Skill Path

Integrate and Evaluate LLMs with OpenAI and Hugging Face

Learn to integrate large language models into applications using APIs, prompt engineering, and evaluation metrics for AI systems.

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This skill path includes
This skill path includes
  • Skill level

    Intermediate
  • Time to complete

    Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary
    3 hours
  • Projects

    2
  • Prerequisites

    2 courses
    We suggest you complete the following courses before you get started with Integrate and Evaluate LLMs with OpenAI and Hugging Face:
    • Intro to PyTorch and Neural Networks
    • Intermediate Python 3

About this skill path

Working with large language models requires more than understanding the technology—it demands practical skills in integration, optimization, and evaluation. In this course, you’ll learn how to use APIs to connect LLMs to real-world applications, craft effective prompts that generate reliable outputs, and measure model performance using industry-standard metrics. You’ll gain hands-on experience with the OpenAI API, managing conversation context, and applying both AI-specific metrics like perplexity, BLEU, and ROUGE alongside traditional machine learning evaluation techniques. By the end, you’ll be equipped to build, deploy, and assess LLM-powered systems with confidence.

Skills you'll gain

  • Understand what APIs are and use them to integrate LLMs into applications
  • Create reliable output from LLMs through effective prompt engineering
  • Send chat requests using the OpenAI API and manage conversation context

Syllabus

5 units • 4 lessons • 2 projects • 4 quizzes
  • 1

    Welcome to the Integrate and Evaluate LLMs Skill Path

    Welcome to the Integrate and Evaluate LLMs with OpenAI and Hugging Face Skill Path!

  • 2

    Intro to OpenAI API

    Leverage the OpenAI API within your Python code. Learn to import OpenAI modules, use chat completion methods, and craft effective prompts.

  • 3

    OpenAI API Coding with Python

    Leverage the OpenAI API within your Python code. Learn to import OpenAI modules, use chat completion methods, and craft effective prompts.

  • 4

    Benchmarking LLMs

    Learn how to integrate large language models using APIs, engineer effective prompts for reliable outputs, and evaluate LLM performance.

  • 5

    Integrate and Evaluate LLMs Skill Path Next Steps

    Integrate and Evaluate LLMs Next Steps!

  • Certificate of completion available with Plus or Pro

    Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.

The platform

Hands-on learning

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Earn a certificate of completion

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Reviews from learners

  • The progress I have made since starting to use codecademy is immense! I can study for short periods or long periods at my own convenience - mostly late in the evenings.
    Chris
    Codecademy Learner @ USA
  • I felt like I learned months in a week. I love how Codecademy uses learning by practice and gives great challenges to help the learner to understand a new concept and subject.
    Rodrigo
    Codecademy Learner @ UK
  • Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.
    John-Andrew
    Codecademy Learner @ USA

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    We’ve hand-picked the content in each Skill Path to fast-track your journey and help you gain a new skill in just a few months.

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What's included in skill paths

  • Practice Projects

    Guided projects that help you solidify the skills and concepts you're learning.
  • Assessments

    Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
  • Certificate of Completion

    Earn a document to prove you've completed a course or path that you can share with your network.