AI-Augmented Software Engineering (AIASE) Training Course
AI-Enhanced Software Engineering (AIASE) involves applying artificial intelligence to optimize and automate various tasks in the software development lifecycle.
This instructor-led, live training (available online or onsite) targets intermediate software professionals eager to harness AI and machine learning to boost efficiency and innovation in their projects.
Upon completing this training, participants will be able to:
- Grasp the role of AI and machine learning in automating software development tasks.
- Utilize AI tools for generating code, tests, and documentation.
- Apply AI techniques to optimize code, ensure quality assurance, and facilitate debugging.
- Integrate AI into DevOps and CI/CD pipelines to enhance deployment strategies.
- Navigate ethical considerations and challenges inherent in AI-augmented software engineering.
Course Format
- Interactive lectures and discussions.
- Numerous exercises and practical activities.
- Hands-on implementation in a live-lab environment.
Customization Options
- For a tailored training experience, please contact us to arrange your needs.
Course Outline
Introduction to AIASE
- Overview of AI in software engineering
- History and evolution of AIASE
- Key concepts and terminology
AI Technologies in Software Development
- Machine learning fundamentals
- Natural language processing (NLP) for code
- Neural networks and deep learning models
Automating Software Development with AI
- AI tools for generating boilerplate code
- Automated code refactoring and optimization
- Functional and unit test code generation
- AI-assisted test case design and optimization
Enhancing Code Quality with AI
- AI for bug detection and code reviews
- Predictive analytics for software maintenance
- AI-powered static and dynamic analysis tools
- Automated debugging techniques
- AI-driven fault localization and repair
AI in DevOps and Continuous Integration/Continuous Deployment (CI/CD)
- AI for build optimization and deployment
- AI in monitoring and log analysis
- Predictive models for CI/CD pipelines
- AI-based test automation in CI/CD workflows
- AI for real-time error detection and resolution
AI for Documentation and Knowledge Management
- Automated generation of docstrings and documentation
- Knowledge extraction from codebases
- AI for code search and reuse
Ethical Considerations and Challenges
- Bias and fairness in AI tools
- Intellectual property and licensing issues
- Future of AI in software engineering
Hands-On Projects and Case Studies
- Working with popular AI tools in software engineering
- Case studies of AIASE in industry
- Capstone project: Developing an AI-augmented software application
Summary and Next Steps
Requirements
- Familiarity with software development processes and methodologies
- Proficiency in Python programming
- Foundational knowledge of machine learning concepts
Target Audience
- Software developers
- Software engineers
- Technical leads and managers
Need help picking the right course?
uzbekistan@nobleprog.com or +919818060888
AI-Augmented Software Engineering (AIASE) Training Course - Enquiry
AI-Augmented Software Engineering (AIASE) - Consultancy Enquiry
Testimonials (1)
Shane had everything prepared well beforehand which made sure that we were able to follow up and do some hands on practice as well.
Navneet Rehsi - Tactica
Course - AI-Augmented Software Engineering (AIASE)
Related Courses
Advanced GitHub Copilot & AI for Projects and Infrastructure
14 HoursGitHub Copilot is an AI-powered code completion tool designed to accelerate development while enhancing quality and productivity. When combined with Artificial Intelligence applications in projects, infrastructure, and software, managers can leverage AI to optimize resource allocation, streamline workflows, and improve decision-making.
This instructor-led, live training (available online or onsite) is tailored for advanced-level managers seeking to deepen their expertise in GitHub Copilot while exploring practical AI applications in corporate environments, with examples relevant to large-scale projects and industries such as oil and gas.
By the end of this training, participants will be able to:
- Apply advanced Copilot functionalities in large-scale corporate projects.
- Integrate Copilot into multidisciplinary workflows for maximum efficiency.
- Leverage AI tools to optimize project management, infrastructure, and software acquisition.
- Implement AI-based strategies to improve planning, estimation, and time optimization.
- Recognize practical AI applications in industry-specific scenarios such as oil and gas.
Course Format
- Interactive lectures and discussions.
- Hands-on exercises and real-world case studies.
- Live lab demonstrations of AI tools and Copilot workflows.
Customisation Options for the Course
- To request a customised training session for this course, please contact us to arrange.
Advanced Cursor: Prompt Engineering, Fine-Tuning & Custom Tooling
14 HoursCursor is an advanced AI-powered development environment that enables engineers to extend, fine-tune, and customize its coding intelligence for specialized use cases and enterprise workflows.
This instructor-led, live training (available online or on-site) is designed for advanced-level developers and AI engineers who aim to design tailored prompt systems, fine-tune model behavior, and build custom extensions for internal development automation.
By the end of this training, participants will be able to:
- Design and test advanced prompt templates to achieve precise AI behavior.
- Connect Cursor to internal APIs and knowledge bases for context-aware code generation.
- Develop fine-tuned or domain-adapted AI models for specialized tasks.
- Build and deploy custom tools or adapters that securely extend Cursor’s functionality.
Course Format
- Technical presentations and guided demonstrations.
- Hands-on development and prompt optimization labs.
- Practical projects integrating Cursor with real-world enterprise systems.
Course Customization Options
- This course can be tailored to align with specific internal architectures, AI frameworks, or security compliance requirements.
Advanced GitHub Copilot
14 HoursThis instructor-led, live training in Uzbekistan (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.
GitHub Copilot: Advanced Agent Mode
21 HoursThis instructor-led, live training (Uzbekistan online or onsite) is aimed at developers who wish to use GitHub Copilot Agent Mode to autonomously build features, run tests, and manage larger coding tasks.
By the end of this training, participants will be able to activate Agent Mode, plan and iterate within the agent loop, execute terminal commands, and implement enterprise governance.
GitHub Copilot for DevOps Automation and Productivity
14 HoursGitHub Copilot is an artificial intelligence-driven coding assistant designed to automate various development tasks, including critical DevOps operations such as crafting YAML configurations, managing GitHub Actions, and developing deployment scripts.
This instructor-led live training, available both online and on-site, is tailored for beginner to intermediate professionals eager to utilize GitHub Copilot to streamline DevOps workflows, enhance automation capabilities, and significantly boost productivity.
Upon completing this training, participants will be equipped to:
- Utilize GitHub Copilot to support shell scripting, configuration management, and CI/CD pipelines.
- Harness AI-driven code completion features within YAML files and GitHub Actions.
- Accelerate processes related to testing, deployment, and automation workflows.
- Apply Copilot responsibly by understanding its limitations and adhering to industry best practices.
Course Format
- Interactive lectures and group discussions.
- Extensive exercises and practical practice sessions.
- Hands-on implementation within a live laboratory environment.
Customization Options
- For customized training arrangements, please reach out to us to coordinate your specific needs.
AI-Assisted Development & Coding with Cursor
21 HoursThis 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.
Cursor for Data & ML Engineering: Notebooks, Pipelines & Model Ops
14 HoursCursor is an AI-driven development environment designed to boost productivity and reliability in data and machine learning workflows through intelligent code generation, context-aware suggestions, and streamlined documentation.
This live, instructor-led training (available online or onsite) targets intermediate-level data and ML professionals looking to integrate Cursor into their daily workflows to accelerate prototyping, build scalable pipelines, and improve model operations.
Upon completion of this training, participants will be able to:
- Utilize Cursor to speed up notebook development and code exploration.
- Generate, refactor, and document ETL and feature engineering pipelines.
- Leverage AI-assisted code for model training, tuning, and evaluation.
- Enhance reproducibility, collaboration, and operational consistency in ML workflows.
Course Format
- Interactive lectures and demonstrations.
- Practical, hands-on exercises in live coding environments.
- Case studies integrating Cursor with ML pipelines and model ops tools.
Course Customization Options
- This training can be tailored to specific frameworks such as TensorFlow, PyTorch, or scikit-learn, or to organizational MLOps platforms.
Cursor Fundamentals: Accelerating Developer Productivity
14 HoursCursor is an AI-powered code editor designed to enhance developer productivity through intelligent code completions, contextual edits, and adaptive assistance.
This instructor-led, live training (online or onsite) is aimed at beginner-level developers and engineering teams who wish to streamline their coding workflow and safely leverage AI suggestions for improved efficiency.
Upon completion of this training, participants will be able to:
- Install and configure Cursor for optimal use in development projects.
- Understand and apply AI-assisted code completion, in-editor chat, and refactoring tools.
- Evaluate, accept, or modify AI-generated code suggestions effectively and securely.
- Adopt best practices for team onboarding, collaboration, and version control integration.
Format of the Course
- Interactive lecture and discussion.
- Hands-on demonstrations and guided exercises.
- Real-world coding challenges and lab practice using Cursor.
Course Customization Options
- This course can be tailored to specific programming languages or frameworks used by your team.
Cursor for Teams: Collaboration, Code Review & CI/CD Integration
14 HoursCursor is an intelligent, AI-driven development environment designed to boost team collaboration, automate code reviews, and seamlessly integrate with modern CI/CD pipelines.
This instructor-led live training, available online or on-site, targets intermediate-level technical professionals seeking to implement Cursor within their teams. The course focuses on improving collaboration efficiency, streamlining review processes, and ensuring quality standards across automated workflows.
After completing this training, participants will be equipped to:
- Configure and manage team workspaces in Cursor to support collaborative development.
- Utilize AI tools for automated code reviews, pull request creation, and merge validation.
- Establish code governance, review policies, and security guidelines using Cursor’s features.
- Connect Cursor with CI/CD systems to uphold continuous delivery and consistent quality benchmarks.
Course Format
- Instructor-led lectures combined with collaborative team discussions.
- Practical labs based on real-world team collaboration scenarios.
- Live exercises focusing on integration with CI/CD and version control tools.
Customization Options
- The curriculum can be tailored to specific CI/CD platforms, repository management tools, or enterprise security needs.
GitHub Copilot for Developers
14 HoursThis instructor-led, live training in Uzbekistan (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to learn how to utilise the capabilities of GitHub Copilot effectively within modern development workflows.
GitHub Copilot in Team Environments: Collaboration Best Practices
14 HoursThis instructor-led live training in Uzbekistan (online or on-site) is designed for intermediate to advanced participants seeking to optimize team workflows, enhance collaborative coding practices, and manage Copilot usage effectively in multi-developer environments.
Upon completing this training, participants will be able to:
- Configure GitHub Copilot for team environments.
- Apply Copilot to strengthen collaborative coding practices.
- Streamline team workflows using Copilot’s capabilities.
- Oversee Copilot’s integration within multi-developer projects.
- Ensure consistent code quality and standards across all teams.
- Utilize advanced Copilot features tailored to specific team requirements.
- Integrate Copilot with other collaborative tools to boost efficiency.
Tabnine for Beginners
14 HoursThis instructor-led, live training in Uzbekistan (online or onsite) is designed for beginner developers who want to enhance their coding efficiency with Tabnine.
By the end of this training, participants will be able to:
- Install and set up Tabnine in their preferred IDE.
- Use Tabnine's autocomplete features to accelerate coding.
- Adjust Tabnine's settings for maximum assistance.
- Understand how Tabnine's AI learns from their code to offer better suggestions.
Tabnine for Advanced Developers
14 HoursThis instructor-led, live training in Uzbekistan (online or onsite) is designed for advanced-level developers and team leads who aim to master the advanced capabilities of Tabnine.
By the end of this training, participants will be able to:
- Implement Tabnine within 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 by leveraging Tabnine's insights.
Tabnine: Code Smarter with AI
21 HoursThis instructor-led, live training in Uzbekistan (online or onsite) is aimed at developers ranging from novices to experts who wish to leverage AI for code generation with Tabnine.
By the end of this training, participants will be able to:
- Understand the basics of AI-powered code generation.
- Install and configure Tabnine in their development environment.
- Utilize Tabnine for efficient code completion and error correction.
- Create and train custom AI models with Tabnine for specialized tasks.
Tabnine for Python Developers
14 HoursThis instructor-led, live training in Uzbekistan (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.