Warp is free to try but for a limited time, you can try Warp Pro free for 7 days with 2,500 AI credits - no card required. Use my link https://go.warp.dev/forrestytcow

Everyone seems to be using AI to code now, and in this video, I'm showing you how to actually code with AI - not vibe code. Because there's a huge difference between software developers who strategically guide AI, and vibe coders who just let it take the wheel.

0:00 Everyone’s Coding with AI
0:32 Stop Repeating Yourself
1:45 Prompting is Important
4:21 The Software Development Workflow
6:42 Pair Programming
7:57 Implement Multiple Agents
9:25 git worktree
9:57 Extra Stuff AI Can Help With
11:21 Pull the Plug
11:58 Always Remember This

This video is sponsored by Warp.

If you're a developer, sign up to my free newsletter Dev Notes 👉 https://www.devnotesdaily.com/

If you're a student, checkout my Notion template Studious: https://notionstudent.com

Don't know why you'd want to follow me on other socials. I don't even post. But here you go.
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This video contains a practical roadmap to learn agentic AI using free learning resources and step by step study plan.

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Is AI-assisted coding the future? 🤔 Cedric Clyburn explores spec-driven development, a game-changing approach that combines LLMs with software development best practices. Learn how it differs from vibe coding, integrates SDLC principles, and improves coding workflows with requirements-driven precision. 🚀

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What is Artificial Intelligence? by Simplilearn is an introduction to artificial intelligence that deals with the fundamentals of artificial intelligence and its critical technicalities. Artificial Intelligence In five Minutes tutorial video will help you enhance your knowledge of Artificial Intelligence. This video on AI Explained by Simplilearn covers the most Critical AI Concepts in the simplest ways.

Don't forget to take the quiz at 03:50.

00:00:00 Introduction to What is AI?
This video segment on what is AI? will cover the briefing on Artificial Intelligence.

00:00:30 What is AI?
This section of the What is AI? video will give the technical definition of AI.

00:00:57 Types of AI
This section of the What is AI? video will cover the types of AI available in the industry.

00:01:46 Machine learning and Deep learning
This section of the What is AI? video will cover the aspects of machine learning and deep learning in detail.

00:02:30 Deep Learning and NLP
This section of the What is AI? video will cover the aspects of Deep Learning and NLP in detail.

00:02:45 AI in different fields
This section of the What is AI? video will cover the various fields where AI is currently operational.

00:03:30 Salary of AI engineer
This section of the What is AI? video will cover the salary details of AI engineers.

00:03:48 Quiz on What is AI?
This section of the What is AI? video will have a quick and simple quiz question on AI.

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- Use the NumPy and SciPy packages for high-level mathematical and technical computing and the Pandas package for data analysis.
- Learn about supervised and unsupervised learning methods such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN and pipeline and time series modeling.
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Find the full "AI Agents for Beginners" Course and code samples here ➡️ https://aka.ms/ai-agents-beginners

In this lesson:
00:00 Introduction
00:00 Lesson 1 What are AI agents?
5:55 Lesson 2 Which agent framework to use
14:14 Lesson 3 How to design good AI agents
19:35 Lesson 4 What is the Agent Tool Use Design Pattern?
25:47 Lesson 5 What is agentic RAG?
33:03 Lesson 6 How to build effective AI agents
38:54 Lesson 7: What is the AI Agent Planning Design Pattern?
44:20 Lesson 8 How to use a multi-AI agent system
51:22 Lesson 9 How can AI agents improve?
58:32 Lesson 10 How to deploy AI agents into production

🔥Advanced Certification in Agentic AI Engineering: https://www.edureka.co/agentic-ai-training-course
🔥 Integrated MS+PGP Program in Data Science & AI https://www.edureka.co/dual-ce....rtification-programs

In this video, we dive into the exciting developments and advancements that are set to shape the industry in 2025. We will learn what Agentic AI is and how it goes beyond traditional AI by acting with purpose and autonomy. You’ll discover 5 powerful secrets behind Agentic AI—from multi-agent collaboration to real-world tool integration and ethical guardrails. By the end, you’ll understand how Agentic AI is transforming industries and why it’s the future of intelligent systems.

Join us as we discuss the latest trends, innovations, and predictions for Agentic AI in 2025. Whether you're an AI enthusiast, a business leader, or simply curious about the future of technology, this video is for you.

00:00:00 Introduction
00:17:13 What is Agentic AI?
00:36:19 Agentic AI vs Generative AI
00:46:07 Agentic AI Roadmap
00:52:18 Introduction to Artificial Intelligence
00:58:37 Introduction to Deep Learning
02:28:29 Artificial Neural Network
03:08:09 Transformers Explained Using Generative AI
03:09:37 Transformers Neural Networks Explained
03:21:52 What are Large Language Models?
03:38:17 LLM vs SLM
03:41:59 What is LangChain?
03:59:35 What is RAG?
04:22:07 LLMOps: The Future of AI Development
04:29:57 Prompt Engineering
04:42:41 Natural Language Processing (NLP) & Text Mining using NLTK
05:22:21 KNN Algorithm using Python
05:45:23 Alibaba’s Qwen 2.5-Max Just Beat GPT-4 & DeepSeek?
05:49:47 DeepSeek vs OpenAI: Who Wins the AI Race?
06:02:06 Deep Learning Interview Questions

✅Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV
📝Feel free to share your comments below.📝
𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
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- - - - - - - - - - - - - -

What is Agentic AI?
Agentic AI refers to artificial intelligence systems that can autonomously make decisions, take actions, and pursue goals with minimal human intervention. Unlike traditional AI, which adheres to predetermined rules, agentic AI may dynamically adapt to new situations. It is widely utilized in robotics, virtual assistants, self-driving cars, and sophisticated decision-making processes.

What are the prerequisites for this Agentic AI Training Course?
In order to complete this course successfully, participants need to have a basic understanding of the Python programming language, machine learning, deep learning, natural language processing, generative AI, and prompt engineering concepts.

Who should take this AI Agents Training Course?
The Agentic AI online Training Course is ideal for AI enthusiasts, developers, and professionals looking to build autonomous AI agents. It is best suited for LLM Engineers, Generative AI Engineers, AI Research scientists, AI/ML practitioners, and freshers who want to leverage Agentic AI for automation and decision-making.

For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: +18885487823(toll-free).

#agenticai #aiagents #agenticaicourse #generativeai

The Dark Knight (2008)
Scene: HIT ME! (Batman vs Joker) - Joker gets Caught (IMAX Version 8K)
Director: Christopher Nolan
Writers: Jonathan Nolan (screenplay), Christopher Nolan (screenplay), David S. Goyer (story)
Cast: Christian Bale (Bruce Wayne \ Batman), Heath Ledger (Joker), Aaron Eckhart (Harvey Dent \ Two-Face), Michael Caine (Alfred), Maggie Gyllenhaal (Rachel), Gary Oldman (Gordon), Morgan Freeman (Lucius Fox), Monique Gabriela Curnen (Ramirez), Cillian Murphy (Scarecrow), Chin Han (Lau), Eric Roberts (Maroni)

Production Companies
Warner Bros. (presentation)
Legendary Entertainment (in association with)
Syncopy
DC Comics

WarnerMedia©

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🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐌𝐒 𝐄𝐱𝐜𝐞𝐥 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 : https://www.edureka.co/advance....d-ms-excel-self-pace (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This Edureka video on 'Excel Interview Questions' will help you prepare for your upcoming Excel interviews with the top 50 MS Excel Interview Questions and answers. Here are all the categories the questions are divided into:
00:00 Introduction
00:24 Agenda
00:42 General Excel Interview Questions
Excel Pivot Tables and Pivot Charts Interview Questions
Excel Formulas and Functions Interview Questions

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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
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Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.

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This video, "Who Is A Business Analyst" by Simplilearn, will help you understand who is a business analyst and what does a business analyst do. Here, you will be acquainted with the roles and responsibilities of a business analyst through an interesting story. Business analysts carry out several duties, so let's get started and look at a day in a business analyst's life.
The topics covered in this video on who is a business analyst are:
00:00:00 Who Is A Business Analyst?
00:00:55 Planning the Project
00:01:48 Understand the Business Objectives
00:02:11 Gather Requirements
00:02:34 Allocate Resources
00:03:06 Provide Suggestions
00:03:23 Collect Feedback
00:03:50 Build Reports
00:04:21 Conduct Meetings
00:04:42 Documentation and Presentation
00:05:31 Who Is a Business Analyst

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✅ Business Analysis Certification Overview

This Post Graduate Program in Business Analysis is for professionals looking to pursue a Business Analysis career, understand business analysis techniques, get hands-on experience, and for experienced analysts looking to learn the latest tools and frameworks used by Agile teams.

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🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

ChatGPT-4 Prompt Engineering: The Tree of Thoughts Process

𝐅𝐢𝐧𝐝 𝐭𝐡𝐞 𝐏𝐫𝐨𝐦𝐩𝐭 𝐓𝐞𝐦𝐩𝐥𝐚𝐭𝐞 𝐇𝐞𝐫𝐞:
https://www.allabtai.com/the-t....ree-of-thoughts-prom

Paper:
https://arxiv.org/abs/2203.02155

Get a FREE 45+ ChatGPT Prompts PDF here:
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Explore how AI can mimic human-like problem-solving with the revolutionary Tree of Thoughts (ToT) approach. Traditional AI methods fall short - ToT is the future, considering multiple reasoning paths like exploring a forest, not just one trail.

Witness how Prompt Engineering with ToT tackles complex problems more efficiently than ever before.

00:00 ChatGPT-4 Prompt Engineering: ToT Intro
00:25 What is the Tree of Thoughts Prompt Approach?
01:36 The Brainstorming Phase
03:59 The Evaluation Phase
06:19 The Expansion Phase
07:59 The Decision Phase

Learn how to build and deploy a SaaS using NextJS 13.4, DrizzleORM, OpenAI, Stripe, TypeScript, Tailwind, and Vercel. You will gain expertise in the following areas:
- Leveraging NextJS 13's cutting-edge App Router.
- Managing Payments seamlessly through Stripe.
- Harnessing the beauty of Shadcn and the power of Tailwind CSS.
- Unleashing the capabilities of OpenAI's API for Language Model usage.
- Interacting with databases with the efficiency of ORMs.

Resources
🔗 GitHub Repo: https://github.com/elliott-chong/chatpdf-yt
🔗 Vercel AI SDK: https://vercel.com/blog/introd....ucing-the-vercel-ai-
🔗 Timestamp 3:20:00 /api/chat/route.ts file https://pastebin.com/crLipeHK

Course developed by @elliottchong

⭐️ Contents ⭐️
⌨️ (0:00:00) Intro & Demo
⌨️ (0:09:53) Set Up NextJS
⌨️ (0:11:59) Set Up Shadcn
⌨️ (0:15:45) Set Up ClerkAuth
⌨️ (0:21:52) Home Page
⌨️ (0:33:22) DrizzleORM
⌨️ (0:50:15) File Upload Component
⌨️ (0:57:11) Set Up AWS S3
⌨️ (1:18:12) AI RAG Explanation
⌨️ (1:30:39) React Query Set Up
⌨️ (1:45:11) Set Up Pinecone DB
⌨️ (2:32:27) Chat Side Bar
⌨️ (2:47:42) PDF Viewer
⌨️ (2:50:33) Chat Component ( Vercel AI SDK )
⌨️ (3:08:02) Pinecone OpenAI Get Context
⌨️ (3:26:19) Persist Chat Logs to DB
⌨️ (3:34:16) Stripe Integration
⌨️ (4:14:59) Deploy and Outro

🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
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👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama

--

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

15 Jaw-Dropping Consequences of the Singularity (AGI IS CLOSER THAN YOU THINK!)

Welcome to our channel where we bring you the latest breakthroughs in AI. From deep learning to robotics, we cover it all. Our videos offer valuable insights and perspectives that will expand your knowledge and understanding of this rapidly evolving field. Be sure to subscribe and stay updated on our latest videos.

🔵 Intellipaat ReactJS training: https://intellipaat.com/react-....js-certification-tra
In this React Tutorial for beginners, you will learn everything about ReactJS from basic to advance level. This ReactJS course video includes DOM & Virtual DOM, the difference between Class, Functions, and Components, React hooks, ReactJS Bootstrap, Angular vs React, how to become ReactJS Developer, React Interview Questions, and lots of hands-on demos. This ReactJS for beginners video is a must-watch for everyone who wishes to learn ReactJS and make a career in it.

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React is a JavaScript library that specializes in helping developers build user interfaces or UIs. React on its own is a very functional, modular way to create expressive UI, and with its single responsibility mentality, it can be integrated with other systems as well as utilize its own ecosystem to develop full single page and multi-page apps.

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Ensemble Learning is a popular machine learning technique for building models. This video on Ensemble Learning covers the basics of Ensemble Learning Methods. You will learn about the Adaboost and Gradient boosting algorithm. You will get an understanding of the Xgboost technique. The video will make you learn how to create a model using Ensemble Learning. Finally, you will look into the model selection and cross-validation skills.

1. Ensemble Learning
2. Overview
3. Ensemble Learning Methods: Part a
4. Ensemble Learning Methods: Part B
5. Working with Adaboost
6. Adaboost Algorithm and Flowchart
7. Gradient Boosting
8. Xgboost
9. Xgboost Parameters: Part a
10. Xgboost Parameters: Partb
11. Demo: Pima Indians Diabetes
12. Model Selection
13. Common Splitting Strategies
14. Demo: Cross Validation
15. Key Takeaways

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This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

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Prepare for a job interview about deep learning. This course covers 50 common interview questions related to deep learning and gives detailed explanations.

✏️ Course created by Tatev Karen Aslanyan.

✏️ Expanded course with 100 questions: https://academy.lunartech.ai/p....roduct/deep-learning

⭐️ Contents ⭐️
⌨️ 0:00:00 Introduction
⌨️ 0:08:20 Question 1: What is Deep Learning?
⌨️ 0:11:45 Question 2: How does Deep Learning differ from traditional Machine Learning?
⌨️ 0:15:25 Question 3: What is a Neural Network?
⌨️ 0:21:40 Question 4: Explain the concept of a neuron in Deep Learning
⌨️ 0:24:35 Question 5: Explain architecture of Neural Networks in simple way
⌨️ 0:31:45 Question 6: What is an activation function in a Neural Network?
⌨️ 0:35:00 Question 7: Name few popular activation functions and describe them
⌨️ 0:47:40 Question 8: What happens if you do not use any activation functions in a neural network?
⌨️ 0:48:20 Question 9: Describe how training of basic Neural Networks works
⌨️ 0:53:45 Question 10: What is Gradient Descent?
⌨️ 1:03:50 Question 11: What is the function of an optimizer in Deep Learning?
⌨️ 1:09:25 Question 12: What is backpropagation, and why is it important in Deep Learning?
⌨️ 1:17:25 Question 13: How is backpropagation different from gradient descent?
⌨️ 1:19:55 Question 14: Describe what Vanishing Gradient Problem is and it’s impact on NN
⌨️ 1:25:55 Question 15: Describe what Exploding Gradients Problem is and it’s impact on NN
⌨️ 1:33:55 Question 16: There is a neuron in the hidden layer that always results in an error. What could be the reason?
⌨️ 1:37:50 Question 17: What do you understand by a computational graph?
⌨️ 1:43:28 Question 18: What is Loss Function and what are various Loss functions used in Deep Learning?
⌨️ 1:47:15 Question 19: What is Cross Entropy loss function and how is it called in industry?
⌨️ 1:50:18 Question 20: Why is Cross-entropy preferred as the cost function for multi-class classification problems?
⌨️ 1:53:10 Question 21: What is SGD and why it’s used in training Neural Networks?
⌨️ 1:58:24 Question 22: Why does stochastic gradient descent oscillate towards local minima?
⌨️ 2:03:38 Question 23: How is GD different from SGD?
⌨️ 2:08:19 Question 24: How can optimization methods like gradient descent be improved? What is the role of the momentum term?
⌨️ 2:14:22 Question 25: Compare batch gradient descent, minibatch gradient descent, and stochastic gradient descent.
⌨️ 2:19:12 Question 26: How to decide batch size in deep learning (considering both too small and too large sizes)?
⌨️ 2:26:01 Question 27: Batch Size vs Model Performance: How does the batch size impact the performance of a deep learning model?
⌨️ 2:29:33 Question 28: What is Hessian, and how can it be used for faster training? What are its disadvantages?
⌨️ 2:34:12 Question 29: What is RMSProp and how does it work?
⌨️ 2:38:43 Question 30: Discuss the concept of an adaptive learning rate. Describe adaptive learning methods
⌨️ 2:43:34 Question 31: What is Adam and why is it used most of the time in NNs?
⌨️ 2:49:59 Question 32: What is AdamW and why it’s preferred over Adam?
⌨️ 2:54:50 Question 33: What is Batch Normalization and why it’s used in NN?
⌨️ 3:03:19 Question 34: What is Layer Normalization, and why it’s used in NN?
⌨️ 3:06:20 Question 35: What are Residual Connections and their function in NN?
⌨️ 3:15:05 Question 36: What is Gradient clipping and their impact on NN?
⌨️ 3:18:09 Question 37: What is Xavier Initialization and why it’s used in NN?
⌨️ 3:22:13 Question 38: What are different ways to solve Vanishing gradients?
⌨️ 3:25:25 Question 39: What are ways to solve Exploding Gradients?
⌨️ 3:26:42 Question 40: What happens if the Neural Network is suffering from Overfitting relate to large weights?
⌨️ 3:29:18 Question 41: What is Dropout and how does it work?
⌨️ 3:33:59 Question 42: How does Dropout prevent overfitting in NN?
⌨️ 3:35:06 Question 43: Is Dropout like Random Forest?
⌨️ 3:39:21 Question 44: What is the impact of Drop Out on the training vs testing?
⌨️ 3:41:20 Question 45: What are L2/L1 Regularizations and how do they prevent overfitting in NN?
⌨️ 3:44:39 Question 46: What is the difference between L1 and L2 regularisations in NN?
⌨️ 3:48:43 Question 47: How do L1 vs L2 Regularization impact the Weights in a NN?
⌨️ 3:51:56 Question 48: What is the curse of dimensionality in ML or AI?
⌨️ 3:53:04 Question 49: How deep learning models tackle the curse of dimensionality?
⌨️ 3:56:47 Question 50: What are Generative Models, give examples?

For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-education

January 9, 2026
This lecture covers:
• How the ongoing integration of LLMs into our social worlds is creating new risks and opportunities
• Best practices for designing rehabilitative bots

To follow along with the seminar schedule, visit: https://hci.stanford.edu/

Jeremy Foote is an Assistant Professor in the Brian Lamb School of Communication at Purdue University and a faculty member in the Community Data Science Collective.

Learn more about AI in the SDLC here → https://ibm.biz/~naNTyKNWO

AI promises speed, but where are the real gains? Cedric Clyburn breaks down why productivity stalls across the software development lifecycle despite faster coding. Learn how redesigning SDLC workflows with AI agents improves outcomes, testing, and delivery.

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Hi 👋 I'm Samin. This channel is for you if you’re a business owner who wants to:
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You may be feeling stuck, trying to figure out how to attract consistent leads, increase your sales, and grow your business without burning out.

If that sounds like you I can help.

But why even listen to me?
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I’m an Ex-Amazon software engineer with over 6 years of experience
I have a computer science degree from NYU

00:00 Meet My AI Team
00:27 The Big Setup Questions
01:10 Why Build an AI Team?
01:43 The Business Bottleneck
02:28 Small Team, Bigger Output
03:08 Match the Model to the Job
03:44 From Separate Bots to a Team
04:29 How Buzz Brings It Together
5:09 Full tour of Buzz
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12:39 Subscriptions vs pay-per-token
16:39 Mac mini vs VPS
21:27 Setting up Buzz from scratch
27:58 Building an AI project manager
31:45 Making your agents debate