C10 / Advanced (foundation for C1/C2/C4)
Applied Machine Learning & Statistics for Business
Explore probability, inference & a/b testing, regression. Work through applied exercises and develop a project you can explain, test, and improve.
A certificate issued by this academy is a certificate of completion only. It is not accredited. It is not approved by the Ohio State Board of Career Colleges and Schools (SBCCS) or any other state agency. No income or employment outcome is promised.
10 modules≈135 learner hoursSelf-paced draft
YOUR TAKEAWAYS
What you will practice
- Explain the core theory of probability.
- Apply methods from regression.
- Analyze trade-offs in trees & ensembles.
- Evaluate solutions involving causal inference basics.
- Design and build ml in production.
- Produce the capstone: forecasting or churn model on real business data, defended to a human reviewer.
THE LEARNING PLAN
Inside the course
- 01Probability
- 02Inference & A/B Testing
- 03Regression
- 04Classification
- 05Trees & Ensembles
- 06Time Series & Forecasting
- 07Causal Inference Basics
- 08Neural Networks
- 09Model Evaluation & Fairness
- 10ML in Production
TRY THE MATERIAL
A little of what is inside.
EXCERPT FROM THE STUDENT MATERIAL
A sample space Ω lists all outcomes; events are subsets. Kolmogorov's axioms: P(A) ≥ 0; P(Ω) = 1; for disjoint events, P(A ∪ B) = P(A) + P(B). Consequences: P(Aᶜ) = 1 − P(A); P(A ∪ B) = P(A) + P(B) − P(A ∩ B).
Excerpt from C10. The full curriculum is not publicly downloadable in this preview.