AI Agents for Software Development Training Course
AI Agents for Software Development Training Course is designed to equip software engineers, developers, architects, and technology professionals with advanced skills in AI-powered coding, autonomous software agents, generative AI development, intelligent automation, and agentic programming workflows.
Course Overview
AI Agents for Software Development Training Course
Introduction
AI Agents for Software Development Training Course is designed to equip software engineers, developers, architects, and technology professionals with advanced skills in AI-powered coding, autonomous software agents, generative AI development, intelligent automation, and agentic programming workflows. As organizations accelerate digital transformation, AI agents are becoming essential tools for automated code generation, software testing, debugging, DevOps optimization, application modernization, and intelligent developer assistance. This course explores how developers can leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI copilots, autonomous coding agents, prompt engineering, API orchestration, and machine learning-powered development ecosystems to build faster, smarter, and more reliable software solutions.
Participants will gain practical expertise in designing, deploying, and managing AI-driven software engineering workflows that enhance productivity across the entire Software Development Life Cycle (SDLC). Through hands-on labs, real-world case studies, and industry-aligned projects, learners will understand how AI agents collaborate with developers to perform tasks such as requirements analysis, architecture design, code generation, vulnerability detection, automated testing, continuous integration, and intelligent application maintenance. The course prepares professionals to lead the next generation of AI-assisted software engineering and autonomous development environments.
Course Duration
5 Days
Course Objectives
By the end of this course, participants will be able to:
- Understand the foundations of AI agents, generative AI, and autonomous software engineering systems.
- Design AI-powered development workflows using agentic AI architectures.
- Apply Large Language Models (LLMs) for intelligent coding assistance.
- Build automated programming solutions using AI coding agents and copilots.
- Implement prompt engineering strategies for software development tasks.
- Develop AI agents for code generation, refactoring, and optimization.
- Integrate AI agents into modern DevOps and CI/CD pipelines.
- Apply AI-driven software testing and quality assurance automation.
- Use Retrieval-Augmented Generation (RAG) for intelligent code knowledge systems.
- Create multi-agent systems for collaborative software engineering.
- Apply AI techniques for cybersecurity, vulnerability analysis, and secure coding.
- Manage ethical, responsible, and scalable enterprise AI development practices.
- Deploy production-ready AI agent solutions using modern cloud and software platforms.
Target Audience
- Software Developers and Programmers
- Full-Stack Developers
- Software Architects and Technical Leads
- DevOps Engineers and Cloud Engineers
- AI Engineers and Machine Learning Professionals
- Application Development Teams
- IT Managers and Digital Transformation Leaders
- Technology Entrepreneurs and Solution Designers
Course Modules
Module 1: Foundations of AI Agents in Software Development
- Understanding AI agents, autonomous systems, and agentic workflows
- Evolution from traditional programming to AI-assisted development
- Role of LLMs and generative AI in software engineering
- AI agent architecture, reasoning, memory, and tool usage
- Case Study: How GitHub Copilot transformed developer productivity through AI-assisted coding
Module 2: AI Coding Assistants and Developer Copilots
- Introduction to AI-powered coding assistants and intelligent IDE integrations
- Using AI agents for code completion and programming support
- Generating functions, classes, APIs, and application components
- Improving developer productivity through conversational programming
- Case Study: Enterprise adoption of AI coding assistants for accelerating application delivery
Module 3: Prompt Engineering for Software Engineers
- Designing effective prompts for coding, debugging, and documentation
- Advanced prompting patterns for software development tasks
- Chain-of-thought alternatives and structured reasoning approaches
- Creating reusable AI development prompt libraries
- Case Study: Building a developer prompt framework for enterprise engineering teams
Module 4: Building AI Agents for Code Generation and Automation
- Designing autonomous coding agents and software assistants
- Connecting AI agents with APIs, repositories, and developer tools
- Automating programming workflows using agent frameworks
- Creating AI agents for application scaffolding and modernization
- Case Study: AI agent generating a complete web application prototype from requirements
Module 5: AI Agents for Software Testing and Quality Engineering
- Automated test generation using AI agents
- AI-powered debugging and error detection
- Intelligent code review and quality improvement
- Security scanning and vulnerability identification
- Case Study: AI-driven testing platform reducing software testing cycles
Module 6: AI Agents in DevOps and Cloud Engineering
- Integrating AI agents into CI/CD pipelines
- Automating deployment, monitoring, and infrastructure management
- AI-powered incident detection and resolution
- Using AI agents for cloud optimization and resource management
- Case Study: Autonomous DevOps assistant improving deployment reliability
Module 7: Multi-Agent Software Engineering Systems
- Understanding collaborative AI agent architectures
- Creating specialized developer agents for different tasks
- Agent communication, coordination, and workflow management
- Managing AI agent memory and knowledge retrieval
- Case Study: Multi-agent system where AI agents collaborate on enterprise software delivery
Module 8: Enterprise AI Software Development and Future Trends
- Scaling AI agents across software engineering organizations
- Governance, security, and responsible AI development
- Managing AI-generated code quality and compliance
- Future trends in autonomous software engineering
- Case Study: Enterprise transformation using AI-driven software development platforms
Training Methodology
- Instructor-led interactive sessions
- Hands-on practical coding laboratories
- AI agent development workshops
- Real-world enterprise case studies
- Software engineering simulations
- Group projects and collaborative challenges
- Demonstrations of AI development platforms
- Capstone project: Building an AI-powered software development agent
Register as a group from 3 participants for a Discount
Send us an email: info@datastatresearch.org or call +254724527104
Certification
Upon successful completion of this training, participants will be issued with a globally- recognized certificate.
Tailor-Made Course
We also offer tailor-made courses based on your needs.
Key Notes
a. The participant must be conversant with English.
b. Upon completion of training the participant will be issued with an Authorized Training Certificate
c. Course duration is flexible and the contents can be modified to fit any number of days.
d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.
e. One-year post-training support Consultation and Coaching provided after the course.
f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.