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AI Development

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AI Agent Development

Developing Generative AI Programs Using OpenAI API

This course teaches you how to use generative AI models using the OpenAI API. In this course, you will learn the basics of using the API, how to use various language models, and practical programming examples and applications to learn how to apply generative AI in real life.

(4.5) 11 reviews

78 learners

  • YoungJea Oh
이론 실습 모두
Python
NLP
ChatGPT
openAI API
Generative AI

What you will learn!

  • Basic concepts and features of the latest OpenAI API

  • How to create and manage API keys

  • How to select different language models and tune parameters

  • Automated text generation

  • Chatbot Development

  • Document Summary and Generation

  • How to optimize performance and make efficient API calls

How can OpenAI APIs make us more productive? 🤔

The answer lies in the powerful combination of generative AI and APIs . The OpenAI API provides a wide range of functions, including natural language processing, text generation, image generation, and speech processing , helping developers quickly and easily create AI-powered applications.

In this lecture, you will learn how to develop AI-based applications using the OpenAI API . You will learn how to implement natural language processing, voice conversion, image generation, and recommendation systems using OpenAI's GPT-4o, DALL·E, Whisper, and Embedding models.

In addition, you will learn cutting-edge technologies such as Prompt Engineering, Function Calling, Assistants API, and Structured Outputs, and build AI applications that can maximize productivity .

If you're tired of superficial tutorials, rediscover the fun of development by building AI applications that can be used in real-world situations ! 🚀

Text, images, and even voice
Practical Development with OpenAI API

📌 All the core functions of the OpenAI API at once! We provide practical AI application development know-how using GPT-4o, DALL·E, Whisper, and Embedding.

📌 This is a lecture where you will learn through hands-on practice the latest technologies of OpenAI, such as Prompt Engineering, Function Calling, and Assistants API .

📌 10% theory, 90% practice! Rather than simply explaining concepts, you will build and experiment with AI services based on the OpenAI API .

📌 How to use AI to increase productivityLearn how to use AI not just as a tool, but in a way that can be applied directly to real projects.

📌 Intermediate Course! If you have basic API development experience using Python, you can master AI-based application development in this course. 🚀

I recommend this to these people

🧑‍💻 I want to learn AI-based backend development.

You can create a basic API, but if you are wondering how to add advanced features using AI, this course will help you.

🌍 I am interested in developing services using AI and API.

This course is for those who want to learn how to apply AI to real-world projects using ChatGPT, DALL·E, Whisper, and Embedding models.

🚀 I want to apply the latest AI technology in practice.

You will learn how to develop AI services using the latest features of the OpenAI API, such as Function Calling, Assistants API, and Prompt Engineering.

After class

💡 Utilizing OpenAI API becomes natural.

You will be able to freely develop AI-based applications using GPT-4o, DALL·E, Whisper, and Embedding.

🔍 Advanced AI service development is now possible using Function Calling and Assistants API.

You'll learn how AI calls external APIs, retrieves files, and executes code in a real-world production environment.

📊 You can improve the response quality of AI by using Prompt Engineering.

You can design more sophisticated AI responses by leveraging Few-shot Prompting, Chain-of-Thought, Structured Outputs, and more.

Learn about these things.

📌 OpenAI API Basics and Utilization
We directly implement natural language processing, image generation, voice conversion, recommendation systems , etc. using GPT-4o, DALL·E, Whisper, and Embedding models.

📌 Function Calling and Assistants API
Learn how AI can call external APIs, retrieve files, and execute code using OpenAI's Function Calling.

📌 Prompt Engineering Optimization Technique
Learn how to design more sophisticated and accurate AI responses using Few-shot Prompting and Chain-of-Thought techniques.

📌 Understanding the principles of Transformer and Embedding
Learn how the Transformer model works and how to use Embedding to vectorize text, find similarity, and build recommendation systems .

Who created this course - Youngje Oh

  • 2019 ~ Present: Professional AI Instructor

  • 2001~2019: IT development and operation in the field

  • Inflearn runs 13 AI courses

💡 Increase the credibility of this course by introducing knowledge sharers related to this course.

  • Please write about your background and experiences that are closely related to the lecture topic.

  • Rather than just listing all your experiences, it would be better to include the concerns and motivations that went into creating this course.

  • Use portfolios, videos, photos, etc. along with simple text to grab attention.

Things to note before taking the class

Practice environment

  • The course is based on Windows . If you have Anaconda installed on MacOS, you can follow most of the exercises.

  • In this lecture, we will practice using the OpenAI API using Jupyter Notebook .

  • You will need to obtain an OpenAI API Key for this exercise. Instructions on how to obtain one will be explained in detail in the course.

Learning Materials

  • We provide it as a pdf file and a github link!

Player Knowledge and Notes

  • Basic Python Grammar

  • Prior knowledge of artificial intelligence natural language processing models is helpful, but not required.

Recommended for
these people

Who is this course right for?

  • Developers and engineers familiar with programming languages including Python

  • Students and researchers learning machine learning and deep learning

  • Startup founders and planners who want to apply AI technology to their business

  • Professors and lecturers who conduct AI education

Need to know before starting?

  • Python programming language

  • Natural Language Processing (NLP) Basics

Hello
This is

3,743

Learners

287

Reviews

144

Answers

4.8

Rating

14

Courses

오랜 개발 경험을 가지고 있는 Senior Developer 입니다. 현대건설 전산실, 삼성 SDS, 전자상거래업체 엑스메트릭스, 씨티은행 전산부를 거치며 30 년 이상 IT 분야에서 쌓아온 지식과 경험을 나누고 싶습니다. 현재는 인공지능과 파이썬 관련 강의를 하고 있습니다.

홈페이지 주소:

https://ironmanciti.github.io/

Curriculum

All

43 lectures ∙ (9hr 26min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

11 reviews

4.5

11 reviews

  • sunheeshin4499님의 프로필 이미지
    sunheeshin4499

    Reviews 4

    Average Rating 5.0

    5

    30% enrolled

    • trimurti
      Instructor

      Thank you for the good review.

  • gynam4062님의 프로필 이미지
    gynam4062

    Reviews 15

    Average Rating 4.7

    3

    30% enrolled

    • stakso7540님의 프로필 이미지
      stakso7540

      Reviews 5

      Average Rating 3.4

      4

      100% enrolled

      • jyp4님의 프로필 이미지
        jyp4

        Reviews 13

        Average Rating 4.8

        5

        100% enrolled

        It's been over a year since I started using it for work, but only now have I begun learning the fundamentals. Once you know it, it seems like nothing, but the entry barrier feels a bit high. The examples were good. It was good because they were immediately applicable with just a little bit of adaptation. It was good to learn the overall usage of openai.

        • trimurti
          Instructor

          Thank you for the good review.

      • nammiga20597님의 프로필 이미지
        nammiga20597

        Reviews 10

        Average Rating 4.4

        3

        30% enrolled

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