Data Science with Python
Data preparation, exploratory analysis and visualisation: a solid foundation in data science.
Learn more →Containers, automation and the fundamentals of AWS cloud architecture.
Basic Linux and software development knowledge recommended.
Course content is tailored to your organisation's needs. All programmes can be delivered on-site at your premises or online. Participants who complete a programme receive a certificate of attendance.
No. It focuses on the DevOps and AWS fundamentals teams use day to day; it isn't official certification prep.
Git workflows, CI/CD, containerisation with Docker, core AWS services and infrastructure as code.
A working environment is needed for the exercises; one that meets your security rules is agreed in advance.
The training prepares your team. For the migration itself we can work together through our AWS Consulting service.
Answer a few short questions and see the AI training programmes that suit your team as an ordered path, with the reason for each.
Data preparation, exploratory analysis and visualisation: a solid foundation in data science.
Learn more →Classification, regression, model evaluation and feature engineering on real-world datasets.
Learn more →RAG architectures, agents and MCP, output evaluation, security and on-premise LLM deployment.
Learn more →CI/CD, model versioning, monitoring and data drift, plus LLMOps for LLM applications: keeping models reliable in production.
Learn more →Tell us which programmes you are interested in, the number of participants and the preferred format, and we will prepare a tailored proposal.