For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai

This lecture covers:
1. The course (10 mins)
2. Human language and word meaning (15 mins)
3. Word2vec introduction (15 mins)
4. Word2vec objective function gradients (25 mins)
5. Optimization basics (5 mins)
6. Looking at word vectors (10 mins or less)

Key learning: The (astounding!) result that word meaning can be represented rather
well by a (high-dimensional) vector of real numbers

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs224n-natural

To follow along with the course schedule and syllabus visit: hhttps://web.stanford.edu/class..../archive/cs/cs224n/c

Professor Christopher Manning
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science
Director, Stanford Artificial Intelligence Laboratory (SAIL)

A complete guide to the mathematics behind neural networks and backpropagation.

In this lecture, I aim to explain the mathematical phenomena, a combination of linear algebra and optimization, that underlie the most important algorithm in data science today: the feed forward neural network.

Through a plethora of examples, geometrical intuitions, and not-too-tedious proofs, I will guide you from understanding how backpropagation works in single neurons to entire networks, and why we need backpropagation anyways.

It's a long lecture, so I encourage you to segment out your learning time - get a notebook and take some notes, and see if you can prove the theorems yourself.

As for me: I'm Adam Dhalla, a high school student from Vancouver, BC. I'm interested in how we can use algorithms from computer science to gain intuition about natural systems and environments.

My website: adamdhalla.com
I write here a lot: adamdhalla.medium.com
Contact me: [email protected]

Two good sources I recommend to supplement this lecture:

Terence Parr and Jeremy Howard's The Matrix Calculus You Need for Deep Learning: https://arxiv.org/abs/1802.01528

Michael Nielsen's Online Book Neural Networks and Deep Learning, specifically the chapter on backpropagation http://neuralnetworksanddeeple....arning.com/chap2.htm

ERRATA----
I'm pretty sure the Jacobians part plays twice - skip it when you feel like stuff is repeating, and stop when you get to the part about the "Scalar Chain Rule" (00:24:00).

And, here are the timestamps for each chapter mentioned in the syllabus present at the beginning of the course.

PART I - Introduction
--------------------------------------------------------------
00:00:52 1.1 Prerequisites
00:02:47 1.2 Agenda
00:04:59 1.3 Notation
00:07:00 1.4 Big Picture
00:10:34 1.5 Matrix Calculus Review
00:10:34 1.5.1 Gradients
00:14:10 1.5.2 Jacobians
00:24:00 1.5.3 New Way of Seeing the Scalar Chain Rule
00:27:12 1.5.4 Jacobian Chain Rule

PART II - Forward Propagation
--------------------------------------------------------------
00:37:21 2.1 The Neuron Function
00:44:36 2.2 Weight and Bias Indexing
00:50:57 2.3 A Layer of Neurons

PART III - Derivatives of Neural Networks and Gradient Descent
--------------------------------------------------------------
01:10:36 3.1 Motivation & Cost Function
01:15:17 3.2 Differentiating a Neuron's Operations
01:15:20 3.2.1 Derivative of a Binary Elementwise Function
01:31:50 3.2.2 Derivative of a Hadamard Product
01:37:20 3.2.3 Derivative of a Scalar Expansion
01:47:47 3.2.4 Derivative of a Sum
01:54:44 3.3 Derivative of a Neuron's Activation
02:10:37 3.4 Derivative of the Cost for a Simple Network (w.r.t weights)
02:33:14 3.5 Understanding the Derivative of the Cost (w.r.t weights)
02:45:38 3.6 Differentiating w.r.t the Bias
02:56:54 3.7 Gradient Descent Intuition
03:08:55 3.8 Gradient Descent Algorithm and SGD
03:25:02 3.9 Finding Derivatives of an Entire Layer (and why it doesn't work well)

PART IV - Backpropagation
--------------------------------------------------------------
03:32:47 4.1 The Error of a Node
03:39:09 4.2 The Four Equations of Backpropagation
03:39:12 4.2.1 Equation 1: The Error of the last Layer
03:46:41 4.2.2 Equation 2: The Error of any layer
04:03:23 4.2.3 Equation 3: The Derivative of the Cost w.r.t any bias
04:10:55 4.2.4 Equation 4: The Derivative of the Cost w.r.t any weight
04:18:25 4.2.5 Vectorizing Equation 4
04:35:24 4.3 Tying Part III and Part IV together
04:44:18 4.4 The Backpropagation Algorithm
04:58:03 4.5 Looking Forward

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New Claude Code Update is INSANE! (AI Coding Revolution)

Anthropic just released a massive update to Claude Code Desktop that transforms your computer into an autonomous AI coding machine. Discover how it handles everything from live app previews to automated PR merges while streamlining your entire development workflow. Learn why this update is a game-changer for developers and how to start using it today.

00:00 - Intro: The Massive Claude Update
01:04 - Live App Previews & Auto-Fixing
02:07 - Automated Local Code Reviews
02:47 - CI Failure Handling & Auto-Fix
03:26 - PR Monitoring & Auto-Merge
04:21 - Session Mobility Explained
04:48 - The Future of AI Development
06:59 - How to Get Started with Claude Code

🚀 Complete Agentic AI Course for Beginners in Telugu

Code files:
LangGraph code:
https://drive.google.com/file/....d/1l6N1T06ghWX-PpTSR

CrewAI code:
https://drive.google.com/file/....d/13QghlEBku_OCM5kYi

In this 3-hour full course, you will learn Agentic AI from scratch and understand how to build your own AI Agents step by step.

This course is explained in Simple Telugu and is perfect for beginners who want to learn modern AI Agent development.

What You Will Learn

✅ What is an AI Agent?
✅ AI Agent vs Chatbot
✅ How AI Agents think, plan, use tools and complete tasks
✅ LangGraph explained with practical workflow
✅ MCP — Model Context Protocol
✅ A2A — Agent-to-Agent Protocol
✅ CrewAI multi-agent systems
✅ OpenAI Agents SDK overview
✅ How to build AI Agents from scratch
✅ Real-world Agentic AI use cases

Topics Covered

🤖 AI Agents
🔷 LangGraph
🔗 MCP
🤝 A2A Protocol
👥 CrewAI
⚡ OpenAI Agents SDK
🧠 Agentic AI Architecture
💻 Practical AI Agent Projects

If you want to learn AI, Machine Learning, Generative AI and Agentic AI in Simple Telugu, subscribe to AI School of India.

Let’s make AI learning simple and practical 🚀

Hashtags

#AgenticAI #AIAgents #LangGraph #CrewAI #MCP #A2A #OpenAIAgentsSDK #GenerativeAI #ArtificialIntelligence #AIinTelugu #AISchoolOfIndia #MachineLearning #DataScience

Learn how to build smart AI workflows with N8N: automate tasks, connect apps, and deploy AI agents.

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Business Inquiries: [email protected]

Time Stamps:
00:00:00 — Introduction
00:02:57 — What's n8n?
00:04:44 — How to use it
00:12:42 — Core concepts
00:28:38 — Integrations
00:37:17 — AI Agents
00:39:06 — Inbox Manager overview
00:49:53 — Categorize new Emails
01:03:37 — Create issue tasks
01:22:38 — Generate draft replies

Build an AI agent that learns alongside you

In this free, end‑to‑end course, you’ll build a powerful language‑learning AI agent from scratch using Python, LangGraph, OpenAI, Ollama, and MCP. Over this hands‑on tutorial, we’ll create a ReAct‑style agent that sources vocabulary, performs accurate translations, and automatically generates Anki flashcards.

You’ll learn how to:
• Build a ReAct agent using LangGraph
• Connect agents to external tools with MCP
• Combine proprietary and local LLMs (OpenAI & Ollama)
• Design real‑world AI agent workflows

No NLP background required — we explain both the how and the why. By the end of this course, you’ll go from an empty Python project to a fully functional AI assistant you can adapt for your own AI projects.

Download PyCharm for free, the only Python IDE you need to build data models and AI agents: https://jb.gg/ai-agents-course

The full code for this tutorial, as well as the resources used, can be found in this GitHub repo: https://github.com/t-redactyl/....language-learning-ag
You can connect with Jodie, as well as see more of her work, at http://t-redactyl.io

Resources:
https://github.com/eymenefealt....un/all-words-in-all-
https://www.kaggle.com/datasets
https://www.kaggle.com/datasets?tags=13204-NLP
https://archive.ics.uci.edu/datasets
https://huggingface.co/learn/agents-course/

Timestamps
00:00 - Course Intro: What We’ll Build, AI agent tech stack
00:43 - What You’ll Learn: Building an AI Language Learning Agent
01:41 – Who This AI Agent Tutorial Is For (Python Prerequisites)
02:42 – Instructor Introduction: NLP & Data Science Background
03:01 – Why Use PyCharm for AI Agents & Data Science

Environment & Project Setup
03:36 – Installing PyCharm and AI Assistant
05:45 – Creating a Python Project with Virtual Environments

Dataset Selection & Preparation
07:26 – Choosing a Multilingual Vocabulary Dataset
08:46 – Best NLP Datasets: Kaggle & UCI Repositories
10:02 – Cloning and Organizing NLP Datasets in PyCharm

Installing Python & AI Dependencies
13:06 – Installing NLP Libraries: pandas, SpaCy, wordfreq
15:09 – Installing LangChain, LangGraph & MCP Libraries

Data Exploration & Analysis
16:56 – Exploring NLP Data with Jupyter Notebooks
18:01 – Analyzing Vocabulary Size Across Languages
20:45 – Visualizing Word Counts with Pandas Charts
22:08 – Identifying Data Problems in Multilingual Word Lists
24:36 – Introduction to SpaCy for Natural Language Processing

Cleaning the Word Lists
29:02 – Inspecting and Debugging Raw Vocabulary Data
31:48 – Removing Noise: Basic Text Cleaning Techniques
33:06 – Lemmatizing Words with SpaCy Models
35:10 – Using Zipf’s Law Overview to Filter Rare Words
37:26 – Word Frequency Analysis with wordfreq and SpaCy
42:35 - Understand Word Frequencies with wordfreq

Final Dataset Creation
45:22 – Building a Complete NLP Cleaning Pipeline
49:01 – Validating Results with a Spanish Dataset
50:01 – Comparing Raw vs Cleaned NLP Data

ReAct Agent Basics
54:40 – From Clean Data to an AI Agent
55:45 – What Is an AI Agent? Core Concepts
56:19 – Thought-Action-Observation Loop Explained
58:11 – Types of AI Agents

Large Language Models (LLMs) Explained
1:00:56 – How Large Language Models Understand Language
1:01:01 – Word Embeddings & Word2Vec Explained
1:05:24 – Why Word Embeddings Fail Without Context
1:06:05 – Transformers & Self-Attention Explained
1:10:23 – GPT Models and Decoder-Only Architectures

Reasoning Models for AI Agents
1:11:52 – Why Reasoning Models Power AI Agents
1:12:08 – How Reasoning Models Are Trained (Chain-of-Thought)
1:17:04 – When Not to Use Reasoning Models

1:20:24 How to Build a ReAct Agent with LangGraph
1:21:31 Agent State, Memory & Tools Explained
1:23:34 Choosing Between GPT-4 and Open-Source Models
1:26:36 How to Manage OpenAI API Keys Securely

1:30:09 How to Build Custom Tools for LangGraph Agents
1:33:14 Auto-Generating Tool Docstrings with AI
1:35:01 Improving Agent Reliability with System Prompts

1:38:13 Building and Connecting a LangGraph Agent Graph
1:41:21 Running an AI Agent End-to-End
1:43:02 How to Debug AI Agents in PyCharm
1:44:37 Visualizing Agent Execution Graphs

1:47:36 How to Run AI Agents Locally with Ollama
1:49:24 Choosing the Best Open-Source Reasoning Model
1:51:04 Installing and Managing Ollama Models
1:53:19 GPT-4 vs Ollama: Model Comparison for Agents

1:58:12 Switching LangGraph Agents from OpenAI to Ollama
2:00:22 Testing a Fully Local AI Agent

2:11:31 Adding Difficulty-Aware Vocabulary Tools
2:14:01 Handling Ambiguous User Requests in AI Agents
2:19:56 Testing AI Agents with Natural Language Prompts

2:24:48 How to Translate Words Using an LLM Tool
2:27:34 Building a Translation Tool with Ollama
2:32:28 Parsing Structured Output from LLMs

2:37:02 Multi-Step Tool Use in ReAct Agents
2:39:34 Handling Errors and Non-Determinism in AI Agents

2:41:40 What Is MCP (Model Context Protocol)?
2:42:13 Connecting AI Agents to External Tools with MCP

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In recent years, the spotlight in AI has primarily been on large language models (LLMs) and emerging large multi-modal models (LMMs). Now, building on these tools, a new paradigm is emerging with the rise of AI agents and agentic reasoning, which are proving to be both cost-effective and powerful for building numerous new applications. As AI continues to evolve, data across all industries, particularly unstructured data such as text, images, video, and audio, is becoming more critical than ever. In this keynote session from BUILD 2024, Andrews Ng, Founder and Executive Chairman of Landing AI, explores the rise of AI, agents, and the growing role of unstructured data. He also discusses how this convergence will shape automation and application building across industries.

Andrew Ng will be a featured speaker at Snowflake Dev Day 2025. Join us on June 5 in San Francisco. Registration is free and open now: https://www.snowflake.com/en/summit/dev-day

Watch the Snowflake Summit 2024 Opening Keynote featuring Snowflake CEO Sridhar Ramaswamy and OpenAI CEO Sam Altman, moderated by Sarah Guo, founder and managing partner of Conviction here: https://youtu.be/gJf39VG87O8

Check out Andrew Ng speaking about AI agentic workflows and their potential for driving AI progress here:
👉 https://www.youtube.com/watch?v=q1XFm21I-VQ

Register to watch more BUILD on-demand here:
👉 https://www.snowflake.com/build/

Enroll in the "Introduction to Generative AI with Snowflake" course on Coursera:
👉 http://coursera.org/learn/intro-generative-ai-course-snowflake/?utm_medium=institutions&utm_source=snowflake&utm_campaign=yt-promo

❄Join our YouTube community❄ https://bit.ly/3lzfeeB

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➡️ Careers: http://careers.snowflake.com
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#Snowflake #DataCloud

Build your own functional AI coding agent from the ground up using Python and the free Gemini Flash API. This project-based tutorial provides a deep understanding of how powerful AI tools work by guiding you through the creation of an agentic loop powered by tool calling. You will implement the core abilities for your agent to interact with and modify a codebase, including reading files, writing to files, and executing code to get feedback.

Lane Wagner created this course.

Check out the interactive version of the course on boot.dev: https://www.boot.dev/courses/build-ai-agent-python

❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp

⭐️ Contents ⭐️
- 00:00:00 Introduction
- 00:01:14 Why Build an AI Agent?
- 00:01:49 Course Overview & What We're Building
- 00:02:25 How to Follow Along
- 00:03:47 What is an AI Agent? (Agentic Loops & Tool Calling)
- 00:06:03 The Agent's Four Tools
- 00:07:58 Prerequisites & Project Goals
- 00:10:08 Demo: Agentic vs. One-Shot Responses
- 00:13:07 Python Project Setup with UV
- 00:15:44 Getting Started with the Gemini API
- 00:19:21 Making Your First API Call
- 00:24:44 Accepting Command-Line Arguments
- 00:27:46 Managing Conversation History
- 00:30:39 Adding a Verbose Flag for Debugging
- 00:33:35 Setting Up the Project for Our Agent (Calculator App)
- 00:36:23 Building Tool #1: Get Files Info
- 00:49:39 Building Tool #2: Get File Content
- 00:58:24 Building Tool #3: Write File
- 01:05:26 Security Note: Dangers of Running AI-Generated Code
- 01:07:30 Building Tool #4: Run Python File
- 01:18:00 Understanding the System Prompt
- 01:33:10 How Tool Calling Works: Declaring Functions for the LLM
- 01:41:38 Adding All Function Declarations
- 01:49:19 Implementing the Function Calling Logic
- 01:57:30 Creating the Agentic Loop
- 02:07:11 Final Demo: Agent Fixes a Bug Autonomously
- 02:13:44 Conclusion & Next Steps

🎉 Thanks to our Champion and Sponsor supporters:
👾 Drake Milly
👾 Ulises Moralez
👾 Goddard Tan
👾 David MG
👾 Matthew Springman
👾 Claudio
👾 Oscar R.
👾 jedi-or-sith
👾 Nattira Maneerat
👾 Justin Hual

--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news

Learn about generative models and different frameworks, investigating the production of text and visual material produced by artificial intelligence. This course was originally recorded live.

Instructors: Krish Naik, Sunny Savita, and Boktiar Ahmed Bappy.

For course details, visit: https://ineuron.ai/course/gene....rative-ai-community-

⌨️ (00:00:00) DAY 1: Introduction to Generative AI Community Course
⌨️ (01:44:14) DAY 2: Introduction to OpenAI and understanding the OpenAI API
⌨️ (03:37:49) DAY 3: Introduction to LangChain
⌨️ (05:16:48) Day 4: Hugging Face API + Langchain
⌨️ (07:13:08) DAY 5: Memory in Langchain
⌨️ (09:07:53) DAY 6: LLM Generative AI Project using OpenAI & LangChain
⌨️ (11:03:29) DAY 7: LLM Generative AI Project & Deployment
⌨️ (13:09:02) DAY 8: Introduction to Vector Database for AI & LLM
⌨️ (14:52:41) DAY 9: Mastering Vector Databases with Pinecone
⌨️ (17:02:19) DAY 10: Mastering ChromaDB Vector Databases
⌨️ (19:04:25) DAY 11: Introducing Meta Llama 2
⌨️ (20:54:33) DAY 12: End to End Medical Chatbot Project, Part 1
⌨️ (22:36:05) DAY 13: End to End Medical Chatbot Project, Part 2
⌨️ (24:22:10) Generative AI: Everything You need to know about Gemini Pro LLM Models
⌨️ (26:16:33) End to End Gen AI Project using Google Gemini Pro
⌨️ (28:24:14) Webinar - Generative AI Revolution: The Future

🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
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👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama

--

Learn to code for free and get a developer job: https://www.freecodecamp.org

Read hundreds of articles on programming: https://freecodecamp.org/news

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If this is your first video: I'm Nick Saraev. I run LeftClick, an AI growth agency. We've done work for large brands you're likely familiar with, like Mr. Beast, Anthropic, OpenAI, and a few others.

In plain English: I help people build systems that generate leads, close deals, and scale businesses, mostly using new AI models like Claude. I also make videos about how to do all of that here on YouTube.

It hasn't always been this way. My family immigrated from a Soviet bloc country (People's Republic of Bulgaria) in the 90s. They worked extremely hard, and we were broke for a very long time. I grew up wishing for more security, stability, and freedom over my own life.

I don't have a programming degree, and never took formal education for IT or workflows. I learned it all myself from YouTube videos like you're watching now.

As for my path: I started my first business at 19 in college. We threw events (mostly parties) at campus bars, and charged people for entry.

That failed to provide me enough money to pay my bills, so at 21, I started another business, a door-to-door marketing agency.

From there, every year, I would start several companies, over 10 in total. I did this in a variety of industries, like e-commerce, photography, videography, SaaS, credit repair, etc. Each grew slightly more profitable, until, at 25, I would start 1SecondCopy, a content writing company. A friend and I eventually scaled that to over $90,000/m. It was my first taste of financial independence, and the reason I'm here today.

Since starting my journey, I've grown a fair bit of capital. To diversify my income, at 30, I began investing in other businesses and advising companies on how to grow in the AI era. These include SaaS businesses, like Clairvo, agencies like Dental Connect, and more.

Collectively, the businesses that I own outright or are a part of generate over $10 million per year. This returns far more than the 5-10% you would get in the stock market, but also requires a lot of my active time. There's a tradeoff there, but I greatly prefer active investing, where I have control over the entities I'm a part of.

It wasn't easy to get here. But I did in the end! For anyone on their own entrepreneurial journey: I wish you luck, happiness, and perseverance. You can make it!

Summary ⤵️
Hey, this is an end to end, extremely comprehensive course all about AI agents. It covers the three modern agentic AI tools: Codex, Claude Code, and Antigravity, and is agnostic to whichever you use.

I will guide you through initial setup; workspace configuration; and then a variety of foundational to prompting techniques like self modifying agent instructions, multi agent MCP orchestration, video-to-action pipelines, agent chatrooms, subagent verification loops, prompt contracts, reverse prompting, and even more!

By the end, you will have learned, no fluff, both foundational AI agent design and advanced prompt engineering both. You will also have mastered a bunch of key agentic AI principles, like context management and token usage optimization! Thanks and happy watching!

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Chapters
00:00 Introduction to AI Agent Full Course
02:14 Multi-Agent Chrome MCP Workflow Demonstration
04:28 Core Agent Workflow
09:09 Understanding AI Agent Architecture
13:18 The Three Major AI Agent Platforms (Codex, Claude Code, Antigravity)
22:29 Platform-Specific Performance Insights
25:43 Self-Modifying System Prompts
34:57 Standardizing Workflows with Agent Skills
39:03 Multi-Agent Orchestration Strategies
47:20 Video-to-Action Pipeline
56:07 Implementing Stochastic Multi-Agent Consensus
1:04:44 Agent Suggestions Unveiled
1:05:08 Consensus Reports and Insights
1:06:05 Harnessing Multiple Agents
1:07:41 Agent Chat Rooms Explained
1:10:34 Debate and Collaboration Among Agents
1:13:25 Sub-Agent Verification Loops
1:17:32 The Mixture of Experts
1:20:56 Prompt Contracts Introduced
1:24:23 Crafting Effective Prompt Contracts
1:27:40 Reverse Prompting for Clarity
1:31:41 Context Management Strategies
1:37:34 Multi-Agent Chrome Automation
1:48:49 Understanding MCP Tools and Skills
1:53:34 Context Compression Techniques
1:59:19 Optimizing Token Usage
2:06:46 Cost-Efficient Multi-Agent Strategies
2:11:30 LLM Pricing Principles

🔥Artificial Intelligence Engineer Program (Discount Coupon: YTBE15): https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=Artificial-Intelligence-In-5-Minutes-ad79nYk2keg&utm_medium=DescriptionFirstFold&utm_source=youtube
🔥Professional Certificate Program In AI And Machine Learning: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=Artificial-Intelligence-In-5-Minutes-ad79nYk2keg&utm_medium=DescriptionFirstFold&utm_source=youtube

🔥 Caltech Post Graduate Program In AI And Machine Learning: https://www.simplilearn.com/artificial-intelligence-masters-program-training-course?utm_campaign=Artificial-Intelligence-In-5-Minutes-ad79nYk2keg&utm_medium=DescriptionFirstFold&utm_source=youtube

This video on "What is Artificial Intelligence" will give you a brief overview of artificial intelligence as a technology in just 5 minutes. We will start with a minor introduction to artificial intelligence in which we will know what is artificial intelligence with the help of examples. Moving ahead we will see what are the uses of AI, what is strong AI and what is weak AI. We will warp up this video by making you understand the major difference between AI ML and Deep Learning which will be followed by the future scope of artificial intelligence.

By the end of this video, you will understand:
00:00 What is Artificial Intelligence?
00:37 Uses of AI
01:48 What is AI
02:02 Weak AI
02:18 Strong AI
03:13 Difference between AI ML and Deep learning
05:00 Future of Artificial Intelligence

Don't forget to take the quiz at 04:10!

🔥 Enroll for FREE Artificial Intelligence Course & Get your Completion Certificate: https://www.simplilearn.com/learn-ai-basics-skillup?utm_campaign=Artificial-Intelligence-In-5-Minutes-ad79nYk2keg&utm_medium=DescriptionFirstFold&utm_source=youtube

Subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

Watch more videos on Artificial Intelligence: https://www.youtube.com/playli....st?list=PLEiEAq2VkUU

#AritificialIntelligence #WhatIsArtificialIntelligenceExactly #AritificialIntelligenceTutorial #WhatIsAi #WhatIsArtificialIntelligence #AiIn5Minutes #AITutorial #AITutorialForBeginners #AritificialIntelligenceBasics #AI #Simplilearn

What is Artificial Intelligence?
Artificial Intelligence or AI is the combination of algorithms used for the purpose of creating intelligent machines that have the same skills as a human being. It uses machine learning and deep learning techniques to build complex systems.

✅ About Caltech Post Graduate Program In AI And Machine Learning:

Designed to boost your career as an AI and ML professional, this program showcases Caltech CTME's excellence and IBM's industry prowess. The artificial intelligence course covers key concepts like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, and Reinforcement Learning through an interactive learning model with live sessions.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- PGP AI & ML completion certificate from Caltech CTME
- Masterclasses delivered by distinguished Caltech faculty and IBM experts
- Caltech CTME Circle Membership
- Earn up to 22 CEUs from Caltech CTME
- Online convocation by Caltech CTME Program Director
- IBM certificates for IBM courses
- Access to hackathons and Ask Me Anything sessions from IBM
- 25+ hands-on projects from the likes of Twitter, Mercedes Benz, Uber, and many more
- Seamless access to integrated labs
- Capstone projects in 3 domains
- 8X higher interaction in live online classes by industry experts

✅ Skills Covered
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- Recommendation Systems
- NLP
- Neural Networks
- GANs
- Deep Learning
- Reinforcement Learning
- Speech Recognition
- Ensemble Learning
- Computer Vision

✅ Tools Covered
- Python
- Keras
- TensorFlow
- Matplotlib
- Scikit Learn
- Django
- Flask
- OpenCV

✅ Eligibility Criteria

For admission to this Post Graduate Program in AI and ML, candidates should have:
- 2+ years of work experience preferred
- A bachelor's degree with an average of 50% or higher marks
- Basic understanding of programming concepts and mathematics

👉 Learn more at: https://www.simplilearn.com/artificial-intelligence-masters-program-training-course?utm_campaign=Artificial-Intelligence-In-5-Minutes-ad79nYk2keg&utm_medium=Tutorials&utm_source=youtube
🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

Agents are everywhere these days, but with so much information available, it’s easy to feel overwhelmed. Most tutorials and videos focus on specific frameworks without covering the fundamental principles behind these systems.

This course takes a different approach. Over four modules, you'll learn to implement the four core agentic patterns from scratch, using just Python and Groq LLMs:

* Reflection Pattern
* Tool Use Pattern
* Planning Pattern
* Multi-Agent Pattern

Explore the written lessons on my Substack blog:

https://theneuralmaze.substack.com/

Check out the code here:

https://github.com/neural-maze/agentic_patterns

––––––––––––––––––––––––––––––

If you like this content, you can also follow me here:

📩 Substack - https://theneuralmaze.substack.com/
💼 LinkedIn - https://www.linkedin.com/in/migueloteropedrido/
💻 GitHub - https://github.com/MichaelisTrofficus
🐦 Twitter - https://x.com/moteropedrido

––––––––––––––––––––––––––––––

––––––––––––––––––––––––––––––

0:00 Introduction
2:48 Module 1 - Reflection Pattern
20:40 Module 2 - Tool Pattern
44:22 Module 3 - Planning Pattern
1:13:16 Module 4 - MultiAgent Pattern
1:41:00 Conclusion

––––––––––––––––––––––––––––––
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MIT 18.642 Topics in Mathematics with Applications in Finance, Fall 2024
Instructor: Jake Xia
View the complete course: https://ocw.mit.edu/courses/18....-642-topics-in-mathe
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

In this video Jake Xia provides an overview of key financial concepts, including market structure, types of financial products like stocks, bonds, derivatives, and the roles of various market participants. He also introduces investment strategies, emphasizing the importance of understanding personal financial goals, risk management, and the use of mathematical models in pricing and trading, culminating in a practical trading game to apply these concepts.

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Support OCW at http://ow.ly/a1If50zVRlQ

We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.

El Machine Learning y el Deep Learning son clave para la evolución de la Inteligencia Artificial porque permiten que las máquinas puedan aprender y mejorar por sí mismas, logrando que estas máquinas puedan hacer tareas complejas y resolver problemas de manera autónoma. Pero, ¿qué es Machine Learning y Deep Learning exactamente? Te lo explicaremos en este nuevo video de EDteam.

Y si no lo sabías #LoAprendisteEnEDteam

🎉 ¡CURSOS NUEVOS DE LA SEMANA!
1. Curso: Android desde cero https://edy.to/android-yt
2. Curso: Desarrollo de apps con Vue 3 y TypeScript (Pre-venta) https://edy.to/vue-typescript-yt

Si quieres que EDteam de una conferencia gratis en tu institución, contáctanos aquí 👉 https://ed.team/conferencias

💻 Cursos recomendados:
- Carrera: Machine Learning e Inteligencia Artificial https://ed.team/especialidades/machine-learning
- Curso: Introducción al Machine Learning https://edy.to/ML-yt
- Curso: Introducción a las redes neuronales artificiales https://edy.to/redes-neuronales-yt
- Curso: Redes neuronales con TensorFlow https://edy.to/tensorflow-yt


📺 Videos recomendados
- ¿Qué es la Inteligencia Artificial y cómo está cambiando al mundo? https://www.youtube.com/watch?v=98-SzelNMzU
- ¿Qué es el Big Data? https://www.youtube.com/watch?v=M26iIqmqWkI&t=6s
- ¡Los peores errores de programación de la historia! https://www.youtube.com/watch?v=qi9nFs2caj4

⌚ Timeline:
00:00 - Introducción
00:59 - Que es Machine Learning
04:50 - Tipos de MAchine Learning
08:00 - Las Redes Neuronales
11:40 - El Deep Learning


- 🧑‍🎓👩‍🎓 ¿Eres estudiante? Postula a las becas de EDteam: https://edy.to/estudiantes-yt
- 🎁 ¡Accede a 9 cursos GRATIS de tecnología! https://edy.to/cursos-gratis-yt
- 🧑‍🏫 Dicta un curso en EDteam: https://edy.to/profesores-yt
- ⭐ Sube a premium y accede a cientos de cursos: https://edy.to/premium-yt
- 💻 Mira todos nuestros cursos en: https://edy.to/cursos-yt

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🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=-ZH7K_f8IxU&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Professional Certificate Program in Generative AI and Machine Learning - IITG (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=-ZH7K_f8IxU&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=-ZH7K_f8IxU&utm_medium=DescriptionFirstFold&utm_source=Youtube

The Generative AI Full Course 2025 provides a structured learning path from fundamentals to advanced AI concepts. Begin with What is Gen AI?, the Evolution of AI, and AI Careers in 2025. Explore DeepSeek R1, Deep Learning, and the Generative AI Roadmap to understand key trends. Dive into Search GPT, LangChain, and GANs (Generative Adversarial Networks), along with Transformers, LSTM, and LLMs. Strengthen your foundation with Machine Learning & Reinforcement Learning Tutorials. Advanced topics include Recurrent Neural Networks (RNNs), ChatGPT Analysis, OpenAI Sora, LLM Benchmarking, and Hugging Face. Conclude with Agentic AI, Google Quantum AI, and Top AI Tools for Job Interviews, ensuring industry readiness.

Following are the topics covered in the Gen AI Full Course for 2025:

00:00:00 Introduction to Gen AI Full Course 2025
00:00:45 What is Gen AI
00:11:17 Evolution of AI
00:22:02 AI Careers in 2025
00:44:49 Deepseek r1
00:51:48 Deep Learning
00:53:15 Roadmap Gen AI
01:09:58 Search GPT
01:12:13 Langchain
02:08:48 Generative Adversarial Tutorial
02:18:10 What are Gans
02:19:11 Transformers in AI
02:31:40 LSTM
02:33:04 Introduction to LLM
03:34:17 What is Machine Learning
04:30:49 Machine Learning Tutorial For Beginners
06:36:12 Reinforcement Learning
08:05:51 Recurrent Neural Network
08:25:42 Chatgpt analyze
08:36:38 Openai sora
08:45:31 LLM Benchmarking
09:36:14 Hugging Face and its tutorial
09:51:38 Open ai chatgpt o1 model
09:52:19 Top 10 AI Technologies
10:05:29 Gen ai tools for job interview
10:42:31 Agentic AI
10:50:54 Google Quantum AI

✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Artificial Intelligence training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULa5a

#genai #generativeai #artificialintelligence #ai #machinelearning #llm #simplilearn #2025

➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered:
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

Learning Path:
✅ IITG AI: Program Induction
✅ IITG AI: Programming Fundamentals
✅ IITG AI: Python for Data Science (IBM)
✅ IITG AI: Applied Data Science with Python
✅ IITG AI: Machine Learning
✅ IITG AI: Deep Learning with TensorFlow (IBM)
✅ IITG AI: Deep Learning Specialization
✅ IITG AI: Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ IITG AI: Advanced Generative AI
✅ IITG AI: Capstone
Electives:
✅ IITG AI: ADL & Computer Vision
✅ IITG AI: NLP and Speech Recognition
✅ IITG AI: Reinforcement Learning
✅ IITG AI: Academic Masterclass
✅ IITG AI: Industry Masterclass

👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=-ZH7K_f8IxU&utm_medium=Description&utm_source=Youtube

Full courses + unlimited support: https://www.skool.com/ai-autom....ation-society-plus/a
All my FREE resources: https://www.skool.com/ai-automation-society/about
Work with me: https://uppitai.com/

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In this video, I break down building an AI Agent so simply even a 10-year-old could do it! I’ll walk you through what an AI agent is and how to build a basic email agent in n8n that can automatically send emails for you.

No coding experience? No problem! I’ll guide you step-by-step, showing just how quick and easy you can get this set up. By the end of this video, you’ll have your very own email-sending AI agent up and running in no time.


Sponsorship Inquiries:
📧 [email protected]

WATCH NEXT:
https://youtu.be/u2Tuu02r7QI

TIMESTAMPS
00:00 Components of an AI Agent
03:50 Step 1: Chat Input
04:18 Step 2: Adding the Brain
05:49 Step 3: Adding Memory
07:45 Step 4: Adding Send Email Tool
10:21 Step 5: Adding Instructions (System Message)
12:04 Testing the Email Agent
13:43 Reviewing the Agent Log
15:00 Step 6: Adding Contact Database Tool
16:57 Final Test
18:05 Final Thoughts

Gear I Used:
Camera: Razer Kiyo Pro
Microphone: HyperX SoloCast
Background Music: https://www.youtube.com/watch?v=Q7HjxOAU5Kc&t=0s

Learn more: https://bit.ly/4mVUPyF

Building effective Agentic AI systems is one of the most valuable skills in AI today.

Introducing Agentic AI, a new course from Andrew Ng, now available on DeepLearning.AI.

While most developers build AI that just responds to prompts, the most productive teams are building AI that executes multi-step workflows autonomously. 

In this course, you'll learn how to build 4 key agentic workflows using raw Python so that you'll see how each step actually works.

Skills you’ll gain: 

- Build agentic design patterns: reflection, tool use, planning, and multi-agent workflows
- Integrate AI with external tools: databases, APIs, web search, and code execution
- Evaluate and optimize AI systems: performance metrics, error analysis, and production deployment

Build everything from scratch in Python—no frameworks, no black boxes.

Agentic AI is available exclusively on DeepLearning.AI. With a Pro membership you get access to quizzes, code labs, and Professional Certifications along with early access to our available catalog of advanced AI courses.

Enroll in Agentic AI on DeepLearning.AI: https://bit.ly/4mVUPyF

🔥Purdue - Applied Generative AI Specialization - https://www.simplilearn.com/applied-ai-course?utm_campaign=NhEhl7HonDA&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Professional Certificate Program in Generative AI and Machine Learning - IITG (India Only) - https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=NhEhl7HonDA&utm_medium=DescriptionFirstFold&utm_source=Youtube
🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=NhEhl7HonDA&utm_medium=DescriptionFirstFold&utm_source=Youtube

This ChatGPT Full Course by simplilearn provides a deep dive into AI technologies and applications, starting with the Top 10 AI Technologies and covering essentials like ChatGPT basics, Prompt Engineering, and Generative AI. It explores advanced topics such as ChatGPT 4 vs. ChatGPT 3.5, RAG vs. Prompt Tuning, and Prompt Injection, alongside practical applications like building apps, blogging, and creating Telegram bots with ChatGPT. Discover tools for automating tasks such as Excel, crafting PowerPoint presentations, and using LangChain. Other highlights include tutorials on GANs, OpenAI's Strawberry and Sora, and a guide to earning money with AI innovations like selling eBooks and job preparation in AI fields.

These are the following topics covered in the ChatGPT Full Course

00:00:00 Introduction to ChatGPT Full Course
00:00:41 Top 10 AI Technologies
00:18:08 Introduction to ChatGPT
00:23:19 What is Prompt Engineering
00:24:04 What is Gen AI
00:40:22 How to get Job in AI
00:40:59 ChatGPT 40 vs ChatGPT 4
01:17:07 Chatgpt analyse
01:18:14 Run Lama Privately
01:33:51 Search GPT
01:35:03 Sell Ebooks using ChatGPT
02:01:25 Build App Using ChatGPT
04:07:05 ChatGPT for Programming
04:22:02 Prompt Formulae Chatgpt
05:34:32 Automate Excel using Chatgpt
06:19:09 Generative Adversarial Tutorial
06:20:37 Blogging with ChatGpt
06:47:56 Powerpoint using Chatgpt
06:49:02 Rag Vs Prompt Tuning
07:01:16 Prompt injection
07:53:50 Telegram BOT using ChatGPT
07:54:50 How to Earn Money using ChatGPT
09:09:59 Prompt Engineering Tutorial
09:15:41 Open AI Strawberry Tutorial
09:26:37 Openai sora Tutorial
09:28:52 Langchain Tutorial
09:56:14 Open ai chatgpt o1 model
✅ Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

⏩ Check out the Artificial Intelligence training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULa5a

#gpt #chatgpt #chatgptforbeginners #chatgptcourse #genai #generativeai #artificialintelligence #ai #machinelearning #llm #simplilearn #2025

➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered:
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

Learning Path:
✅ Program Induction
✅ Programming Fundamentals
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning with TensorFlow (IBM)
✅ Deep Learning Specialization
✅ Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ Advanced Generative AI
✅ Capstone
Electives:
✅ ADL & Computer Vision
✅ NLP and Speech Recognition
✅ Reinforcement Learning
✅ Academic Masterclass
✅ Industry Masterclass

👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=NhEhl7HonDA&utm_medium=Description&utm_source=Youtube