Sure, sounds like the core prerequisites are Stats 1, Stats 2, a Regressions/Applied Regressions class and some algebra and linear algebra foundations. I don't think you'll need to go down the mathematical statistics path or any calculus.
If I were you I would find some online regressions/applied regressions classes that go over:
- Simple Linear Regression (SLR), ANOVA for SLR,
- Multivariate Linear Regression (MLR), ANOVA for MLR, polynomial variables, indicator variables
- Logistic Regression
- Hypothesis testing for the above and writing good conclusions
If you find some topics in the above a bit challenging, work backward from what you don't know into a Stats 2 class - which will focus mainly on SLR, ANOVA and might briefly touch on MLR. If that stuff is still a little unapproachable, jump back into a Stats 1 class - which will cover z-sore and t-score tests, distributions and some probability.
Unfortunately, I don't have any great resources for online stats courses. I haven't tested this one, but I did find one that is about a Stats 2 level, that uses R: Coursera: Linear Regression and Modeling.
I know the University of Waterloo has a good free Linear Algebra class, though I wouldn't call it a high priority for you. If you do check it out, you'll likely only need to review the first 4 lessons of the 3rd Unit and the first 2 lessons of the 4th unit: https://open.math.uwaterloo.ca/4?gid=314
Feel free to message me about any courses you find online and I can let you know how relatively useful they would be.