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Home > Shop Courses > AI-Driven Software Development & Intelligent Automation
- December 10-11, 2026
- 9:00 AM – 5:00 PM (UTC+8)
- Virtual Instructor-Led Training (VILT)
- 2 days of instructor-led training
- Training courseware
- Hands-on learning exercises
- 30 days of post-training support
Php20,888.00 Php35,000.00
Save ₱14,112 (40.3%)
Join scheduled online Virtual Instructor-Led Training classes designed for individual learners and professionals.
Customized training for organizations, with flexible scheduling and delivery arrangements.
The AI-Driven Software Development & Intelligent Automation training program is designed to equip IT professionals, software developers, and technical teams with foundational knowledge and practical skills in applying Artificial Intelligence (AI) to modern software development and business automation.
This two-day program introduces essential AI concepts, including Machine Learning (ML), Generative AI, Large Language Models (LLMs), and AI-assisted development tools. Participants will explore how AI can enhance coding productivity, streamline software engineering workflows, improve testing and quality assurance, and support the development of intelligent applications.
Through practical demonstrations, guided exercises, and real-world use cases, participants will learn how to integrate AI models into basic applications using APIs, design supervised intelligent automation workflows, and evaluate opportunities for responsible AI adoption.
The course emphasizes practical implementation, security, reliability, and human oversight to help organizations adopt AI technologies effectively while maintaining software quality and governance standards.
Upon successful completion of this training, participants will be able to:
- Understand AI Fundamentals: Explain the fundamental concepts of Artificial Intelligence, Machine Learning, Generative AI, and Large Language Models, including their capabilities, limitations, and applications in software development.
- Apply AI-Assisted Development Techniques: Utilize AI tools and techniques to support coding, debugging, refactoring, code reviews, technical documentation, and requirements analysis.
- Develop Effective Prompt Engineering Skills: Create structured prompts that improve AI-generated outputs for programming, software architecture, API design, and development tasks.
- Explore AI-Enabled Software Architecture: Understand fundamental architectural patterns and approaches for integrating AI capabilities into existing and new software applications.
- Integrate AI Models into Applications: Demonstrate how to connect a basic application to an AI model through an API, process user requests, and handle AI-generated responses.
- Implement Intelligent Automation Concepts: Differentiate traditional automation from AI-assisted workflows and explore the fundamentals of AI agents, tool integration, and human-in-the-loop processes.
- Enhance Software Testing and Quality Assurance: Apply AI-assisted techniques to generate test cases, support debugging, review code, and improve software quality.
- Promote Responsible AI Adoption: Identify important considerations involving data privacy, cybersecurity, intellectual property, model reliability, and enterprise AI governance.
- Identify AI Adoption Opportunities: Evaluate practical AI use cases within software development and business processes, and propose measurable opportunities for productivity improvement.
This course is designed for participants with basic technical knowledge or familiarity with software development concepts.
Recommended Prerequisites:
- Basic understanding of programming concepts and software development processes.
- Familiarity with at least one programming language, such as Python, JavaScript, Java, or C#.
- General knowledge of software applications, APIs, or web-based systems is beneficial.
- Basic understanding of software testing, debugging, or development workflows is an advantage.
- Basic computer proficiency and familiarity with development tools.
Prior experience with Artificial Intelligence, Machine Learning, or Generative AI is not required.
For Hands-On Activities:
Participants are encouraged to have access to a laptop or workstation with an appropriate development environment, internet connectivity, and any required AI tools or API credentials, as specified by the training provider.
DAY 1 | AI Fundamentals & AI-Driven Software Development
· Module 1 — Introduction to AI in Software Development
o AI, machine learning, generative AI and large language models
o Capabilities, limitations and common enterprise use cases
o Where AI fits in software engineering and existing applications
o Selecting practical opportunities for AI adoption
· Module 2 — AI-Assisted Software Development & Productivity
o AI-supported coding, refactoring and debugging
o Code review, technical documentation and requirements analysis
o Using AI throughout the software development lifecycle
o Reviewing and validating AI-generated code
· Module 3 — Prompt Engineering for Development Teams
o Writing clear prompts with context, constraints and examples
o Prompts for code generation, architecture and API specifications
o Iterative prompting to improve development outputs
o Recognizing incorrect or incomplete AI responses
· Module 4 — AI-Enabled Software Design & Architecture
o Basic patterns for AI-enabled applications
o Connecting existing applications to AI services
o Introduction to model APIs and cloud AI options
o Security, maintainability and reliability considerations
DAY 2 | Intelligent Applications & Automation
· Module 5 — Introduction to AI Application Development
o AI-enabled application components and request-response flow
o Connecting a basic application to an AI model using an API
o Processing user input and displaying model responses
o Basic input validation, failure handling and output checks
· Module 6 — Intelligent Automation & AI Agents
o Differences between fixed automation and AI-assisted workflows
o Fundamentals of AI agents, tools and human approval
o Integrating AI into business and development processes
o Designing a simple supervised automation workflow
· Module 7 — AI-Driven Testing & Quality Assurance
o AI-assisted test-case and test-data generation
o Debugging and code-review support
o Checking generated code for correctness and security
o Practical quality-control and regression-testing approaches
· Module 8 — Responsible AI & Enterprise Adoption
o Privacy, confidentiality and safe handling of enterprise data
o Intellectual property and AI-generated code considerations
o Model limitations, human review and governance
o Identifying pilot use cases and practical productivity measures
This training program is ideal for professionals and technical teams seeking to integrate AI capabilities into software engineering, application development, and organizational workflows.
- Recommended Participants:
- Software Developers and Programmers – Professionals interested in improving coding efficiency, debugging, refactoring, and application development through AI-assisted tools.
- Software Engineers and Application Developers – Technical professionals seeking to integrate AI models, APIs, and intelligent capabilities into applications.
- IT Professionals and Technical Specialists – Individuals exploring practical AI applications within existing IT systems and business processes.
- Software Architects and Technical Leads – Professionals responsible for evaluating AI-enabled application architectures, integration approaches, and technical standards.
- Quality Assurance Engineers and Software Testers – Professionals interested in using AI to support test-case generation, debugging, code validation, and quality assurance.
- DevOps Engineers and Automation Specialists – Technical teams seeking to explore AI-assisted automation, intelligent workflows, and supervised AI agents.
- IT Project Managers and Development Team Leaders – Professionals responsible for identifying AI adoption opportunities and improving software development productivity.
- Technical Business Analysts and Systems Analysts – Professionals involved in requirements analysis, process improvement, and AI-supported solution design.
- Digital Transformation and Innovation Teams – Organizations and professionals evaluating responsible AI adoption to enhance operational efficiency and business performance.
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Axentra Global Inc. is a leading provider of IT training, professional certification courses, corporate learning solutions, and software development services in the Philippines. We help individuals, teams, and organizations build in-demand technology skills through instructor-led training, hands-on workshops, and globally recognized certification programs.
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