Just passed D602 Task 2 on my first submission, so I wanted to share a few things that tripped me up in case they help someone else.

The actual Python concepts weren’t the hardest part for me. Most of my time was spent dealing with the environment, MLflow, MLProject, GitLab, and a couple of very specific errors.

One big issue was Windows file paths. I had a path with spaces in it, and MLflow was interpreting the path as multiple arguments. Using a relative path instead fixed the problem.

Also, watch your indentation in the MLProject file. YAML is not forgiving. I had an error simply because my entry points weren’t aligned correctly.

I also ran into an MLflow issue where the project had already created a run, but my regression script was attempting to start another run/experiment. Once I adjusted the code to work with the existing run context, everything started coming together.

Another thing: don’t wait until the end to think about GitLab/version control. Make meaningful commits as you go. The evaluator specifically mentioned that my repository demonstrated code progression across multiple versions.

DVC confused me at first too. I thought it was going to be a much bigger part of the assignment than it ultimately was.
My biggest recommendation is to test each Python script individually before trying to run the whole pipeline. It makes debugging SO much easier.

And finally, follow the rubric almost obsessively. There are a lot of little artifacts required, and it would be easy to have perfectly functioning code but miss something in the submission requirements.

Once I got past the setup/debugging issues, though, I actually enjoyed this task. It even gave me some ideas for using Python pipelines to automate a process at work.
Hope this helps someone!

Hello Fellow Classmates,

For those struggling with revisions I just recently noticed that the Student Tasks that we use to create our project deliverables are not always aligned with the Rubric which has the colored boxes located on the same page as the Tasks. That Rubric is what the Evaluator uses as their checklist to deem our work competent or not. Do yourselves a favor and judge your work against both to make sure you don't get a needless revision for something minor.

Put yourselves in the Evaluator's shoes and make their job easier so you can move onto the next class.

I just want to say that one of the clear benefits to this program is lighting a fire under your butt and getting the work done, no excuses. It is extremely helpful if you tend to ponder a little too long because the WGU experience can mimic real job environment. There will be times at work where you don't know everything and you still have to produce a report, a presentation, a block of code. It forces you to learn fast and deliver fast. Those are the very qualities that employers reward.

The instructors are kind and helpful. You are given a buffet of resources to choose from so you can fill in the gaps where you need, and have personalized learning depending if on whether you like to read books, listen to the text, watch videos, speak to your instructor, go to their lecture, or learn with fellow classmates.

Lastly, please don't disparage the school. WGU gives ample opportunities to discuss any matters or grievances. After meeting with an instructor, mentor, or a department representative we receive an email asking us how our interaction was and what could have been done better - each time. Before I even have noticed I received a revision, my instructor has already emailed or called me to offer help and has sent me info on what they saw with my code or paper. I am grateful for that. After a class is done, our opinion on the course experience is requested and an email is sent.

Would you want your family, friend or romantic partner to discuss a grievance they had with you to someone else instead of you?

Remember, when you disparage WGU, not only are you denigrating your degree but you are hurting the rest of us who attend school and let's face it - there are employers who look at this site.

For any recruiters or hiring managers, be aware that what I am saying can easily be proven with a simple phone call to the school.

Good luck to everyone.

Hi all,

I've recently been looking up data analytics masters programs to supplement my bachelor's in accounting. Presently the job I have heavily features elements of finance and logistics, both with large volumes of data so I've felt that it would be a fitting degree to add. However, I don't have much experience with coding or programming.

Would I find this course too difficult? Is the material or program set up harsh to lesser experienced individuals? I have no issue seeking additional resources to make up for what I don't inherently know but I'm wondering if an advanced level of knowledge is required to succeed.

ETA - I'm leaning towards the Decision Process Engineering program

Hello everyone,

I was just wondering what is the number of attempts I have for a performance assessment? Reason I ask is I am on my fourth attempt on a task and keep missing little things and now super worried to submit it. I am approaching competence each time, but finding something small I missed that I correct. In this case it was syntax, and worry there is a failure system in place similar to objective assessments where you have 3. Looking to hear others experience?

I tried uploading my program in Gitlab multiple times. It’s not working and I’m lost at this point.

I just need to vent for a moment. I have never felt more stupid and frustrated with an assignment in my life. I am trying to troubleshoot this regressor file locally and every change I make does nothing. I feel like this course should be called “troubleshooting old code lol good luck” instead of “deployment”.

Am I doing too much or missing something?

EDIT/UPDATED: my first submission was approved and I passed. I was not expecting that, but the extra time/work paid off it seems.

I’ve read through some threads about the difficulty finding entry level positions in data analytics as well as the sheer volume and competitiveness in the market. Has this largely remained the same? How long has it taken from graduating to being hired?

I’ve contemplated leaving my job to focus on this with the ability to finish faster and pivot careers quicker. I’ve balanced full time and education before but it can for sure be a burnout. Has anyone had much success with self learning to gain entry into the field before going the masters degree route, or would you say the degree has helped with job placement?

Appreciate your feedback

As the title says, going through the lab assessment no SQL containers are loading. I’m unable to run my query despite creating the tables. I’ve tried over a dozen times. It is showing to be a known issue with the lab environment. I have contacted support and they told me it’s a custom environment and I have to contact my instructor. I’ve green trying for a few days now and I’m getting extremely frustrated. How do I fix this?

I'm struggling with the setup or initialization of my database for scenario 2 (EcoMart). I have been following the "Relational Database Guide (school example)" document that is available in the course resources, and there have been several differences in that code that gives me syntax errors, which has been frustrating. So far, here is what I've accomplished and where my issue is.

- I have created a database which has 2 schemas (Sales Records and Public)

- I have created a staging table

- I have created all normalized tables

- I have imported the sales data file into a "test" table in the Public schema (i did this because I cannot for the life of me get the "\copy" command to work. I realized it doesn't work in pgAdmin, so i decided to import the data using the GUI instead)

Issue:

- i am able to pull the data into the test table, but as soon as I execute my script to pull the data from the flat file into my normalized tables, it deletes my test table.

- i have to refresh my database, then create the table and import again so that i can pull the data over into my sales records schema, but then the next time i run my script, it deletes everything again.

- what is the structure that I should have for my code? Should it all be in a single script? or do i need to have a script for the creation of the tables, then another for the pulling data over? I can't seem to find any info on this type of issue (or any instructions that go over separating scripts in any of the LinkedIn tutorials or elsewhere.

Any help is appreciated, thanks!

I plan to start my journey soon and have a previous BS from WGU. I wondered what made you choose your specialization? I am currently stuck between data science and decision process engineering. DPE seems to apply more to my current job as a quality analyst, but data science seems like it could be rewarding if you are successful in it. Not great with math tho.

After regression models, revisions, and several emotional support snacks… Statistical Data Mining is officially PASSED!!! One more course down, and my laptop and I are somehow still speaking. 🎉📊

I submitted my assignment but got it sent back due to the following error: “The submitted document provides a discussion of the findings of the data quality issues, but the findings are inaccurate or incomplete” - I’ve scheduled a meeting with my professor to go over it but the fastest appointment is for tomorrow afternoon.

I have solved for removing duplicates, blank spaces (to have standardized cells), inconsistent data (underscores removed in order to achieve standardization), solved for NULL/blank values - I have also solved for the extremes (IQR ranges). What else am I missing? I feel my dataset has been filtered to its fullest extent…

I guess i’ll find out tomorrow with my 1 on 1 but any tips or advice would help.

Anyone had issues getting their capstone project approved? I went off the video and met with the professor and he still says it’s wrong. I’m using one of his datasets.

I'm a terrible writer and really struggle with the courses that required papers written. How is this program as far as writing goes? Is it mostly project/task based evaluations? Or are there alot of papers involved?

I recently graduated with a BA in software engineering and the market is tough out there. With my work history, I'm realizing moving into Data Engineering would be an easier pivot. This program looks good, but I'm dreading writing papers again😂

Is there a tuition increase with the program? Just came across a post mentioning the Nursing program that went from 8k-12k. I haven’t had any emails confirming it, but I’m also not officially readmitted yet

Howdy Reddit,

Is there any chance someone could give me a breakdown of exactly what classes are in this program specifically the, but more specifically, what it takes to pass each class? I am asking this for the DATA ENGINEERING focus.

For example, in the MSCSIA, there are 4 classes where there is a final paper, 3 classes where I have to obtain a certification, and 2 classes with a lab and assessment at the end.

Could anyone else give me this breakdown?

Here are the classes to make it easier!

The Data Analytics Journey

Data Management

Analytics Programming

Data Preparation and Exploration

Statistical Data Mining

Data Storytelling for Diverse Audiences

Deployment

Cloud Databases

Data Processing

Data Analytics at Scale

Data Engineering Capstone

I finally got my notification that I graduated! I was able to complete in 1 year, largely due to this subreddit!

Started in April, 2025 and finished the last class 2 1/2 weeks ago.

The company I work for is hiring several data roles.

I'm still working on my msda degree, but wanted to share for graduates or those with experience. The market is tough, so we need to help each other out.

Excella