Certified Generative AI in Software Development
About This Course
This course is designed to transition modern software practitioners from manual implementation to Artificial Intelligence (AI)-native software engineering with design and architectural orchestration. The curriculum focuses on bridging the gap between isolated AI chat interfaces and fully integrated, context-aware agentic workflows.
Participants will evolve from "prompting for code" to "governing autonomous systems," mastering the tools that automate the tedious aspects of the Software Development Life Cycle (SDLC) while maintaining rigorous engineering standards.
What You'll Learn
b. Automate terminal-based debugging with (Command-line Interface)CLI-native agents.
c. Link AI models to local data via Model Context Protocol (MCP) servers.
d. Orchestrate multi-agent workflows using orchestration frameworks.
e. Implement codebase Retrieval-Augmented Generation (RAG) for intelligent project navigation.
f. Deploy self-healing AI agents within Continuous Integration/Continuous Delivery or Deployment (CI/CD) pipelines.
g. Build low-code workflows to automate business-dev operations.
h. Modernize legacy systems using autonomous refactoring agents.
i. Audit AI-generated code for security and architectural integrity.
j. Enforce Application Programming Interfaces (API) contracts through automated AI auditing tools.
Entry Requirements
a. Familiarity with software development lifecycle.
b. Working understanding of any programming languages (e.g. Python, Java, Javascript).
c. Basic operational knowledge of Artificial Intelligence (AI) tools and platforms.