AI-Driven Software Development Lifecycle (SDLC) Training Course

This advanced training in Australia focuses on GitHub Copilot and AI applications for corporate infrastructure. It equips managers with the skills to optimise project management, streamline workflows, and enhance decision-making using AI tools, with a particular emphasis on large-scale projects.

This instructor-led training in Australia equips advanced developers to master prompt engineering, fine-tuning, and custom tooling within Cursor. Participants will design precise AI behaviours, integrate internal knowledge bases, and build secure, domain-adapted extensions for enterprise workflows.

This instructor-led, live training in Australia (online or onsite) is designed for advanced participants keen on tailoring GitHub Copilot for team initiatives, mastering its advanced capabilities, and integrating it seamlessly into CI/CD pipelines to boost collaboration and productivity.

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

• Tailor GitHub Copilot to meet specific project requirements and team workflows.
• Harness advanced Copilot features to handle complex coding tasks.
• Integrate GitHub Copilot into CI/CD pipelines and collaborative environments.
• Maximise team collaboration through AI-powered tools.
• Effectively manage and troubleshoot Copilot settings and permissions.

This instructor-led, live training in Australia (online or onsite) is aimed at developers who wish to use GitHub Copilot Agent Mode to build features autonomously, 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.

This instructor-led, live training (conducted online or in-person) is designed for intermediate-level software developers looking to enhance productivity and code quality through AI-assisted coding with Cursor.

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

• Install and set up Cursor for AI-assisted software development.
• Integrate Cursor with Git repositories and established development workflows.
• Utilise natural language to generate, debug, and optimise code.
• Harness AI capabilities for refactoring, documentation, and testing.

This instructor-led training in Australia introduces Cursor as an AI-powered environment to accelerate data and ML workflows. Participants will learn to streamline notebook development, ETL pipelines, and model operations through practical exercises that enhance productivity and operational consistency.

This instructor-led training in Australia guides developers in adopting Cursor, an AI-powered editor that enhances productivity through intelligent completions and contextual edits. Participants will develop hands-on capabilities in refactoring, safe review of AI suggestions, and team collaboration to streamline their workflows.

This instructor-led live training in Australia assists teams in integrating Cursor to streamline collaboration and code reviews. It covers managing workspaces, automating AI-assisted PRs, enforcing governance policies, and connecting Cursor to CI/CD pipelines to ensure consistent quality.

This instructor-led, live training in Australia (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 instructor-led, live training in Australia (online or onsite) targets intermediate to advanced participants looking to optimise team workflows, elevate collaborative coding practices, and effectively manage Copilot usage in multi-developer settings.

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

• Configure GitHub Copilot for team environments.
• Use Copilot to strengthen collaborative coding practices.
• Optimise team workflows using Copilot’s features.
• Manage Copilot’s integration within multi-developer projects.
• Ensure consistent code quality and standards across teams.
• Leverage advanced Copilot features tailored to specific team requirements.
• Integrate Copilot with other collaborative tools for greater efficiency.

This instructor-led, live training in Australia (online or onsite) is aimed at beginner-level developers who wish to increase their coding efficiency with the help of Tabnine.

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

• Install and set up Tabnine in their preferred IDE.
• Utilise Tabnine's autocomplete features to speed up coding.
• Customise Tabnine's settings for optimal assistance.
• Understand how Tabnine's AI learns from their code to provide better suggestions.

This instructor-led, live training in Australia (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 Australia (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.

This instructor-led, live training in Australia (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 behaviour to fit their coding style and project needs.
• Understand how Tabnine's AI model works specifically with Python code.