Free
Course

Prompt Engineering for Analytics

Ready to tap into AI prompt engineering for data analytics? Learn how to use APIs to turn OpenAI’s GPT model into your own personal analytics assistant.

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  • Skill level

    Intermediate

  • Time to complete

    Approx. 1 hour

  • Certificate of completion

    Included with paid plans

  • Prerequisites

    1 course

About this course

Whether you are a professional data analyst or just have data to analyze, AI models like OpenAI’s GPT can help you generate everything from analytics strategies to Python code. In this course, you will learn how to use OpenAI’s models as an AI assistant directly within your own Jupyter Notebook environment. Get ready to power up your analytics workflow with AI.

Skills you'll gain

  • Write effective analytics prompts

  • Connect to OpenAI using an API key

  • Improve performance with API parameters

  • Understand and avoid common AI pitfalls

Syllabus

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Hands-on learning

Don’t just watch or read about someone else coding — write your own code live in our online, interactive platform. You’ll even get AI-driven recommendations on what you need to review to help keep you on track.
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Meet the creator of the course
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Ada Morse
Data Science Instructional Designer at Codecademy
Ada is a Data Science Instructional Designer at Codecademy. Her background is in mathematics, with a Ph.D. focused on the design of self-assembling DNA nanostructures. Ada has worked on courses across our Data Science catalog, covering topics including Python, Excel, and Data Engineering.
Meet the full team

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    Codecademy Learner @ USA

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  • 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.
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Frequently asked questions about Prompt Engineering for Analytics

  • Prompt engineering is the art and science of designing prompts for large language models, to improve their output. Data Analytics requires specific prompting techniques to communicate information about the dataset and context within a Jupyter Notebook.