MLOps - Machine Learning Operations Course in New Zealand

Batches are announced in NZST (GMT+12) as well as IST. Because our trainers are based in India, the natural overlap is early morning or late evening NZST (GMT+12), which works well alongside a full-time job. If none of the running batches fit, a 1-on-1 track is built entirely around your calendar.

Fees are quoted in NZD (NZ$) equivalent on request, and international learners can pay by card or bank transfer. WhatsApp +91 9180377502 for the current MLOps - Machine Learning Operations pricing, the next batch date in NZST (GMT+12), and the 1-on-1 option.

Every session is live and interactive — live coding, screen sharing and real-time doubt-clearing with a working MLOps - Machine Learning Operations engineer, not a recorded playlist. Recordings are provided afterwards so you can revise or catch up if a session lands awkwardly in NZST (GMT+12).

In New Zealand, typical market ranges for these roles are around NZ$75,000 – NZ$95,000 at entry level, NZ$110,000 – NZ$145,000 at mid level, and NZ$155,000 – NZ$200,000 for senior and lead engineers. Actual offers depend on the employer, your experience and how well you handle the design and coding rounds — which is exactly what the 6 projects and interview prep in this course target.

Teams hiring these skills across New Zealand include Xero, Datacom, ANZ, Spark, Fisher & Paykel, Trade Me, plus a long tail of scale-ups and consultancies. The course is built around what those interviews actually test: MLOps, MLflow, Docker, real production practice, and 6 portfolio projects you can talk through in detail.

To be straightforward: our placement network and referral relationships are strongest in India, so we do not promise job placement in New Zealand. What international learners get is the part that travels — CV and LinkedIn review against New Zealand job descriptions, mock technical interviews, portfolio projects, and coaching on how these roles are interviewed at Xero, Datacom, ANZ, Spark, Fisher & Paykel and similar employers.

You receive a course completion certificate you can add to LinkedIn and your CV. Like any training certificate, it supports your application rather than replacing employer screening — in New Zealand what carries the interview is your project portfolio and how you perform in the technical rounds, which is what the live sessions are built to prepare you for.

10 weeks, with 80+ live hours and 6 hands-on projects. Prerequisites: Python & ML fundamentals (or our Data Science course), Basic DevOps concepts. If you are returning to tech or switching stack, book a free consultation and we'll tell you honestly whether to start here or a step earlier.

Cost and access to practitioners. A live, mentor-led MLOps - Machine Learning Operations course from Prakalpana costs a fraction of an equivalent bootcamp in New Zealand, and you learn from engineers who work with MLOps, MLflow, Docker in production every day. You keep your job, join live from Auckland, Wellington, Christchurch, Hamilton or anywhere else, and get an optional 1-on-1 track rather than a fixed classroom schedule.