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Course Outline

AI-Assisted Software Engineering

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

Scaling AI-Assisted Development for Large Codebases

  • Using AI to generate and refactor large-scale code efficiently.
  • Implementing AI-assisted documentation and inline explanations.
  • Best practices for reviewing AI-generated code in team environments.

Advanced AI-Powered Debugging

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

Automating Software Development Workflows

  • AI-assisted code reviews and static code analysis.
  • Generating CI/CD scripts and configuration files with AI.
  • Implementing AI-powered task automation in software teams.

Integrating AI into DevOps and CI/CD Pipelines

  • Enhancing DevOps with AI-powered automation.
  • Using DeepSeek Coder for continuous integration and deployment.
  • Security and compliance considerations in AI-assisted software development.

Optimizing Performance with AI

  • Refactoring AI-generated code for efficiency and maintainability.
  • Using AI to detect and prevent performance bottlenecks.
  • 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

  • Experience in programming and software development.
  • Basic familiarity with DeepSeek Coder or similar AI-assisted coding tools.
  • Understanding of debugging, code optimization, and software development workflows.

Audience

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

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