AI for Software Development Training in Maia

Artificial Intelligence (AI) comprises technologies that emulate human intelligence within machines and applications, facilitating the creation of smarter and more adaptable software.

This instructor-led live training, available either online or onsite, is designed for intermediate developers aiming to construct AI-driven applications using practical tools and platforms.

Upon completing this training, participants will be equipped to:

• Grasp fundamental AI and machine learning concepts.
• Create AI features utilizing Python and widely adopted libraries.
• Implement AI techniques within real-world software development projects.
• Assess models and deploy intelligent services.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical activities.
• Hands-on implementation in a live-lab environment.

Customization Options

• For customized training on this course, please contact us to make arrangements.

Huawei Ascend constitutes a range of AI processors engineered for superior inference and training capabilities.

This instructor-led live training, available both online and onsite, targets intermediate-level AI engineers and data scientists eager to develop and fine-tune neural network models utilizing Huawei’s Ascend platform alongside the CANN toolkit.

Upon completion of this training, participants will be equipped to:

• Establish and configure the CANN development environment.
• Create AI applications leveraging MindSpore and CloudMatrix workflows.
• Enhance performance on Ascend NPUs through custom operators and tiling techniques.
• Deploy models across edge or cloud infrastructures.

Course Format

• Interactive lectures accompanied by group discussions.
• Practical application of Huawei Ascend and the CANN toolkit within sample projects.
• Guided exercises concentrating on model construction, training, and deployment.

Customization Options

• To arrange customized training tailored to your specific infrastructure or datasets for this course, please contact us.

This instructor-led live training in Maia (online or onsite) is designed for intermediate-level software professionals who want to utilise AI and machine learning to boost efficiency and drive innovation in their development work.

Upon completion of this training, participants will be able to:

• Grasp the role of AI and machine learning in automating software development tasks.
• Deploy AI tools to generate code, tests, and documentation.
• Apply AI techniques for code optimization, quality assurance, and debugging.
• Integrate AI into DevOps and CI/CD pipelines to improve deployment strategies.
• Address ethical considerations and challenges associated with AI-augmented software engineering.

This instructor-led, live training in Maia (online or on-site) targets intermediate to advanced participants looking to optimise team workflows, enhance collaborative coding practices, and effectively manage Copilot usage in multi-developer environments.

By the end of this training, participants will be able to:

• Set up GitHub Copilot for team environments.
• Utilize Copilot to enhance collaborative coding practices.
• Optimize team workflows using Copilot’s features.
• Manage Copilot’s integration in multi-developer projects.
• Maintain consistent code quality and standards across teams.
• Leverage advanced Copilot features for team-specific needs.
• Combine Copilot with other collaborative tools for efficiency.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level QA engineers, developers, and team leads who wish to leverage GitHub Copilot for more efficient debugging, code quality enhancement, and streamlined code review.

By the end of this training, participants will be able to:

• Set up GitHub Copilot for debugging and code review purposes.
• Use Copilot to identify and resolve bugs efficiently.
• Enhance code quality with AI-assisted suggestions.
• Streamline code review processes with Copilot's capabilities.
• Collaborate effectively using Copilot in team environments.

Course Customization Options

Format of the Course

By the end of this training, participants will be able to:

Prompt Engineering for Software Development is a practical course designed to equip developers with the skills to craft effective prompts that enhance the usefulness, precision, and safety of AI-generated outputs within software engineering tasks.

This instructor-led live training (available online or onsite) targets intermediate-level developers who wish to incorporate prompt engineering techniques into their use of AI coding assistants, code analyzers, and intelligent automation tools.

• Create precise prompts for code generation, review, and optimization tasks.
• Use prompt chaining and refinement to improve AI responses in iterative workflows.
• Generate structured outputs such as test cases, SQL queries, and documentation from minimal input.
• Mitigate hallucination and improve control over LLM behavior in technical environments.

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

• To request a customized training for this course, please contact us to arrange.

Responsible AI in Software Development is a foundational course that addresses the ethical, legal, and governance considerations when using AI tools in the software development process. The course emphasizes transparency, fairness, intellectual property concerns, and safe deployment of AI-generated code.

This instructor-led, live training (online or onsite) is aimed at beginner-level technical and non-technical professionals who wish to ensure ethical, compliant, and risk-aware use of AI in their software projects.

By the end of this training, participants will be able to:

• Identify and mitigate ethical and legal risks associated with AI-assisted development.
• Understand bias in AI-generated code and how to evaluate fairness.
• Manage software licenses and attribution related to AI-generated content.
• Establish governance, policy, and compliance frameworks for AI use in development teams.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This practical course explores the use of generative AI to convert stakeholder feedback into structured requirements, epics, user stories, and acceptance criteria tailored for Agile development environments.

Delivered as live instructor-led training (available online or onsite), it is designed for beginner-level product and project professionals aiming to utilise tools such as ChatGPT or Claude to enhance clarity, efficiency, and traceability during requirement gathering and refinement phases.

Upon completion, participants will be capable of:

• Employing AI prompts to collect and refine business requirements.
• Transforming feature requests into clearly structured user stories and epics.
• Producing acceptance criteria, edge cases, and definitions of done with the aid of AI.
• Collaborating with development teams using documentation structured by AI.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live laboratory environment.

Customisation Options

• For a bespoke training version of this course, please contact us to make arrangements.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level to intermediate-level Python developers who wish to leverage GitHub Copilot for Python-specific tasks, debugging, and implementing machine learning workflows.

By the end of this training, participants will be able to:

• Set up and configure GitHub Copilot for Python development.
• Leverage Copilot to write efficient Python code.
• Debug Python applications using AI-generated suggestions.
• Automate repetitive coding tasks and improve workflow efficiency.
• Utilize Copilot for implementing machine learning projects in Python.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level participants who wish to customize GitHub Copilot for team projects, utilize its advanced features, and integrate it seamlessly into CI/CD pipelines for enhanced collaboration and productivity.

By the end of this training, participants will be able to:

• Customize GitHub Copilot for specific project needs and team workflows.
• Leverage advanced features of Copilot for complex coding tasks.
• Integrate GitHub Copilot into CI/CD pipelines and collaborative environments.
• Optimize team collaboration using AI-powered tools.
• Manage and troubleshoot Copilot settings and permissions effectively.

The 'Generative AI for Front-End Development' course investigates how large language models and AI-driven utilities can streamline front-end workflows. It focuses on prompt-based code generation, rapid layout prototyping, and user interface optimization.

Delivered as an instructor-led live training (available online or onsite), this programme targets beginner to intermediate front-end professionals seeking to leverage generative AI to construct and iterate user interfaces with greater speed and creativity.

Upon completion, participants will be equipped to:

• Utilize AI tools to produce HTML, CSS, and JavaScript from natural language instructions.
• Construct and refine UI components and layouts using generative models.
• Rapidly prototype responsive web designs without writing code entirely from scratch.
• Enhance front-end code through AI-driven suggestions and automated workflows.

Course Format

• Interactive lectures paired with group discussions.
• Extensive exercises and practical practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To arrange customized training for this course, please contact us.

AI-Enhanced Test Generation and Quality Engineering investigates how artificial intelligence tools and large language models (LLMs) can broaden test coverage, accelerate test creation, and refine quality assurance processes.

This instructor-led, live training (available online or onsite) is designed for intermediate-level QA professionals aiming to automate and upgrade their testing strategies using AI-driven tools and methodologies.

By the end of this training, participants will be able to:

• Generate unit, integration, and UI tests using AI tools and prompts.
• Utilise LLMs for exploratory testing, edge-case discovery, and regression analysis.
• Cluster and prioritise test failures and anomalies using AI-assisted triage.
• Integrate AI-based testing into CI/CD pipelines to improve release confidence.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Maia (online or onsite) is aimed at advanced-level developers and team leads who wish to master advanced features of Tabnine.

By the end of this training, participants will be able to:

• Implement Tabnine in complex software projects.
• Customize and train Tabnine's AI models for specific use cases.
• Integrate Tabnine into team workflows and development pipelines.
• Enhance code quality and accelerate development cycles using Tabnine's insights.

This instructor-led, live training in Maia (online or onsite) is designed for beginner to intermediate software developers who wish to integrate AI coding assistants into their development workflow.

By the end of this training, participants will be able to:

• Understand the role and capabilities of AI coding assistants in software development.
• Utilize various AI coding assistant tools to automate routine coding tasks.
• Integrate AI coding assistants into their software development lifecycle.
• Enhance their productivity and focus on more complex and creative programming tasks.
• Address ethical considerations and responsible use of AI in software development.

Devstral is an open-source framework engineered to build and operate coding agents capable of interacting with codebases, developer tools, and APIs to boost engineering productivity.

This instructor-led live training (available online or onsite) targets intermediate to advanced-level ML engineers, developer-tooling teams, and SREs who aim to design, implement, and optimize coding agents using Devstral.

Upon completion of this training, participants will be able to:

• Configure and set up Devstral for coding agent development.
• Design agentic workflows tailored for codebase exploration and modification.
• Integrate coding agents seamlessly with developer tools and APIs.
• Apply best practices for secure and efficient agent deployment.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live-lab environment.

Customization Options

• For personalized training requests, please contact us to arrange.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level developers who wish to understand GitHub Copilot's capabilities, set it up, and use it effectively to enhance their coding experience.

By the end of this training, participants will be able to:

• Understand what GitHub Copilot is and how it works.
• Set up GitHub Copilot with a supported code editor.
• Use GitHub Copilot to write, refactor, and debug code faster.
• Leverage Copilot to explore coding techniques and solutions.
• Apply best practices for integrating GitHub Copilot into daily workflows.

This technical course focuses on the application of large language models (LLMs) to enhance code quality, diminish technical debt, and automate documentation processes for software teams.

Delivered via instructor-led live sessions, either online or onsite, this training targets intermediate to advanced software professionals seeking to leverage LLMs, such as GPT, to more effectively analyze, refactor, and document complex or legacy codebases.

Upon completion of this training, participants will be equipped to:

• Utilize LLMs to clarify code, dependencies, and logic within unfamiliar repositories.
• Identify and refactor anti-patterns while enhancing code readability.
• Automate the creation and maintenance of inline comments, README files, and API documentation.
• Integrate LLM-driven insights into existing CI/CD and code review workflows.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live-lab environment.

Customization Options

• To arrange customized training for this course, please contact us.

This instructor-led, live training in Maia (online or onsite) is aimed at intermediate-level Python developers and data scientists who wish to boost their productivity with the help of Tabnine.

By the end of this training, participants will be able to:

• Install and configure Tabnine in their Python development environment.
• Use Tabnine's autocomplete features to write Python code more efficiently.
• Customize Tabnine's behavior to fit their coding style and project needs.
• Understand how Tabnine's AI model works specifically with Python code.

The AI-Driven Software Development Lifecycle (SDLC) course provides a practical exploration of how artificial intelligence can elevate every stage of the software development process. Participants will learn to integrate AI tools and techniques throughout the entire lifecycle, ranging from automating requirement analysis to enabling intelligent test generation and optimizing deployment strategies.

This instructor-led training, available both online and onsite, is designed for intermediate-level software leaders seeking to modernize their SDLC practices by adopting AI-assisted workflows and tools.

Upon completion of this training, participants will be capable of:

• Utilizing AI to transform business input into structured requirements and user stories.
• Applying Large Language Models (LLMs) to enhance code documentation, review processes, and refactoring efforts.
• Automating the generation of test cases and conducting coverage analysis using AI-powered tools.
• Implementing AI-driven monitoring and deployment decision-making within CI/CD pipelines.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• For inquiries regarding customized training for this course, please contact us to arrange.

This instructor-led, live training (online or onsite) is aimed at intermediate-level software developers who wish to boost productivity and code quality using AI-assisted coding with Cursor.

By the end of this training, participants will be able to:

• Install and configure Cursor for AI-assisted software development.
• Integrate Cursor with Git repositories and development workflows.
• Use natural language to generate, debug, and optimize code.
• Leverage AI capabilities for refactoring, documentation, and testing.

This instructor-led, live training in Maia (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to learn how to utilize the capabilities of GitHub Copilot effectively within modern development workflows.

This immersive, one-day workshop empowers software teams to integrate cutting-edge AI tools throughout the Software Development Lifecycle (SDLC). Structured as an interactive game with progressive "levels," this experience blends technical skill-building, creativity, and collaboration.

Participants will tackle real-world challenges across all stages of the SDLC — from requirement gathering and design to coding, testing, deployment, and monitoring — using AI-powered tools like ChatGPT, GitHub Copilot, and ML-based log analysis systems.

Designed for modern development environments, this workshop fosters AI fluency, team synergy, and a deep understanding of how to augment software delivery pipelines with generative AI and machine learning capabilities.

This instructor-led live training in Maia (online or onsite) targets beginner-level professionals who wish to use Replit AI to build, test, and deploy simple applications more efficiently.

By the end of this training, participants will be able to create an app from a prompt, improve code with AI assistance, manage configuration securely, and deploy a working application.

This instructor-led live training in Maia (online or onsite) is designed for beginner to intermediate to advanced-level product teams, developers, and technical business users who wish to use Lovable to build production-ready apps more rapidly, with improved structure, quality, and deployment practices.

By the end of this training, participants will be able to plan and generate functional apps, enhance user flows and data handling, implement key production features, and prepare applications for deployment and team collaboration.

The aim of this instructor-led, live training is to equip professionals without coding or technical backgrounds with the confidence to utilise Claude Code — Anthropic’s AI-driven coding and automation tool — for constructing real-world projects, automating workflows, and integrating everyday applications using plain English.

Participants will engage with the Claude app (claude.ai and Claude Desktop) to undertake practical tasks, progressing from initial interactions to linking Claude with external services via MCP (Model Context Protocol) connectors. The 7-hour curriculum includes a dedicated Live Build Session where the group collaboratively develops workflows based on real problems submitted by participants. This dynamic segment fosters prompt evaluation skills in a manner that solitary practice cannot match. By the course conclusion, every participant will have constructed a functional project and linked Claude to at least one external service.

Course Format

• Interactive lectures and live demonstrations
• Guided practical exercises following each concept (participants follow along in real time)
• Collaborative Live Build Session addressing real participant-submitted workflow challenges
• Cumulative capstone project with showcase

This instructor-led, live training aims to empower professionals without coding or technical backgrounds to confidently utilize Claude Code — Anthropic’s AI-driven coding and automation tool — to build real projects, automate workflows, and integrate everyday tools using plain English.

Participants will use the Claude application (claude.ai and Claude Desktop) to complete hands-on tasks, starting from their first interaction through to connecting Claude with external services via MCP (Model Context Protocol) connectors. By the end of the course, every participant will have built a functional project and connected Claude to at least one external service.

Format of the Course

• Interactive lecture and live demonstration
• Guided hands-on exercises after every concept (participants follow along in real time)
• Cumulative capstone project built throughout the session

This instructor-led, live training in Maia (online or onsite) is designed for intermediate-level software engineers and technical leads who wish to use Claude Code to accelerate development workflows and improve team productivity with AI-assisted coding.

By the end of this training, participants will be able to install and configure Claude Code, navigate, generate and improve code using AI, integrate AI workflows with Git, and design scalable AI-assisted processes.

This instructor-led, live training in Maia (online or onsite) targets beginner, intermediate, and advanced professionals who wish to use Bolt.new to rapidly create and enhance web app prototypes.

By the end of this training, participants will be able to: generate prototypes from prompts, refine features and interface flows, test and troubleshoot app behavior, and publish prototypes for review.

This instructor-led, live training in Maia (online or onsite) is aimed at developers who wish to use Windsurf to build features conversationally, execute terminal workflows inside the IDE, and refactor across the codebase.

By the end of this training, participants will be able to use Cascade for navigation, execute terminal commands inside the editor, leverage predictive edits, and customize Windsurf for proprietary stacks.

By the end of this training, participants will be able to:

• Master enterprise prompt architecture across 6 layers (Role, Context, Constraints, Domain Standards, Format, Examples).
• Encode business, security and compliance constraints (GDPR, EU AI Act, sector standards) directly into prompts.
• Co-build a prompt library validated, shared and governed by all teams.
• Define sustainable governance: Prompt Curator role, naming conventions, versioning, quality metrics.
• Leave with concrete deliverables: Library v1.0, Governance Charter, 30-Day Deployment Plan.

Course format for participant assessment

• Interactive multi-profile workshops (Architects, Developers, QA, Team Leaders).
• Facilitated co-construction by an architect-consultant: participants build real, operational deliverables.
• All co-built deliverables belong entirely to the client organization.

Course customization options

• To request a customized version of this training, please contact us to make the
  necessary arrangements.