🔥PROMPT ENGINEERING WITH GENERATIVE AI: https://www.edureka.co/prompt-....engineering-generati
Explore the field of artificial intelligence through our Generative AI Tutorial. This video will break down the intricate workings of the generative AI model and give you useful information and pointers for utilizing generative AI in your projects, covering everything from the fundamentals of the technology to its applications, frameworks, and changing the landscape of industries. This course is a crucial place to start, whether you're a professional looking to implement AI-driven solutions or a newcomer excited to learn about AI's creative potential.

✅ 00:00 - Generative AI Tutorial
✅ 02:10 - Introduction to AI
✅ 02:48 - Working of AI
✅ 03:45 - What is Generative AI
✅ 05:00 - AI Prompt Writing
✅ 06:35 - Text-to-Text Generative AI
✅ 07:42 - Prompt Writing Rules
✅ 08:47 - ChatGPT-3.5
✅ 09:15 - ChatGPT-4
✅ 11:24 - Google Gemini
✅ 12:22 - Text-to-Image Generative AI
✅ 13:41 - DezGo
✅ 13:50- Hands-On Tutorial

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𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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What is Prompt Engineering?

Prompt engineering involves optimizing artificial intelligence engineering for multiple purposes. It includes refining large language models (LLMs) using specific prompts and recommended outputs. Additionally, it focuses on enhancing input to different generative AI services to make text or images. With advancements in generative AI tools, prompt engineering becomes crucial for generating diverse content, such as robotic process automation bots, 3D assets, scripts, robot instructions, and various digital artifacts.
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What kinds of jobs can you get with Prompt Engineering skills?‎

Here are some potential job roles:

Machine Learning Engineer
Data Scientist
Natural Language Processing (NLP) Engineer
AI Research Scientist
Software Engineer (AI/ML)
Data Engineer
Content Generation Specialist
Conversational AI Developer
AI Product Manager
AI Ethicist

Remember that the job market and the demand for specific skills can change over time, so staying updated on industry trends and job postings is essential.

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Who are the instructors for Prompt Engineering Course?

All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience to the participants.

For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: +18338555775 (toll-free).

LangChain is an open-source framework that allows you to build applications using LLMs (Large Language Models). In this crash course for LangChain, we are going to cover the following topics,

00:00 Introduction
00:22 What is Langchain?
04:38 Langchain installation and setup
06:28 LLMs, Prompt Templates
10:12 Chains
11:57 Simple Sequential Chain
15:30 Sequential Chain
18:00 Build Streamlit App
27:40 Agents
37:24 Memory

Link to the source code: https://codebasics.io/resource....s/langchain-crash-co

Langchain tutorial playlist: https://www.youtube.com/playli....st?list=PLeo1K3hjS3u

Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses.

Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

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Transformer Neural Networks are the heart of pretty much everything exciting in AI right now. ChatGPT, Google Translate and many other cool things, are based on Transformers. This StatQuest cuts through all the hype and shows you how a Transformer works, one-step-at-a time.

NOTE: If you're interested in learning more about Backpropagation, check out these 'Quests:
The Chain Rule: https://youtu.be/wl1myxrtQHQ
Gradient Descent: https://youtu.be/sDv4f4s2SB8
Backpropagation Main Ideas: https://youtu.be/IN2XmBhILt4
Backpropagation Details Part 1: https://youtu.be/iyn2zdALii8
Backpropagation Details Part 2: https://youtu.be/GKZoOHXGcLo

If you're interested in learning more about the SoftMax function, check out:
https://youtu.be/KpKog-L9veg

If you're interested in learning more about Word Embedding, check out: https://youtu.be/viZrOnJclY0

If you'd like to learn more about calculating similarities in the context of neural networks and the Dot Product, check out:
Cosine Similarity: https://youtu.be/e9U0QAFbfLI
Attention: https://youtu.be/PSs6nxngL6k

If you'd like to support StatQuest, please consider...
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channe....l/UCtYLUTtgS3k1Fg4y5

...buying my book, a study guide, a t-shirt or hoodie, or a song from the StatQuest store...
https://statquest.org/statquest-store/

...or just donating to StatQuest!
paypal: https://www.paypal.me/statquest
venmo: @JoshStarmer

Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
https://twitter.com/joshuastarmer

0:00 Awesome song and introduction
1:26 Word Embedding
7:30 Positional Encoding
12:53 Self-Attention
23:37 Encoder and Decoder defined
23:53 Decoder Word Embedding
25:08 Decoder Positional Encoding
25:50 Transformers were designed for parallel computing
27:13 Decoder Self-Attention
27:59 Encoder-Decoder Attention
31:19 Decoding numbers into words
32:23 Decoding the second token
34:13 Extra stuff you can add to a Transformer

#StatQuest #Transformer #ChatGPT

The attention mechanism is what makes Large Language Models like ChatGPT or DeepSeek talk well. But how does it work? One can see it as a mechanism that uses similarity to figure out what parts of the text to pay more or less attention to. For this, we use word embeddings.
I like to see word embeddings as words flying around in the universe, like planets and stars. In this case, the attention mechanism (the Keys, Queries, and Values matrices) define the fabric of this universe, and the laws of gravity, that resemble (yet in some ways are very different) to the laws of gravity that rule our universe.
Come join me in this celestial adventure in the universe of language!

See other videos in this LLM series
The attention mechanism in LLMs: https://www.youtube.com/watch?v=OxCpWwDCDFQ
The math behind attention mechanisms: https://www.youtube.com/watch?v=UPtG_38Oq8o
Transformer models: https://www.youtube.com/watch?v=qaWMOYf4ri8

Get the Grokking Machine Learning book!
https://manning.com/books/grokking-ma...
Discount code (40%): serranoyt
(Use the discount code on checkout)

01:55 Similarity
02:12 Embeddings
04:56 Attention
07:14 Dot product
09:29 Cosine similarity
11:10 The Keys and Queries matrices
14:19 Compressing and stretching dimensions
18:50 Combining dimensions
23:14 Asymmetric pull
40:57 Multi-head attention
45:14 The Value matrix
49:24 Summary

MIT Introduction to Deep Learning 6.S191: Lecture 3
Convolutional Neural Networks for Computer Vision
Lecturer: Alexander Amini
** New 2025 Edition **

For all lectures, slides, and lab materials: http://introtodeeplearning.com​

Subscribe to stay up to date with new deep learning lectures at MIT, or follow us @MITDeepLearning on Twitter and Instagram to stay fully-connected!!

🔥Enroll for Agentic AI Course: https://intellipaat.com/agenti....c-ai-systems-design-

🔥𝐁𝐨𝐨𝐤 𝐲𝐨𝐮𝐫 𝐅𝐫𝐞𝐞 𝐌𝐚𝐬𝐭𝐞𝐫𝐜𝐥𝐚𝐬𝐬: https://forms.gle/g5tExa7e54xpYZW97

Learn Agentic AI from scratch with this complete course covering the fundamentals, architecture, frameworks, and real-world concepts behind modern AI agents. Start by understanding the difference between Generative AI and Agentic AI, explore how Generative AI systems work, and learn the fundamentals of LangChain, AI Agents, and Agentic AI Design Patterns.

This course also covers Agentic Frameworks, Embeddings, Large Language Models (LLMs), and RAG Agents, helping you understand how AI systems can retrieve information, reason over context, and perform tasks autonomously. You’ll also learn about Model Context Protocol (MCP) and its role in connecting AI models with external tools and data sources.

Whether you’re a developer, AI/ML enthusiast, or someone looking to build the next generation of intelligent applications, this Agentic AI course gives you a structured foundation to understand and build AI agents. Follow the timestamps below to jump directly to the topic you want to learn.

📖 Below are the concepts covered in the video on "Agentic AI Full Course":
00:00:00 – Introduction to Agentic AI Course
00:00:37 – Generative AI vs Agentic AI
00:10:16 – What is a Generative AI System?
01:03:07 – What is LangChain
01:22:51 – AI Agents
01:41:09 – Agentic AI Design Patterns
02:32:56 – Agentic Frameworks & Basics
04:33:44 – Embeddings
05:05:12 – Large Language Model
06:53:23 – RAG Agent
07:51:25 – Model Context Protocol

#agenticai #learnagenticai #agenticaifullcourse #completeagenticaicourse #agenticai2026 #intellipaat #live

➡️ About the Course
The Agentic AI Systems & Design course by Intellipaat is an advanced program focused on building autonomous AI agents that can plan, reason, and execute tasks using tools like APIs, coding environments, and web search. Unlike traditional Generative AI courses, this program goes beyond prompt-based outputs and teaches you how to design production-grade AI systems capable of independent decision-making and complex problem-solving. It is ideal for professionals such as data scientists, AI/ML engineers, and developers who want to move from basic AI usage to creating intelligent, real-world applications powered by agentic workflows

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