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AI Enabled Software Engineering
- Categories:
- Software and DevOps Artificial Intelligence
- Level:
- Intermediate
- Code:
- QAAISAIS
- Exam:
- Not Applicable
Overview
Artificial intelligence is reshaping how software is designed, developed, tested, and maintained. This course explores how generative AI can be used as a practical development partner across the software engineering lifecycle.
Learners will gain hands-on experience using AI tools to support coding, debugging, documentation, and problem solving. The course places a strong emphasis on prompt engineering, helping participants produce structured, relevant, and reliable outputs from AI systems.
Through guided demonstrations, collaborative exercises, and real-world scenarios, learners will practise writing and refining prompts for common engineering tasks. They will also develop the critical thinking skills needed to evaluate AI-generated outputs and improve them through structured iteration.
By the end of the course, participants will be able to confidently integrate AI assistants into their daily workflows and use advanced prompting techniques to enhance productivity and software quality.
Prerequisites
Participants should have:
- Basic software engineering experience, including programming concepts
- Familiarity with an integrated development environment such as Visual Studio Code
- Understanding of software development practices such as debugging, testing, and documentation
- An interest in applying AI tools to improve development efficiency
Target audience
This course is designed for:
- Software engineers and developers looking to integrate AI tools into their workflows
- Engineering teams aiming to improve productivity using generative AI
- Technical leads and architects exploring AI-assisted development capabilities
- DevOps engineers and technical professionals working closely with development teams
What's included
Select your preferred way to learn:
What is Virtual?
Live, instructor-led training delivered online
Interactive online sessions led by subject matter experts. Learners join live classes, take part in discussions, and complete practical exercises from any location, making it easy to fit collaborative learning into busy schedules.
If you prefer to connect to a course that is taking place in a physical classroom, you can choose our Remote Access option. .
Best for: Teams and individuals who want expert guidance, real-time collaboration, and flexible access.
What's included?
1 Day instructor led course
6 month free access to QA learning platform
Free 6-Month Access: Learning Platform Discovery plan
Included FREE with every instructor‑led course
Get free guided access to the QA Learning Platform. Assess your skills, explore in-demand topics, and understand which areas to focus on.
Learn AI, Cloud, Data, and Leadership skills at your own pace.
Put skills into practice with hands-on Labs and Simulabs.
Validate knowledge and highlight gaps with skills assessments.
What is bespoke training?
Custom instructor-led training designed by QA to fit your needs
Tailored programmes built around your organisation’s goals, challenges, and skill levels. Delivered in the format that suits you to maximise relevance and impact.
Best for: Organisations and teams looking to target specific business priorities and capabilities with QA subject matter expertise.
Find out more about the course:
Learning outcomes
By the end of this course, learners will be able to:
- Identify high-impact use cases for generative AI in software engineering
- Explain the importance of human oversight when working with AI systems
- Configure and use an AI coding assistant within a development environment
- Write effective prompts for coding, debugging, and documentation tasks
- Critically evaluate and refine AI-generated outputs
- Integrate AI tools into day-to-day engineering workflows with confidence
Course outline
Introduction to AI in software engineering
- Overview of generative AI and its role in modern development
- Key capabilities and limitations of AI coding assistants
- Understanding AI as a development partner
- Identifying suitable use cases across the software lifecycle
Setting up AI-assisted development environments
- Overview of AI coding tools and integrations
- Configuring AI assistants in development environments
- Working with extensions and plugins
- Security and privacy considerations when using AI tools
Prompt engineering fundamentals
- Principles of effective prompt design
- Structuring prompts for clarity and precision
- Techniques for improving output quality
- Common prompting mistakes and how to avoid them
Using AI for coding and development
- Generating code snippets and functions
- Refactoring and optimising existing code
- Exploring alternative implementations
- Supporting multiple programming languages and frameworks
Debugging and problem solving with AI
- Using AI to identify and fix errors
- Analysing logs and error messages
- Step-by-step debugging with AI assistance
- Validating and testing AI-suggested fixes
Documentation and knowledge generation
- Generating technical documentation
- Creating code comments and explanations
- Producing user guides and knowledge base content
- Maintaining consistency and accuracy in documentation
Evaluating and refining AI outputs
- Assessing relevance and correctness of AI responses
- Identifying hallucinations and inaccuracies
- Iterative prompt refinement techniques
- Establishing validation workflows
Collaborative workflows with AI
- Integrating AI into team development practices
- Using AI in code reviews and collaboration
- Balancing automation with human expertise
- Ethical considerations and responsible AI use
Applying AI in real-world scenarios
- End-to-end development scenarios
- Case studies of AI-assisted engineering
- Measuring productivity and efficiency gains
- Adapting workflows for continuous improvement
Exams and assessments
This course does not include a formal exam.
Hands-on learning
Learners will complete knowledge checks, instructor-led discussions, and practical lab exercises throughout the course to reinforce key concepts and validate their understanding.
Good to know
Ready to book? Complete the form and a member of our team will be in touch shortly to discuss your options.
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What our customers are saying
“I would say the secure software engineering programme QA built, is beyond training. It is more around making transformation in the mindset of people, and this was exactly what we are looking for.”
Emil Minev
Senior Consultant & Programme Manager, Paysafe Group
“QA provides the updated and the comprehensive theory in the domain of AI/ML/DL and DevOps. Being an AWS machine learning speciality enthusiast I don't have to look for different websites or online learning platform for the course materials.”
Authenticated G2 user
Information Technology and Services
Portfolio Director
Andy Smith
Portfolio Director – Software and DevOps
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QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.
All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.
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When will I receive my certificate?
Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.