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How to use ChatGPT in 2025 | ChatGPT Tutorial | ChatGPT Full Course



Begin your journey to being a ChatGPT Pro with our 12-hour ChatGPT Masterclass. This video covers everything from basics to …

35 thoughts on “How to use ChatGPT in 2025 | ChatGPT Tutorial | ChatGPT Full Course”

  1. यु कती अंगरेज क़ा बीज है इसि वज़ह स एंग्रेजी में भासन दे रहि है हिन्दी मे भासन दे

  2. Summary

    This comprehensive tutorial on ChatGPT provides viewers with essential knowledge and insights to maximize the capabilities of this generative AI tool. It covers the basics of ChatGPT, explores its various versions (from 3.5 to 4.0), discusses its applications in coding, digital marketing, finance, and productivity-enhancing tools like Microsoft PowerPoint. The video highlights not only how to use ChatGPT effectively but also addresses its limitations and ethical considerations.

    Highlights

    0:00

    Introduction to what viewers will learn about ChatGPT by the end of the video.

    0:27

    Overview of the tutorial content, including different segments available in the description for easy navigation.

    1:58

    Introduction to prompt engineering – a skill crucial for effective interaction with ChatGPT.

    2:42

    Discusses applications in digital marketing and finance for leveraging AI technologies effectively.

    3:08

    Explanation of generative AI with a simple analogy involving a "magical box" that creates unique toys based on user input.

    11:17

    Detailed look at how large language models (LLMs) function within generative AI frameworks like GPT-4 and beyond.

    28:41

    Explanation on accessing ChatGPT easily through web browsers or mobile apps; practical tips provided for users interested in implementation using APIs as well as third-party platforms like Microsoft Word/Excel integration.

    40:08

    Discusses coding capabilities including code generation across different programming languages while emphasizing ethical usage guidelines.

    42:41

    Addresses key limitations such as accuracy issues, potential biases due to training data influence, etc., urging critical use by users.

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