FAQs: Data Science & AI/ML Course in Wellington
For Wellington learners, this course goes from raw data to a deployed model — not just a notebook exercise.
- Live cohorts, not recordings
- Practitioner-taught
- Community & placement
- Lifetime access
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Ask a question01Do I need a math background to join from Wellington?
Basic statistics helps, but the course builds up the concepts you need as you go.
02What tools does the course use?
Python, pandas, scikit-learn, and SQL, plus an intro to PyTorch.
03Is this different from the Data Analytics course?
Yes — this covers predictive modelling and ML; Data Analytics focuses on SQL, dashboards and reporting.
04Is there a capstone project for Wellington students?
Yes — a full project from raw data to a deployed model.
05How much does this data science course cost for Wellington students?
Exact fees are shared on a short intro call since pricing can vary by cohort and current offers. Wellington students should book a call for current, accurate numbers.
06How is this different from a free Kaggle course or an online ML MOOC?
Free MOOCs typically stop at a notebook with a final accuracy score. This course pushes Wellington students through the full path to a deployed model, with live feedback and MLOps basics included, so you finish with something closer to real production data science work.
07Do I need a math or programming background to join from Wellington?
Basic statistics helps, but the course builds up the concepts Wellington students need as they go. Some comfort with basic programming logic is useful before Module 1, though Python itself is taught from the ground up.
08Is there a certificate at the end of the course?
Yes — Wellington students who complete the capstone project receive a certificate of completion, along with a portfolio project going from raw data to a deployed model.
09What if I miss a live session while working through the capstone?
Sessions are recorded, so Wellington students can catch up before the next module. Since the capstone builds cumulatively, it's worth reviewing missed material promptly rather than falling multiple modules behind.
10What career outcomes can Wellington students expect after this course?
The course is aimed at analysts moving into data science roles and engineers adding ML to their toolkit, both of which typically command a premium over pure reporting or general software roles. The deployed-model capstone project is designed to be a concrete talking point in interviews for Wellington students changing roles.