🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐂𝐨𝐮𝐫𝐬𝐞 - 𝐁𝐞𝐠𝐢𝐧𝐧𝐞𝐫𝐬 𝐭𝐨 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝: https://www.edureka.co/openai-....chatgpt-training-cou
This Edureka video on 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 will talk about multiple use cases where you can use ChatGPT. There are several day to day applications where you can leverage ChatGPT to do the job for you. Below are some important ChatGPT applications covered in this ChatGPT tutorial:
00:00:00 Introduction
00:00:50 ChatGPT for Writing Code
00:02:25 ChatGPT for Code Debugging
00:03:37 ChatGPT for Content Writing
00:05:03 ChatGPT for SEO
00:06:18 ChatGPT for Language Translation
00:07:01 ChatGPT for Writing Legal Documents
00:08:11 ChatGPT for College Assignments
00:08:37 ChatGPT to make Workout Schedule

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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

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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➡️ 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.

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- Capstone projects in 3 domains
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✅ Skills Covered

- Statistics
- Python
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➡️ 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

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Welcome to our comprehensive "Prompt Engineering Full Course," where you'll explore the fascinating world of prompt engineering and its extensive applications in AI technology. This ChatGPT Prompt Engineering Course in-depth tutorial is meticulously designed to help you master the art of crafting effective prompts, an essential skill for anyone working with AI models. We will start with the basics, understanding what prompt engineering is and why it is crucial in the realm of AI. Discover the numerous ways prompt engineering can be applied across various industries. From content creation and SEO to software development, data analysis, education, legal compliance, and customer support, this course provides real-world examples to illustrate the power and versatility of well-crafted prompts. Gain a deeper understanding of advanced topics such as tokenization, the ChatGPT memory feature, and how to customize GPT-4 for specific tasks. We’ll guide you step-by-step through crafting prompts for different use cases, providing detailed examples and DIY exercises to enhance your skills.

00:00:00 Introduction to Prompt Engineering
00:02:29 What is Prompt Engineering
00:03:11 Crafting Effective Prompts
00:04:04 Practical Examples Writing Effective Prompts
00:05:19 Exploring Prompt Engineering Use Cases in Various Sectors
00:07:09 Flow of AI Technologies
00:08:27 having an Overview of Openai and ChatGPT
00:10:28 Tokenization in ChatGPT
00:12:29 Exploring Customize ChatGPT Feature
00:13:26 Exploring GPT 4o and Temporary chat Section
00:13:40 Components required to craft an Effective Prompt
00:16:50 Exploring Prompts with Examples
00:21:56 Examples for crafting Prompts for various Use Cases
00:22:00 Crafting Prompt for Content Creation
00:25:34 Crafting Prompt for SEO Optimization
00:28:40 Crafting Prompt for Developers or Development Field
00:33:20 Crafting Prompt for Data Analysis
00:38:03 Crafting Prompt for Educational Purpose or Roadmaps
00:41:43 Crafting Prompt for Legal and Compliance Field
00:46:29 Crafting Prompt for Customer Support
00:53:50 Exploring ChatGPT's Memory Feature

✅What does prompt engineering do?
Prompt engineering involves crafting effective and specific prompts to guide AI models like ChatGPT in generating desired responses.

✅What is the salary for prompt engineering?
Salaries for prompt engineering can vary based on factors such as location, experience, and the specific industry.

✅What is prompt engineering in ChatGPT?
In ChatGPT, prompt engineering refers to the process of designing prompts or inputs that influence the responses generated by the model.

#PromptEngineering #AI #MachineLearning #ChatGPT #GenerativeAI #ArtificialIntelligence #2024 #Simplilearn #TechTraining

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➡️ About Artificial Intelligence Engineer

This Artificial Intelligence Engineer course Created in partnership with IBM, this course introduces students to blended learning and prepares them to be AI and Data Science specialists. In Armonk, New York, IBM is a significant cognitive service and integrated cloud solution firm that provides many technology and consulting solutions.

IBM is a leader in AI and Machine Learning technology verticals for 2021. This AI masters course will prepare students for Artificial Intelligence and Data Analytics careers.

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Machine Learning is one of those things that is chock full of hype and confusion terminology. In this StatQuest, we cut through all of that to get at the most basic ideas that make a foundation for the whole thing. These ideas are simple and easy to understand. After watching this StatQuest, you'll be ready to learn all kinds of new and exciting things about Machine Learning.

If you're interested in learning more about SoSA, here's the link: http://thesosa.org/

Here's the link to the video about the bias/variance tradeoff:
https://youtu.be/EuBBz3bI-aA

Here's the link to the video about cross-validation, aka the way to determine which samples go into your training set and which samples go into your testing set: https://youtu.be/fSytzGwwBVw

For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/

If you'd like to support StatQuest, please consider...

Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC

Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channe....l/UCtYLUTtgS3k1Fg4y5

...a cool StatQuest t-shirt or sweatshirt:
https://shop.spreadshirt.com/s....tatquest-with-josh-s

...buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/

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

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
0:35 A silly example of classification
2:24 A silly example of regression
3:37 The Bias/Variance Tradeoff
8:15 Fancy machine learning
8:56 Evaluating the performances of a decision tree
11:12 Summary of concepts and main ideas


#statquest #ML

Learn the essentials of working with AI in the cloud from @ExamProChannel. This comprehensive course covers the complete generative AI development lifecycle - from fundamental concepts through practical implementation, including prompt engineering, development tools, deployment, optimization, and advanced topics like RAGs and AI agents.

More course info: https://www.exampro.co/exp-genai-001

❤️ Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba)

⭐️ Contents ⭐️
- 00:00:00 Introduction
- 00:54:16 AI and ML Fundamentals
- 03:02:21 Gen AI Primer
- 03:32:55 Data and ML
- 03:47:56 LLM Basics
- 04:12:22 AI Powered Assistants
- 04:24:42 Env Setup
- 06:12:17 Prompt Engineering
- 07:00:25 WorkBenches and Playgrounds
- 07:44:09 Model as a Service
- 08:36:26 LLM DevTools and Workflow
- 11:52:07 AI Code Assistants
- 14:04:37 App Prototyping
- 17:21:06 Containers
- 18:12:43 Serving
- 18:19:51 AI Delivery Platform
- 19:40:45 GenAI Hardware
- 19:50:21 Framework
- 19:51:49 LLM Customization
- 19:52:35 SFT
- 19:56:25 Size Optimization
- 20:26:04 RAGS
- 22:21:19 Agents

🎉 Thanks to our Champion and Sponsor supporters:
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--

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

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Highlight: At 33:30 Josh Starmer, Statsquatch, and the Normalsaurus from @statquest have an awesome cameo!

Github repo: http://www.github.com/luisguis....errano/singular_valu

Grokking Machine Learning Book:
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40% discount promo code: serranoyt

In this video, we learn a very useful matrix trick called singular value decomposition (SVD), in which we express a matrix as a product of two rotation matrices and one scaling matrix.
We also show a very interesting application to image compression.

Similar videos:
Principal component analysis (PCA): https://www.youtube.com/watch?v=g-Hb26agBFg
Matrix factorization and Netflix recommendations: https://www.youtube.com/watch?v=ZspR5PZemcs

Introduction: (0:00)
Transformations: (0:50)
A puzzle: (1:27)
A harder puzzle: (2:21)
Linear transformations: (3:50)
Dimensionality reduction: (10:50)
Image compression: (23:57)

For a code implementation, check out this repo:
https://github.com/luisguiserr....ano/manning/tree/mas

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML
40% discount code: serranoyt

An introduction to support vector machines (SVMs) that requires very little math (no calculus or linear algebra), only a visual mind.
This is the third of a series of three videos.
- Linear Regression: https://www.youtube.com/watch?v=wYPUhge9w5c
- Logistic Regression: https://www.youtube.com/watch?v=jbluHIgBmBo

0:00 Introduction
1:42 Classification goal: split data
3:14 Perceptron algorithm
6:00 Split data - separate lines
7:05 How to separate lines?
12:01 Expanding rate
18:19 Perceptron Error
19:26 SVM Classification Error
20:34 Margin Error
25:13 Challenge - Gradient Descent
27:25 Which line is better?
28:24 The C parameter
30:16 Series of 3 videos
30:30 Thank you!

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Today we're diving deep into one of the hottest topics in AI right now. Building actual agents in Python. Not just chat bots to respond to your queries, but autonomous systems with memory goals and the ability to take actions in the world.

Want to make real money with coding? I share high-signal insights on careers, monetization, and leverage in my free newsletter. Join here and get my guide How to Make Money With Coding instantly: https://techwithtim.net/newsletter

⏳ Timestamps ⏳
00:00 | AI Agents
00:37 | NVIDIA Free AI Courses
01:38 | AI Agent Building Blocks
05:30 | Python Frameworks
09:01 | Python Tools
09:40 | AI Agent Patterns
13:15 | Picking Your Stack

Hashtags
#Nvidia #AiAgents #Python

Learn about the best AI Business models here - https://www.youtube.com/watch?v=Ta5g-OxjPO4

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This video contains affiliate links. If you buy through these links, I may earn a commission at no extra cost to you.

Anthropic’s Alex Albert (Claude Relations) sits down with Erik Schluntz (Multi-Agent Research and co-author of our blog post, Building Effective Agents) for a discussion on the evolution of agents over the past six months, including tips for building multi-agent systems, common multi-agent patterns, and best practices for using skills, MCP servers, and tools.

00:00 - Introductions
00:35 - Training Claude to tackle agentic tasks
1:30 - Making Claude more autonomous with code
3:20 - Using the Claude Agent SDK to build agents
5:00 - Tips for using Agent Skills
6:40 - The evolution of workflows and agents (workflows of agents)
8:30 - The value of simple agent architectures
9:30 - Building multi-agent systems: orchestrators, subagents, and tool calling
11:40 - Training Claude to use subagents
12:25 - Multi-agent use design patterns: parallelization, MapReduce, and test-time compute
13:20 - Coordinating problem solving with tools and subagents
14:15 - Common agent failure modes
15:00 - Best practices for getting started with building agents (context engineering, MCPs, and tools)
17:15 - The future of agents: coding, computer use, and beyond

Read the original blog post: https://www.anthropic.com/engi....neering/building-eff
Learn more about Agent Skills: https://www.anthropic.com/engi....neering/equipping-ag

Check out Kimi here! https://www.kimi.com/?utm_campaign=TR_grOjaW6m&utm_content=&utm_medium=Youtube&utm_source=CH_kEMBez3l&utm_term=

Timestamps ⏰
00:00 AI agents course!
01:13 Basics of AI Agents - What is an AI Agent?
02:58 What tasks are agents good for?
05:47 Spectrum of Autonomy
06:45 Context Engineering
07:13 Task Decomposition
07:59 Demo: No-Code Agent System
09:22 Intermediate AI Agents - Measuring Performance
10:39 Memory
11:42 Guardrails
12:50 Reflection
13:56 Tool Use
15:51 Designing Good Tools
16:56 Planning
19:05 Multi-Agent Collaboration
20:38 Multi-Agent System Design - Roles
21:25 Multi-Agent System Design - Communication Patterns
23:09 Multi-Agent System Design - Communication Pitfalls
23:44 Multi-Agent System Design - Best Practices
25:02 Demo: Multi-Agent System in Python
26:14 Advanced AI Agents - Advanced Task Decomposition
29:02 Improving Performance
30:26 Reducing Latency
31:16 Reducing Cost
32:39 Observability and Monitoring
35:10 Security
37:17 Bonus Resource!
----------------------------------------
Agentic System Design:
https://gerred.github.io/build....ing-an-agentic-syste

The slides and examples were adapted from a few different courses, including:
https://www.deeplearning.ai/co....urses/design-develop
https://learn.deeplearning.ai/....courses/agentic-ai/i
----------------------------------------
Want to become an AI Engineer? Download my AI Engineering Skills Checklist here: https://www.gratitudedriven.co....m/c/ai-engineering-c

💬 Want to talk 1:1? Book time to chat with me here: https://topmate.io/marina_wyss

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----------------------------------------
🎥 Other videos you might like:

AI Engineering in 76 Minutes (Complete Course/Speedrun!)
https://www.youtube.com/watch?v=JV3pL1_mn2M&t=2s

AI Engineering: A *Realistic* Roadmap for Beginners
https://www.youtube.com/watch?v=dbUIjFXIpis

4 *Real* Machine Learning Projects That Get You Hired - No More Tutorials!
https://www.youtube.com/watch?v=MFSFcPsMsuE

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🦫 About me
I am a Senior Applied Scientist (basically, a blend of Data Scientist/Machine Learning Engineer) at Twitch/Amazon. Outside of my full-time job I'm a 1:1 career coach for people looking to break into the field, with a focus on those from non-traditional backgrounds.

I’m also a Certified Personal Trainer, always busy with too many interests, and really, deeply happy with my life. I hope to be able to help others achieve these things, too.
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✉️ Contact
Instagram: https://www.instagram.com/marina.wyss/
Twitter/X: https://x.com/iammarinawyss
TikTok: https://www.tiktok.com/@gratitudedriven
Leave me a comment here on YouTube!
Business email: [email protected]

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⚖️ Disclaimer
The views and opinions expressed in this video are my own and do not reflect the official policy or position of Twitch/Amazon or any other company I have worked for. All advice and insights shared here are based on my personal experiences and should be considered as such.

Thank you to Kimi for sponsoring this video!

This description may contain affiliate links. If you make a purchase I may make a small commission at no cost to you.

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