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Course Outline

AI-Assisted Software Engineering

  • Exploring the role of AI in modern software development.
  • Capabilities and limitations of AI-assisted coding.
  • Differentiating DeepSeek Coder from other AI coding tools.

Scaling AI-Assisted Development for Large Codebases

  • Efficiently generating and refactoring large-scale code using AI.
  • Implementing AI-assisted documentation and inline explanations.
  • Best practices for reviewing AI-generated code in team environments.

Advanced AI-Powered Debugging

  • Using AI to identify and resolve complex bugs.
  • Generating unit and integration tests with DeepSeek Coder.
  • Employing AI for error pattern recognition and predictive debugging.

Automating Software Development Workflows

  • Conducting AI-assisted code reviews and static code analysis.
  • Creating CI/CD scripts and configuration files with AI assistance.
  • Implementing AI-powered task automation within software teams.

Integrating AI into DevOps and CI/CD Pipelines

  • Enhancing DevOps processes with AI-powered automation.
  • Leveraging DeepSeek Coder for continuous integration and deployment.
  • Addressing security and compliance considerations in AI-assisted software development.

Optimizing Performance with AI

  • Refactoring AI-generated code for enhanced efficiency and maintainability.
  • Utilizing AI to detect and prevent performance bottlenecks.
  • Adopting best practices for integrating AI-assisted development into agile methodologies.

Real-World Applications and Case Studies

  • AI-assisted development in large-scale software projects.
  • Industry use cases: AI-powered automation in software engineering.
  • Future trends and advancements in AI-assisted coding.

Summary and Next Steps

Requirements

  • Proficiency in programming and software development.
  • Familiarity with DeepSeek Coder or similar AI-assisted coding tools.
  • Knowledge of debugging techniques, code optimization, and software development workflows.

Target Audience

  • Developers seeking to streamline coding workflows using AI.
  • Data engineers focused on automating and optimizing large-scale scripts.
  • Software teams looking to integrate AI into DevOps and CI/CD pipelines.
 14 Hours

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