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Coursera

Optimize Python for Agentic AI

Coursera via Coursera

Overview

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"Optimize Python for Agentic AI" is an intermediate course for developers who want to elevate their Python code from functional to professional-grade. In the world of AI, inefficient or unreadable code can cripple an agent's performance and slow down team collaboration. This course equips you with the essential software engineering practices to write Python that is both highly efficient and exceptionally clear. You will learn to apply clean-code conventions, including PEP 8 standards, type hints, and descriptive docstrings, to produce readable and maintainable modules that your teammates can easily understand and build upon. Through hands-on labs, you will master the art of performance tuning by systematically using profiling tools like cProfile to analyze runtime behavior, pinpoint hidden bottlenecks, and refactor code for significant speed improvements. By the end of this course, you will be able to confidently balance readability with runtime efficiency, ensuring the AI systems you build are not only intelligent but also robust, scalable, and production-ready.

Syllabus

  • Code Quality and Documentation Standards
    • You start by understanding how professional AI systems depend not only on smart logic but also on clean, readable Python. When deadlines hit, messy code slows teams down. This module shows you why clarity and consistency matter for maintainability and collaboration. You will refactor a memory manager from an AI agent, practice adding type hints and docstrings, and run style checks with flake8. You will see how these conventions keep complex AI projects manageable—and you will apply them to produce production-quality Python.
  • Runtime Performance Optimization
    • Now that your code reads cleanly, it is time to make it run fast. Performance problems often hide in unexpected places. You will learn when to profile, how to interpret profiler data, and how to refactor Python for efficiency. By the end of this module, you will replace inefficient regex calls and confirm improvements through benchmarks. You will close the course by combining maintainability with performance in a final strategy report.

Taught by

LearningMate

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