Training catalog
Explore Technology Training
Live, instructor-led online training and workshops across five technology areas. Browse the learning paths in each category and enquire about the courses that fit your goals.
Batch dates and schedules vary by course. Enquire about any learning path to hear about upcoming batches and available schedules.
Cybersecurity · 4 learning paths
Cybersecurity Training
Explore security fundamentals, defensive security practices, security operations, and emerging security challenges, with learning paths for learners building foundational knowledge and professionals developing their security skills.
Learning paths
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Cybersecurity Fundamentals
Build the core knowledge every security role relies on: how systems and networks work, the common threats, and how organisations defend against them.
- Intended level
- Beginner
Example topics
- Core security principles
- Networking and operating system fundamentals
- Common threats, malware, phishing and social engineering
- Identity and access management
- Defensive security concepts
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SOC Analyst Foundations
Learn how a Security Operations Centre monitors, detects and responds to threats, and practise the core tasks of an entry-level SOC analyst.
- Intended level
- Beginner to intermediate
Example topics
- Security operations workflows
- Log sources and log analysis
- SIEM concepts and alert triage
- Phishing analysis
- Incident investigation and response fundamentals
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AI Security
Understand how AI and LLM applications can be attacked, and how to design, test and protect them.
Also listed in AI & Generative AI
Example topics
- Security risks and threat modelling for AI and LLM applications
- Prompt injection, jailbreaks and unsafe model interactions
- Data leakage and sensitive-data protection
- Retrieval and tool-access security
- AI application security testing
- Secure design principles and security controls for AI systems
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Cloud Security
Learn how cloud environments are secured, from identity and configuration to monitoring and threat detection.
Example topics
- Cloud identity and access controls
- Security configuration fundamentals
- Logging and monitoring
- Cloud threat detection
- Shared responsibility concepts
Data Engineering
Learn to move, shape and serve data, starting with SQL and Python and progressing to cloud data platforms on Azure and AWS.
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Step 1: SQL
The language of data. Learn to query, combine and transform data with confidence.
- Intended level
- Beginner
Example topics
- Querying and filtering
- Joins and aggregations
- Common table expressions and window functions
- Data analysis and transformation
- Query performance fundamentals
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Step 2: Python for Data Engineering
Use Python to process data, automate tasks and take your first steps in pipeline development.
- Intended level
- Beginner
Example topics
- Python fundamentals
- Data structures and functions
- File handling and APIs
- Data processing and automation
- Introduction to data pipeline development
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Step 3: Azure Data Engineering
Build and operate data pipelines on Microsoft Azure's data platform.
Example topics
- Azure data platform fundamentals
- Azure Data Factory
- Azure Databricks and PySpark
- Azure Data Lake Storage
- Data pipelines, orchestration and monitoring
- Data modelling and performance optimisation
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Step 4: AWS Data Engineering
Build and operate data pipelines with Amazon Web Services data services.
Example topics
- AWS data platform fundamentals
- Amazon S3
- AWS Glue
- Amazon Athena
- Amazon Redshift
- Data pipelines, orchestration and monitoring
Learning paths are shown as a suggested progression. Prerequisites vary by course; ask us which path suits your experience.
AI & Generative AI
Explore how modern AI systems work and how to build, evaluate and secure applications on top of large language models.
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AI Engineer
From machine-learning foundations to building, evaluating and monitoring AI applications.
Example topics
- AI and machine-learning fundamentals
- Large language model concepts
- Embeddings and vector search
- Retrieval-augmented generation (RAG)
- AI application development
- Evaluation, monitoring and responsible AI
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Generative AI Development
Integrate large language models into applications, from prompting to structured outputs and tool calling.
Example topics
- Prompt engineering
- LLM APIs and application integration
- Structured outputs and tool calling
- Retrieval-augmented generation
- AI application testing and evaluation
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AI Security
Understand how AI and LLM applications can be attacked, and how to design, test and protect them.
Also listed in Cybersecurity
Example topics
- Security risks and threat modelling for AI and LLM applications
- Prompt injection, jailbreaks and unsafe model interactions
- Data leakage and sensitive-data protection
- Retrieval and tool-access security
- AI application security testing
- Secure design principles and security controls for AI systems
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AI Agents & Automation
Design multi-step AI workflows and agents that use tools, with the guardrails to run them safely.
Example topics
- Agent architecture
- Tool calling
- Workflow orchestration
- Multi-step AI workflows
- Evaluation, monitoring and guardrails
Cloud Computing
Learn the fundamentals of the major cloud providers: identity, networking, compute, storage, monitoring and architecture.
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Microsoft Azure
Core Azure services and how to design, run and govern workloads on them.
- Intended level
- Beginner
Example topics
- Cloud fundamentals
- Identity and access
- Networking and compute
- Storage and databases
- Monitoring and governance
- Cloud architecture and operations
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Amazon Web Services (AWS)
Core AWS services and how to build secure, well-architected workloads.
- Intended level
- Beginner
Example topics
- Cloud fundamentals
- IAM and networking
- Compute and storage
- Databases and managed services
- Monitoring and security
- Cloud architecture
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Google Cloud (GCP)
Core Google Cloud services, including its data and analytics offerings.
- Intended level
- Beginner
Example topics
- Cloud fundamentals
- Identity and access
- Compute and storage
- Networking and managed services
- Data and analytics services
- Monitoring, security and architecture
These learning paths focus on practical cloud skills. They are not official cloud-provider certification courses.
Software Testing
Learn how teams assure software quality, from test design and API testing to automation and quality engineering.
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Testing Fundamentals
Learn how software is tested and why, from testing principles and levels to writing clear test cases and reporting defects.
- Intended level
- Beginner
Example topics
- Software testing principles
- Testing levels and types
- Test design and test cases
- Defect reporting and tracking
- Testing in agile teams
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API Testing
Test the APIs that connect modern applications, checking behaviour, data and error handling.
Example topics
- HTTP and REST fundamentals
- API test design
- Using API testing tools
- Validating responses, status codes and schemas
- Authentication and error handling
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Test Automation
Automate repeatable tests so teams can release faster with confidence.
Example topics
- Automation fundamentals
- UI test automation
- Test frameworks and project structure
- Automating API tests
- Running automated tests in continuous integration
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Quality Engineering
Build quality into the whole delivery process, from planning and strategy to continuous testing.
Example topics
- Quality engineering practices
- Test strategy and planning
- Continuous integration testing
- Test reporting and quality metrics
- Working with development teams to shift testing left
Learning levels
Training for Every Stage
Our learning paths support different starting points. Ask us which path suits your experience and goals.
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Beginners and freshers
Start with foundational pathways such as Cybersecurity Fundamentals, SQL or Python.
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Working professionals
Strengthen skills you already use, or add a cloud, data or AI specialism.
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Experienced professionals
Explore advanced and emerging areas such as AI security, AI agents and cloud architecture.
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Career switchers
Get guidance on where to start and follow a structured route into a new technology area.
How training works
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Step 1: Explore
Discover the technology and learning topics that interest you.
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Step 2: Connect
Enquire about a course or register your interest in an upcoming batch.
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Step 3: Learn
Get details of upcoming batches and schedules, and join the live training that suits you.
Registering interest does not reserve a place or commit you to anything.
FAQ
Frequently Asked Questions
When do the next batches start?
Batch dates and schedules vary by course. Enquire about the learning path you're interested in and we'll share upcoming batches and available schedules.
How is training delivered?
Training is delivered as live, instructor-led online sessions and workshops. Tell us your preferred format in the enquiry form.
Which learning path should I start with?
If you are new to a technology, start with a foundational path such as Cybersecurity Fundamentals, SQL, Python or Testing Fundamentals. If you are unsure, choose "Not sure yet" in the form and we'll help you decide.
Do the courses lead to a certification or a job?
Our courses focus on practical skills. They are not official certification programmes, and we do not offer job-placement guarantees.
Why is AI Security listed in two categories?
AI Security sits between cybersecurity and AI, so it appears in both sections. It is the same learning path.
How will you use my details?
We use the details you submit only to respond to your training enquiry and to update you about the training you are interested in.
Register your interest
Enquire About Training
Choose a category or learning path and tell us a little about yourself. We'll get back to you with course details, upcoming batches and available schedules.
Registering does not reserve a place or commit you to anything.