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AI Assisted Software Development

Master Enhance Unlock Explore Excel AI-Powered Software Development

Learn to design, build, and deploy software with AI tools

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Key Points

Unlock the Future of Software Development

Discover how AI tools can accelerate your development process, improve code quality, and streamline project management. With hands-on learning, expert guidance, and practical projects, you’ll gain the skills to design, build, and maintain modern software solutions using AI.

Hands-On Learning

Practical exercises for real-world skills

Expert Guidance

Learn from industry leaders in architecture and AI

Flexible Structure

Self-paced modules with live Q&A sessions

Capstone Project

Apply your skills by building a complete AI-powered solution.

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Curriculum

Module 1

Introduction to AI in Software Development

  • AI in Modern Development

    Discover how AI accelerates development by automating coding tasks, improving decision-making, and enhancing productivity. Learn how AI frameworks manage agent behaviors, ensuring scalable, secure, and adaptable systems.

  • AI Tools & Platforms

    Explore key tools like OpenAI, Azure AI, and GitHub Copilot, understanding how each contributes to intelligent development workflows.

  • AI for Code & Testing

    Learn strategies for using AI to auto-generate code, create efficient test cases, and improve performance through intelligent refactoring.

  • Ethical AI Use

    Understand best practices for developing responsible AI systems that align with privacy, fairness, and compliance standards.

Tools

  • Git-Hub Copilot
  • OpenAI API
  • Azure AI Foundy

Hands-on

  • Build a simple app with Git-Hub Copilot suggestions
  • Implement auto-generated tests using AI tools

Module 2

AI-Driven Architecture & Design

  • AI in Architecture

    Learn how AI revolutionises system design by automating complex decision-making, predicting system behaviour, and ensuring robust scalability. Learn how AI-driven frameworks provide enhanced oversight for managing dynamic agent interactions, promoting stability and security in large-scale architectures.

  • Architecture Patterns

    Leverage modern architecture design patterns that harness AI insights to create adaptive, efficient, and scalable software architectures. Discover how to think like an architect and use tools to optimize component interactions, enhance modular design, and ensure flexibility for evolving system demands.

  • Architecture for Refactoring

    Harness architecture skills to conduct deep analysis of legacy systems, identify redundant code, and recommend optimal refactoring strategies. Leverage AI-driven insights to restructure codebases for improved maintainability, scalability, and performance.

  • Architecture AI Agents

    Learn how to design scalable systems that manage AI agent behaviour by combining architectural patterns, intelligent state management, and dynamic decision models. Discover strategies to balance agent autonomy with oversight, ensuring stable, transparent, and predictable outcomes in complex environments.

Tools

  • vFunction - Automated architecture observability and modernization
  • Whimsical – Visual planning for architectural designs
  • Lucidchart – System mapping and flowchart creation

Hands-on

  • Refactor a sample legacy codebase
  • Design an AI-driven system architecture for scalability
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Module 3

AI for Coding & Development

  • AI Code Generation

    Utilize AI to intelligently generate boilerplate code, automate repetitive coding patterns, and fill in logic gaps based on contextual understanding. Learn to apply AI tools to accelerate development, minimize coding errors, and improve code consistency across projects.

  • AI for Code Quality

    Leverage AI-driven insights to identify code smells, security vulnerabilities, and performance bottlenecks. Understand how AI models analyze patterns to recommend optimizations, refactor code structures, and improve maintainability.

  • AI-Enhanced Code Reviews

    Utilize AI to automate code review processes by identifying code smells, improving readability, and recommending optimal design patterns. Learn how AI tools accelerate feedback loops, enhance team collaboration, and ensure coding standards are consistently maintained.

  • AI For Security

    Utilize AI-driven security tools to identify vulnerabilities, analyze code patterns for potential risks, and suggest secure coding practices. Learn how AI models detect anomalies, prevent exploits, and fortify applications against evolving threats.

Tools

  • CodiumAI – AI-based review automation
  • DeepCode – Code quality and security insights
  • TabNine – Smart code completions for improved productivity

Hands-on

  • Generate code snippets using CodiumAI
  • Build a REST API using AI-generated code improvements
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Module 4

AI for Testing & Debugging

  • AI Code Generation

    Utilize AI to intelligently generate boilerplate code, automate repetitive coding patterns, and fill in logic gaps based on contextual understanding. Learn to apply AI tools to accelerate development, minimize coding errors, and improve code consistency across projects.

  • Bug Prediction & Detection

    Learn how AI tools identify patterns in code that predict potential bugs before they occur.

  • AI Debugging Strategies

    Implement AI-enhanced debugging workflows to reduce troubleshooting time and improve stability.

Tools

  • CodiumAI – AI-based review automation
  • DeepCode – Code quality and security insights
  • TabNine – Smart code completions for improved productivity

Hands-on

  • Generate code snippets using Cursor
  • Build a REST API using AI-generated code improvements
  • Feedback-loops - how not to get entagled
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Module 5

AI for Testing & Debugging

  • Predictive Maintenance

    Use AI to anticipate system issues and proactively address performance risks.

  • AI-Enhanced Monitoring

    Integrate AI models that identify patterns in performance data to optimize uptime and reliability.

  • Intelligent CI/CD Pipelines

    Automate deployment tasks with AI-enhanced insights, improving efficiency and reducing errors.

Tools

  • Datadog – Intelligent monitoring and alerts
  • New Relic – AI-enhanced application performance insights
  • Jenkins AI Plugins – Automate key CI/CD stages with AI assistance

Hands-on

  • Implement predictive alerts with Datadog
  • Design an AI-driven CI/CD pipeline for automated deployment
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Module 6

Ethical AI & Best Practices

  • Responsible AI Design

    Build transparent and accountable AI solutions that align with privacy regulations.

  • Mitigating Bias

    Learn best practices for ensuring your AI models are unbiased and ethically sound.

  • Explainable AI

    Develop solutions that provide clear reasoning for AI-driven decisions to foster trust and accountability.

Tools

  • IBM Watson OpenScale – Ensures AI fairness and traceability
  • Fairlearn – Mitigates algorithmic bias
  • Azure AI Responsible AI Toolkit – Ensures responsible AI deployment practices

Hands-on

  • Audit an AI model for fairness and transparency
  • Build an explainable AI feature to clarify model outcomes
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Module 7

Capstone Project

  • Comprehensive AI Solution

    Develop a full-stack project that combines AI-assisted design, coding, testing, and deployment. Covering everything from project idea, project backlog, architecture & design, constraints, architectural characteristics.

  • Real-World Challenges

    Apply AI to solve common development challenges in scalable and maintainable solutions. How to react on issues found during development, how to manage change during project development.

  • Best Practices Integration

    Demonstrate architecture design, code quality, and deployment optimization in your final project. Implement and adapt findings from previous models in everyday tasks.

Tools

  • GitHub - code repository and branch management
  • Azure AI Services – Advanced AI model integration
  • OpenAI API – Implement interactive content generation
  • Cursor coding agents

Hands-on

  • Design, build, and deploy a robust AI-integrated application
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AI Assisted Software Development

Pricing for the on-line version
€ 1500 one-time
  • Online guided training
  • 2 horus personal consultation
  • 2 hours post-training consultation
  • 4 hours daily
  • 2 week course
  • Workshop environment
  • No boring lectures
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Trainings are done online, in a group environment. Trainings takes place in the course of two weeks, each working day, 2 hours module content theory followed by 2 hours hands-on practice.
First week is reserved for modules 1-6.
Second week is reserved for module 7.
For on-site trainings, or if you want to train group of trainees, please send an inquery by filling out the form below.
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Signup to express interest in this training. Once we have full list of attendees we will send you proposal with the couple of training slots. Once you select and pay for the course we will reserve your spot and send you the details.
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