Responsible AI in Software Development Training Course

GitHub Copilot is an AI-driven code completion tool designed to accelerate development while enhancing both quality and productivity. When combined with Artificial Intelligence applications across projects, infrastructure, and software, managers can harness AI to optimize resource allocation, streamline workflows, and improve decision-making processes.

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 settings, with examples relevant to large-scale projects and industries such as oil and gas.

Upon completing this training, participants will be able to:

• Utilize advanced Copilot features within large-scale corporate projects.
• Integrate Copilot into multidisciplinary workflows to achieve maximum efficiency.
• Use AI tools to optimize project management, infrastructure, and software acquisition.
• Deploy AI-based strategies to enhance planning, estimation, and time optimization.
• Identify practical AI applications in industry-specific scenarios, such as the oil and gas sector.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises and case studies.
• Live lab demonstrations of AI tools and Copilot workflows.

Course Customization Options

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

Cursor serves as a sophisticated AI-driven development environment, enabling engineers to customize, fine-tune, and extend its coding intelligence for specialized use cases and complex enterprise workflows.

Designed for advanced-level developers and AI engineers, this instructor-led live training (available online or onsite) focuses on designing tailored prompt systems, optimizing model behavior, and constructing custom extensions to streamline internal development automation.

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

• Engineer and validate advanced prompt templates to achieve precise AI behavior.
• Integrate Cursor with internal APIs and knowledge bases to facilitate context-aware code generation.
• Develop fine-tuned or domain-adapted AI models tailored for specialized tasks.
• Securely build and deploy custom tools or adapters that expand Cursor’s capabilities.

Course Structure

• Technical presentations accompanied by guided demonstrations.
• Practical labs focused on development and prompt optimization.
• Real-world projects integrating Cursor with enterprise systems.

Customization Options

• The curriculum can be tailored to align with specific internal architectures, AI frameworks, and security compliance standards.

This instructor-led, live training in Denmark (online or onsite) is designed for advanced-level participants who aim to customize GitHub Copilot for team projects, exploit its advanced features, and integrate it effectively into CI/CD pipelines to improve collaboration and productivity.

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

• Tailor GitHub Copilot to meet specific project needs and team workflows.
• Leverage Copilot’s advanced capabilities for complex coding tasks.
• Integrate GitHub Copilot into CI/CD pipelines and collaborative settings.
• Optimize team collaboration through the use of AI-powered tools.
• Manage and troubleshoot Copilot settings and permissions with confidence.

This live, instructor-led training, conducted in Denmark (either online or onsite), is tailored for developers aiming to utilize GitHub Copilot Agent Mode for autonomous feature construction, test execution, and the management of extensive coding tasks.

By the conclusion of this program, participants will be equipped to activate Agent Mode, plan and iterate within the agent loop, execute terminal commands, and establish enterprise-grade governance controls.

GitHub Copilot serves as an AI-driven coding assistant designed to streamline development workflows, including DevOps activities such as crafting YAML configurations, GitHub Actions, and deployment scripts.

This live, instructor-led course (available online or onsite) is tailored for professionals ranging from beginners to intermediate level who aim to leverage GitHub Copilot to optimize DevOps tasks, enhance automation, and increase overall productivity.

Upon completion, participants will be equipped to:

• Utilize GitHub Copilot to support shell scripting, system configuration, and CI/CD pipeline management.
• Apply AI-assisted code completion within YAML files and GitHub Actions.
• Speed up processes related to testing, deployment, and automated workflows.
• Adopt Copilot responsibly by understanding its AI limitations and adhering to best practices.

Course Format

• Engaging interactive lectures and discussions.
• Extensive practical exercises and training sessions.
• Practical hands-on implementation in a live-lab setting.

Customization Options

• For bespoke training tailored to this course, please reach out to us to make arrangements.

This live, instructor-led training—delivered online or onsite—targets intermediate-level software developers seeking to improve efficiency and code standards by leveraging AI-assisted coding with Cursor.

By the conclusion of this training, participants will possess the ability to:

• Install and set up Cursor for AI-integrated software development.
• Integrate Cursor into Git repositories and existing dev workflows.
• Employ natural language to create, debug, and optimize code.
• Harness AI capabilities to aid in refactoring, documentation, and testing.

Cursor serves as an AI-driven development environment designed to boost productivity and reliability in data and machine learning workflows by offering intelligent code generation, context-aware suggestions, and simplified documentation processes.

Delivered either online or onsite, this instructor-led live training is tailored for intermediate-level data and ML professionals looking to embed Cursor into their daily routines for quicker prototyping, scalable pipeline creation, and enhanced model operations.

Upon completion of this course, participants will have the ability to:

• Utilize Cursor to speed up notebook creation and code exploration.
• Develop, refine, and document ETL and feature engineering pipelines.
• Apply AI-assisted coding techniques to model training, tuning, and evaluation.
• Improve reproducibility, team collaboration, and operational consistency within ML workflows.

Course Format

• Engaging lectures and live demonstrations.
• Practical, hands-on exercises conducted in real-time coding environments.
• Case studies demonstrating the integration of Cursor with ML pipelines and model ops tools.

Course Customization Options

• The training can be adapted to focus on specific frameworks like TensorFlow, PyTorch, or scikit-learn, or aligned with an organization’s MLOps platform.

Cursor is an AI-driven code editor engineered to elevate developer productivity by delivering intelligent code completions, context-aware edits, and adaptive support.

This instructor-led session, available online or on-site, is tailored for entry-level developers and engineering teams looking to optimize their coding workflows while securely utilizing AI suggestions for enhanced efficiency.

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

• Set up and configure Cursor for peak performance in development projects.
• Master and utilize AI-assisted code completion, in-editor chat, and refactoring capabilities.
• Critically assess, approve, or refine AI-generated code suggestions with confidence and security.
• Implement best practices for team onboarding, collaboration, and seamless version control integration.

Course Delivery Methods

• Engaging lectures and interactive discussions.
• Live demonstrations and structured practical exercises.
• Practical coding challenges and lab sessions using Cursor.

Customization Options

• The curriculum can be adapted to focus on specific programming languages or frameworks utilized by your team.

Cursor serves as an AI-driven development environment designed to boost team cooperation, automate code review processes, and fit seamlessly into contemporary CI/CD pipelines.

This instructor-led live training, available online or onsite, targets intermediate-level technical professionals aiming to embed Cursor into their team workflows. The goal is to enhance collaboration, optimize reviews, and uphold quality standards throughout automated pipelines.

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

• Configure and administer team environments within Cursor to foster collaborative development.
• Utilize AI capabilities for automated code reviews, generating pull requests, and validating merges.
• Apply code governance, review policies, and security safeguards leveraging Cursor’s features.
• Connect Cursor with CI/CD systems to guarantee continuous delivery and consistent quality benchmarks.

Course Format

• Instructor-led presentations combined with team-based discussions.
• Hands-on labs focusing on real-world team collaboration scenarios.
• Live integration exercises involving CI/CD and version control tools.

Course Customization Options

• The curriculum can be tailored to specific CI/CD platforms, repository tools, or enterprise security requirements.

This live, instructor-led training in Denmark (delivered online or on-site) is designed for developers with beginner to intermediate experience who aim to effectively leverage GitHub Copilot's capabilities within modern development workflows.

This instructor-led live training, available Denmark (online or on-site), is designed for intermediate to advanced participants aiming to optimize team workflows, improve collaborative coding practices, and effectively manage Copilot in multi-developer environments.

By the end of the session, participants will be able to:

• Configure GitHub Copilot for team environments.
• Utilize Copilot to enhance collaborative coding practices.
• Improve 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 live, instructor-led training in Denmark (delivered online or onsite) is designed for novice developers seeking to enhance their coding productivity with Tabnine.

Upon completing this training, participants will be able to:

• Install and configure Tabnine within their chosen IDE.
• Leverage Tabnine’s autocomplete capabilities to enhance coding speed.
• Tune Tabnine’s settings to achieve optimal assistance.
• Gain insight into how Tabnine’s AI analyzes code to refine its suggestions.

This live, instructor-led training in Denmark (delivered online or onsite) is designed for senior developers and team leaders aiming to command the advanced functionalities of Tabnine.

Upon completion, participants will be equipped to:

• Deploy Tabnine within intricate software architectures.
• Tailor and train Tabnine's AI models to address specific application needs.
• Seamlessly embed Tabnine into collaborative workflows and development pipelines.
• Boost code integrity and expedite development cycles by leveraging Tabnine's analytical insights.

Delivered by an instructor in Denmark via online or onsite sessions, this live training is designed for developers across the spectrum, from novices to experts, looking to utilize AI for code generation with Tabnine.

By the end of the session, participants will be able to:

• Comprehend the core principles of AI-powered code generation.
• Install and configure Tabnine within their development setup.
• Employ Tabnine for streamlined code completion and error fixing.
• Develop and train custom AI models in Tabnine for specialized applications.

This live, instructor-led training session Denmark (conducted online or on-site) is designed for intermediate Python developers and data scientists seeking to enhance their workflow efficiency by integrating Tabnine into their daily processes.

By the conclusion of this training, participants will be capable of:

• Effectively installing and configuring Tabnine within their Python development environment.
• Leveraging Tabnine’s autocomplete features to write Python code with greater efficiency.
• Customizing Tabnine’s behavior to match personal coding styles and distinct project needs.
• Comprehending the specific mechanics of Tabnine’s AI model as it processes Python code.