AI engineer training
AI engineering has emerged as one of the most in-demand fields in technology and business transformation. Whether it's building scalable machine learning systems or optimising complex data pipelines, AI engineers play a crucial role in shaping how businesses innovate and operate.
To help you develop your AI engineering capabilities, here is a curated list of the best AI engineering courses available right now.
The best courses for developing AI engineering skills
As revealed in the recent Nash Squared Digital Leadership Report, AI has jumped to the top of the list as the most critical skills gap in the UK, with half of UK tech leaders struggling to find talent for AI roles.
AI engineering is a key part of that gap, with talented individuals required to build and manage the AI solutions of the future.
AI engineer level 6 apprenticeship
The AI Engineer Level 6 programme can be funded through the growth and skills levy and helps businesses to embrace AI-transformation by developing specialists with the skills to design, build and deploy generative AI and machine learning solutions.
This programme is now delivered in collaboration with NVIDIA, giving learners expertise in systems powered by NVIDIA technology, and ensuring pilots move seamlessly through to production.
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Generative AI essentials course
As organisations increasingly integrate generative AI into their products, engineers who understand prompting, model behaviour and AI principles are the best place to deliver safe and scalable AI solutions.
This course provides need-to-know information about the fundamental concepts of Gen AI, including practical insights into delivering AI solutions for real-world problems.
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AI enabled software engineering course
This course is ideal for AI engineers who want to integrate generative AI into real development workflows, offering hands-on practice in using AI assistants to accelerate coding, debugging, documentation, and architectural exploration.
It teaches advanced prompting and evaluation techniques, enabling engineers to produce more reliable, structured outputs from AI tools and iterate effectively.
Learners gain the skills to confidently embed AI assistants into their daily engineering processes to boost productivity and problem‑solving efficiency.
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Gen AI engineering with Databricks
Powered through our partnership with leading data intelligence solution, Databricks, this course is perfect for AI engineers who are looking to build production-grade generative AI applications.
It highlights why Databricks is a critical platform for AI engineers, providing unified data, model serving, governance, and monitoring capabilities that streamline end‑to‑end Gen AI development in real enterprise environments.
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Building LLM apps with prompt engineering course
This course is a strong fit for AI engineers because it combines hands‑on prompt engineering with practical tooling such as NVIDIA NIM and LangChain, giving learners real experience building generative applications, document‑analysis pipelines, and chatbot systems.
By working directly with Llama 3.1 and structured LLM workflows, engineers gain the applied skills needed to design reliable, production‑ready AI features and establish the groundwork for more advanced techniques like RAG and fine‑tuning.
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AI threat modelling certificate
Security is now a core responsibility for AI engineers, as the systems they build can be exploited and compromised. This three day course equips engineering and security teams to design safer AI systems by mastering AI‑specific threat modelling using the DICE methodology, with hands‑on labs and red‑vs‑blue exercises.
Participants learn to identify vulnerabilities across the AI lifecycle, develop effective countermeasures, and align their work with standards such as the EU AI Act and the OWASP Top 10 for LLM applications.
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Agentic AI foundations
Agentic AI is becoming essential as organisations move beyond passive LLMs toward systems that can plan, reason, and take autonomous action.
This one‑day intermediate course gives teams a practical foundation in designing and deploying Agentic AI on AWS, exploring tools such as Amazon Q, Kiro, Amazon Bedrock Agents, and AgentCore to build purposeful, goal‑driven solutions.
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These programmes equip teams with the practical capabilities needed to build safe, scalable and production‑ready AI solutions. if you're looking to upskill your teams or develop future AI talent, get in touch today to explore our programmes.
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AI Engineer - Role Guide
What is an AI Engineer?
AI Engineers design, build, and put AI systems into practice. They integrate AI models with software applications to create intelligent solutions that can process information, understand and generate content, make predictions, assist in decision-making, and automate complex tasks.
Learn more about the role of an AI engineer with our guide.
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