Challenge
A leading consulting firm sought to upskill its software engineers, architects, and DevOps professionals to integrate generative AI across the entire software development lifecycle (SDLC).
The organization needed a hands-on, practical program that would move their teams beyond simple code completion and teach them to leverage AI as a true collaborator in their software development workflow.
The goal was to equip their technical staff with the practical skills to integrate Generative AI and AI-assisted coding throughout the software development lifecycle (SDLC). Learners would need to master using GenAI to accelerate requirements, design, coding, testing, deployment, and maintenance tasks.
Methodology
Our approach was to design a comprehensive 10-day, hands-on upskilling program specifically for the client's engineers.
The curriculum would be structured around a single, cumulative project that participants worked on throughout the first week, allowing them to experience the power of AI as a collaborator in building a full-stack application from scratch.
Solution
We worked with our client to create an immersive program led by an experienced instructor with a background in AI ethics and multi-agent systems. The program's technical stack was built on free and open-source software like VS Code, LangChain, Ollama, and Streamlit, which allowed all labs to be run on a standard laptop without requiring specialized hardware.
The program was grounded in a 60/40 practice-to-content ratio, ensuring that participants spent most of their time actively building and applying their skills.
Key Skills Covered
GitHub Copilot: Core concepts and agent capabilities of GitHub Copilot, with a focus on best practices for efficient code generation and debugging.
Prompt Engineering: Prompt engineering for Large Language Models (LLMs), including prompt tuning, optimization techniques, and designing effective system prompts for chatbot assistants.
React.js: React.js fundamentals, focusing on generating components, creating CSS, and building automated test cases.
SQL: SQL development and optimization, covering AI-assisted code generation, prompt-based querying, and advanced performance improvement techniques.
Python FastAPI: Developing and deploying web services using Python's FastAPI framework.
Development Automation: Automating development tasks such as generating unit tests, ensuring Section 508 compliance, running security checks, scaffolding projects, and refactoring code.
Outcomes
This training enabled the client to move its engineers from using AI as a simple tool to building with AI as an integral part of their workflow.
The hands-on, project-based approach ensured that participants gained practical, applicable skills in a short amount of time. The company successfully positioned its teams to leverage AI innovation beyond simple code completion, preparing them to integrate generative AI across every phase of the software development lifecycle.
By the end of the program, engineers, architects, and DevOps professionals were empowered to accelerate their workflows, automate tasks, and build secure, production-ready code with AI and were able to:
- Explain the fundamentals of large language models and effective prompting techniques.
- Identify key integration points of GenAI across the SDLC.
- Use LLMs and GenAI tools for requirements, design, code generation, and testing.
- Apply prompt engineering techniques tailored to different SDLC phases.
- Integrate GitHub Copilot into development environments to improve coding speed and accuracy.
- Build and present a working prototype demonstrating GenAI-enhanced development workflows.
Knowledge Assessment
The average score on the final assessment was 89%.
This training enabled the client to move its engineers from using AI as a simple tool to building with AI as an integral part of their workflow. The hands-on, project-based approach ensured participants gained practical, applicable skills in a short amount of time. By the end of the program, engineers, architects, and DevOps professionals were empowered to accelerate their workflows, automate tasks, and build secure, production-ready code with AI.
Ascendient Learning's AI in Software Development Training
At Ascendient Learning, we offer fully customized, outcome-based learning programs for your team or organization. We partner with you to design practical, hands-on learning that bridges the gap between theory and enterprise practice, ensuring your teams are immediately ready to tackle your most pressing challenges.
Contact us to get started. Read more about our approach to incorporating AI tools into development training in our blog, Teaching Coders in the Age of AI: Why Your Training Must Evolve Now.
