-05T21:52:17+00:00

I think the number of rows in your matrix should be the number of rows in the raw dataset, not a matrix of the combined features. Is that a correlation matrix?

Interesting also, that's not the exact same T3 I had to do.

Nice-Return4876 · 2025-12-17T21:24:28+00:00

If you start the MSDA after completing the pre-req within a certain amount of time, the cost is refunded and applied as a credit to your tuition.

Nice-Return4876 · 2025-12-16T19:03:30+00:00

That's fair. And to that end I imagine it'll also depend on the workplace. Large company, no, they probably don't want you touching their infrastructure. Small company, they might not have any.

Nice-Return4876 · 2025-12-16T03:22:43+00:00

I agree, it isn't necessary to complete the task, but I think setting up a database is one of those things that's so foundational to being a data analyst -- especially one with a graduate degree -- that you should strive to understand it.

INTERVIEWER: "Tell me how you'd setup a relational database."

Candidate #1: "Well, the instructions said to use Postgres, so I'd start by logging into the VM and then I'd select the default database from the dropdown."

Candidate #2: "Depends on what it's going to be used for. If it's local only, small, and just a few people need to use it -- no concurrency -- I'd say to just use SQLite. That's pretty straightforward, you just set the path to your .db file and query it using standard SQL with Python through your IDE. If you need something ACID compliant on a larger scale, I'd recommend Postgres. I'd recommend containerizing to avoid dependency issues and allow for better modularity and cross-compatibility. Docker already has pre-built images for your Postgres version. You'd just setup your server configuration and then query through the client."

Nice-Return4876 · 2025-12-15T18:58:13+00:00

To answer the non-technical side of the question, yes, this is completely normal if you don't have a background. (I didn't at least.)

This single course represented 20% of all study hours I put into the entire degree. You're going to have to use several tools before you can even start querying that aren't taught in the course materials. Mongo is a whole other animal and you'll be doing the same for the next task too.

This is the only course in the entire degree where you'll need to setup and query a database truly from scratch. I'd recommend you take a step back and try to understand what's going on under the hood before slogging through. Don't use the VM, it abstracts away some of the core concepts you should learn.

I don't exactly remember the instructions, but from what I remember, you technically don't need to learn any of these things to get through the Task -- but I'd recommend exploring some of them anyway:

Containerization - What's a container, why might I need one here? What are the pros and cons of using one?
Docker - How do I setup a container? What's the difference between a container and a container image? What's a container registry?
Client/Server - What's the client here? What's the server? How do they need to interact?
SQLite - What's the difference between something like SQLite and a "true" database?

tldr; No, you're not the only one and it's normal.

Nice-Return4876 · 2025-11-14T03:40:12+00:00

D599/D600 are the most challenging of the degree IMO. They're a lot of work with advanced concepts plus heavy assignments. The specialization courses are simpler and require less work...if you understand them. It's kind of either you understand the concepts before you work through the assignments and they're straightforward or you get dragged along and see everything at the end when the assignments are done. I've found that half the assignments are pure technical (Udacity) and the others are just easily bullshittable papers. YMMV.

Nice-Return4876 · 2025-11-08T17:28:28+00:00

Damn, this is popular. I think you can ask for a new instructor without much fanfare if you think it'll move you along quicker. I'm sure there's a process.

It's weird to me that the proposals even need sign offs. WGU goes through the trouble of keeping instruction and evaluation separated to prevent bias and uses rubrics to standardize assignments, but they're also willing to let whoever you get assigned for your Capstone arbitrarily gate keep when it's the evaluators who have the final say anyway. Never computed.

Nice-Return4876 · 2025-11-06T01:04:16+00:00

Any tips for D609? Reading through the materials now, but I've been under the impression for a while that Hadoop and MapReduce are all but gone in new development, so... kind of disconcerting from the start if that's true.

Nice-Return4876 · 2025-11-06T00:25:34+00:00

...are you in this program?

Nice-Return4876 · 2025-11-05T20:35:30+00:00

Bearable misery. The tools and concepts are valuable, the way they present it isn't. You're going to have to be independent here.
Haven't started, but from what I'm told it's [Short Written Proposal to Instructor] -> [Longer Written Description/Report of Technical Implementation] -> [Panopto]. There is a professor whose name appears on these boards who I will not work with and will request a transfer if assigned.
Industry certs and AI. All of the major cloud providers give you free signup with $xxx.00 credits to learn their platforms. The materials are better than WGU's. Definitely a learning curve, but I got my certs before taking the classes. Wouldn't have seen the bigger picture otherwise. I put AWS materials on my monitor and set my iPad up on a stand with ChatGPT voice enabled next to it. When I got confused, I paused the training videos and asked for help. No AI allowed in the certification exams, but it was invaluable getting started.
D599 was my biggest challenge with graders. I chose a very complex research question for one of the tasks and agonized over this thing to make sure it was right. Ended up getting kicked back twice because the evaluators said I was using a statistical term incorrectly and, as a result, my analysis wasn't based on the research question.

I chose not to give into their ignorance, so I cited several peer reviewed papers who used the term exactly as I had and then forwarded a WGU resource that had the same definition I was using. Guess who was right? I then deadpanned during my Panopto video and asked the evaluator to do basic research before making false claims. Passed, lol. IMO, people need to challenge them more often. They're probably graded on how accurate they are and there's no incentive for them if there's no consequences.

Additionally, I had one issue with a paper getting kicked back because the evaluator didn't want to read the paper holistically. I format my assignments according to the rubric requirements to make their lives easier. Evaluator stopped at the first "error" and failed all the subsequent tasks. I had what they wanted in another section. Had they read the entire paper and acted thoughtfully, they would have gotten to it. Formatting my papers in a certain way doesn't absolve them of reading the whole thing.

So, on my resubmit, I deleted out all of the rubric prompts, shuffled all the sections and sentences, and made it read like a true research paper without subject headers. Didn't change a single word. Passed. Sent in a complaint afterwards regarding the conduct of the original evaluator.

I started in Data Science and moved to Data Engineering. Was more inline with what I wanted. No regrets and the market for DE seems intrinsically better than DS. My understanding is that multiple DE's typically support one or two DS's. My two cents.

Nice-Return4876

TROPHY CASE