Based on this YouTube video's total view count of 186K views and industry-standard rates, the estimated total earning is $130 - $373 through ad revenue. Historical data is not yet available to calculate daily, weekly, or monthly averages.

Explore Build AI Apps with ChatGPT, DALL-E, and GPT-4 – Full Course for Beginners with 186,369 views, 5,362 likes, and 130 comments. Experience the impact of this video content that has captured audience attention.

This course will teach you how to build AI-powered apps with the ChatGPT, Dall-E and GPT-4 APIs. Go here to try the interactive browser-version: https://scrimba.com/learn/buildaiapps ✏️ This course was created by Tom Chant, a teacher at Scrimba. If you have any feedback to Tom, please reach out to him on Twitter here: https://twitter.com/tpchant Also, follow Scrimba on YouTube here: https://www.youtube.com/c/Scrimba We recommend that you learn basic HTML, CSS, and JavaScript before taking this course. Here are two free courses that will get you up to speed: 🔗 HTML & CSS: https://scrimba.com/learn/htmlandcss 🔗 JavaScript: https://scrimba.com/learn/learnjavascript ⭐️ Code ⭐️ 🔗 Download via Scrimba: https://scrimba.com/learn/buildaiapps 💫 Links mentioned in course: 🔗 GPT-4 waiting list: https://scrimba.com/links/gpt4-waitlist-openai 🔗 OpenAI Home: https://scrimba.com/links/openai 🔗 OpenAI Docs: https://scrimba.com/links/openai-docs-intro 🔗 OpenAI Completions endpoint docs: https://scrimba.com/links/openai-completions-docs 🔗 GPTTools.com model comparison: https://scrimba.com/links/open-ai-comparison-tool 🔗 OpenAI Playground: https://scrimba.com/links/open-ai-playground 🔗 Dall-E: https://scrimba.com/links/dall-e-openai 🔗 OpenAI endpoint compatibility table: https://scrimba.com/links/chatgpt-endpoint-compatibility 🔗 GPT-4 Chatbot conversation object format: https://scrimba.com/links/chatgpt-object-format 🔗 Data used to fine-tune We-Wingit Chatbot: https://scrimba.com/links/we-wingit-data-csv 🔗 Firebase home: https://scrimba.com/links/firebase-home 🔗 Firebase .val() method: https://scrimba.com/links/firebase-val-method 🔗 Object.values MDN: https://scrimba.com/links/object-dot-values 🔗 Netlify: https://scrimba.com/links/netlify-home ⭐️ Contents ⭐️ 0:00:00 Introduction 0:01:19 Course Intro 0:04:56 MoviePitch intro 0:07:53 The Boilerplate 0:11:26 Getting an OpenAI API Key 0:13:32 Getting info for fetch request 0:15:14 Building an OpenAI fetch request 0:20:23 The first AI fetch request 0:26:41 Models 0:30:18 Tools 0:34:03 Refactor to use dependency l - env variable 0:38:11 Refactor to use dependency ll - The dependency 0:41:07 Refactor to use dependency lll - update fetchReply 0:44:40 Take out of Scrimba 0:46:45 Personalising the message 0:53:04 Tokens 0:57:09 fetchSynopsis 1:03:44 Aside - few shot approach 1:10:45 Aside - few shot approach ll 1:13:42 Refactor fetchSynopsis 1:21:00 Architecture 1:23:23 Title and Temperature 1:31:52 Reaching for the stars 1:37:52 Aside - createImage 1:46:56 fetchImagePrompt 1:54:21 Displaying the image and finishing off the UX 2:03:16 OutroKnowItAll: GPT-4 Chatbox2:06:47 KnowItAll Intro 2:09:40 Starter Code 2:13:10 Aside: How ChatGPT models work for chatbots 2:18:24 Conversation and instructions 2:20:21 Add user input to conversation array 2:23:06 The createChatCompletion endpoint 2:24:38 The model and object 2:28:46 Render the output, update the array 2:33:37 Aside: Theory: Frequency and presence penalties 2:37:07 presence_penalty practice 2:38:36 frequency_penalty practice 2:44:54 The chatbot’s personality 2:47:06 Firebase Intro 2:48:27 Firebase Account and database set up 2:50:43 Firebase dependency and database set up 2:55:53 Push method and instructions object 2:58:33 Update fetch Reply 3:02:24 Update fetchReply 2 3:04:49 Update the database 3:07:19 Render the conversation from the DB 3:12:02 The “start over” button 3:15:20 OutroWe-Wingit: Fine-tuned chatbot3:17:28 Intro to fine-tuning 3:20:04 Convert the Chatbot to We-Wingit 3:22:15 An Overview of the AI 3:23:52 Data for fine-tuning 3:26:34 The data we’re using 3:30:05 CLI 1 - Setting up the environment 3:33:03 CLI 2 - Data Preparation Tool 3:37:03 CLI 3 - Tuning the model 3:38:55 Updating the JS 1 3:41:33 Updating the JS 2 3:44:15 Updating the JS 3 3:47:01 The Separator 3:52:32 Aside - Stop Sequence 3:55:50 Adding the stop sequence 4:00:36 n_epochs 4:07:24 Intro to deployment 4:09:46 Download and GitHub 4:12:07 Netlify sign-up 4:13:56 Add Netlify env var 4:15:54 Netlify CLI 4:17:30 Netlify serverless function 1 4:19:52 Update fetchReply 4:24:28 Serverless function 2 4:27:30 Serverless function 3 4:29:21 Serverless function 4 4:32:32 Outro 🎉 Thanks to our Champion and Sponsor supporters: 👾 davthecoder 👾 jedi-or-sith 👾 南宮千影 👾 Agustín Kussrow 👾 Nattira Maneerat 👾 Heather Wcislo 👾 Serhiy Kalinets 👾 Justin Hual 👾 Otis Morgan -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp

With SocialCounts.org’s view counter, track your YouTube video’s live view count and YouTube likes count in real time with fast, reliable updates.

Watch every YouTube video live view count rise with our real-time YouTube views tracker—built for accuracy and minimal delay.

Follow YouTube real time views as they happen, using our dedicated view counter for YouTube videos.

Get up-to-date live view count on YouTube and see real-time growth with SocialCounts.org’s smart tracking tools.