Customised in-house training

Use-case-driven learning for data analytics

Training uses your real business use cases. Participants leave with Python code they can immediately apply to their datasets or workflows.

SkillsFuture subsidy availableDesigned around your use cases

Discuss your training See our approach

Our motivation

Why customise a course?

While our standard workshops offer a solid foundation for learning Python, applying these concepts to specific, day-to-day tasks can still be challenging.

Customising a course with us bridges this gap. By integrating your organisation’s real-world use cases into the curriculum, learners can master the basics and gain the confidence to immediately apply their new skills to relevant challenges at work.

The examples and final project come from your team’s work.

We tailor courses for varying skill levels

Beginners

Learners who are new to programming and analytics.

Intermediate

Data analysts familiar with other analytical tools but not with Python.

Advanced

Data analysts familiar with Python who need an introduction to new or advanced technology and libraries, such as generative AI APIs or PySpark.

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Approach to customisation

Begin with the outcome, then design the learning.

Discovery

We speak with your team, review the work they do and choose useful examples for the course.

Training parameters

We agree the number of participants, skill levels, duration, schedule, technology constraints, learning format and how participants will collaborate.

Course design

We use one of our proven Python workshops as a base, then customise the examples, exercises and end project around your team’s work.

Common use cases

Bring the work you need to improve.

Manipulating, merging and aggregating spreadsheet data
Extract, transform and load work before visualisation in tools such as Power BI
Working with data from warehouses and file systems
Processing hard-copy documents, such as invoices, with generative AI

Featured case study

Ministry of Digital Development and Information

Helping an internal audit team identify high-risk transactions with Python and generative AI.

The team mainly used Excel to analyse transactions during internal audits. We customised a Python course around their own datasets so participants could return to work with functioning products they could apply immediately.

Identify split transactions
Find duplicate transactions
Cluster high-risk transactions

Course instructor

Brandon Ong

Lead Trainer at Sozcode

Our testimonials