Get your AI development impulse

From requirements analysis, over code and test support to autonomous AI Agents.

A learning path for technical oriented people.


  • 2 hours

    of video content
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➡️ About this Learning Path

Step confidently into the AI-powered future of software development with our immersive workshop, "Software Development with AI (Copilots)." Designed specifically for decision-makers, this workshop offers a comprehensive exploration of how Artificial Intelligence (AI) is transforming every stage of the software development lifecycle. From ideation and planning to implementation, deployment, and maintenance, uncover actionable insights and cutting-edge tools that enhance efficiency, accuracy, and innovation.

📚 Courses in This Learning Path

1️⃣ Introduction to AI in Software Development

This foundational module introduces the transformative potential of AI in software development. You’ll explore its key technologies, including machine learning, natural language processing, and autonomous systems, and understand their impact on the development lifecycle. Through detailed case studies, gain insights into how AI enhances productivity, improves decision-making, and supports innovation. The module concludes with a discussion of current trends shaping the industry and their implications for the future of software engineering.
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2️⃣ AI in Requirements Analysis and Gathering

This module dives deep into the use of AI for enhancing requirements engineering. Participants will explore tools and techniques like natural language processing for analyzing stakeholder input, sentiment analysis for prioritizing user needs, and predictive analytics for anticipating project risks. Hands-on exercises provide practical experience in using AI-powered tools to identify, refine, and prioritize project requirements. Real-world case studies illustrate how AI has streamlined workflows and improved outcomes in successful projects.

3️⃣ AI-Driven Design and Architecture

Learn how AI can revolutionize software design and architecture by automating repetitive tasks and providing intelligent recommendations. Participants will explore tools that assist in pattern recognition, architecture validation, and scenario testing. Case studies from various industries showcase how AI-driven design improves scalability and maintainability while aligning with business objectives. Practical demonstrations offer firsthand experience in integrating these tools into design workflows.
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4️⃣ Autonomous AI Agents – Coding with AI Copilots

This module provides a hands-on introduction to AI copilots like GitHub Copilot and TabNine, highlighting their functionality and benefits.

  • Part 1: Participants will learn how these tools assist with code completion, debugging, and generating boilerplate code, reducing manual effort and increasing coding efficiency.
  • Part 2: Dive deeper into the world of autonomous AI agents, exploring their capabilities for automating coding tasks, performing code reviews, and fixing bugs. Practical demonstrations show how to deploy and manage AI agents within a development workflow.

5️⃣ Quality Boost Through AI-Powered Testing

This course focuses on how AI enhances software testing by automating test case generation, detecting anomalies, and predicting defects. Participants will explore tools like Testim and Applitools and learn how to apply AI to optimize unit, integration, and regression testing. The course also covers techniques for integrating AI into existing testing pipelines to ensure seamless operation and improved coverage.
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6️⃣ Rethinking Infrastructure as Code (IaC) with AI

Explore how AI streamlines infrastructure management by automating IaC processes with tools like Terraform and Bicep. This module covers the role of AI in infrastructure provisioning, optimization, and compliance enforcement. Participants will engage in hands-on activities to set up and manage infrastructure using AI-powered solutions, gaining practical insights into the future of IaC.

7️⃣ AI & Law – Navigating Ethical and Legal Challenges

This module addresses the ethical and legal considerations of integrating AI into software development. Topics include data protection regulations, intellectual property rights, and managing copyright concerns. Participants will also explore the implications of hosting proprietary AI models versus third-party services. Ethical dilemmas, such as workforce displacement and algorithmic fairness, are discussed to ensure responsible AI integration.
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8️⃣ Measuring Success – AI-Driven Metrics

Participants will learn how to evaluate the effectiveness of AI tools in software development by tracking key performance indicators and metrics. This module covers methods to assess productivity, team efficiency, and code quality improvements enabled by AI. Practical exercises provide the tools to measure the return on investment for AI implementations and identify areas for further enhancement.

9️⃣ Enablement of Non-Tech Teams

This module focuses on strategies for making AI tools and concepts accessible to non-technical team members. Participants will learn how to use AI platforms to empower non-technical employees, enabling them to contribute to development processes. Interactive workshops and collaborative exercises foster a deeper understanding of AI’s potential to bridge gaps between technical and non-technical teams.
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