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Dawn Song is well-known for her research on the intersection of deep learning and security. Aside from her research, Song is also a Professor in the Department of Electrical Engineering and Computer Science at UC Berkeley and CEO of Oasis Labs, a blockchain startup that is creating a privacy-first cloud computing platform no blockchain. She has received several awards for her work including the MacArthur Fellowship, the Guggenheim Fellowship, and Best Paper awards from top conferences.

Andrew sits down with Song to chat about her unconventional career path and her current research projects.

Here’s what you’ll learn in the interview:

00:34: How Song first got started in deep learning and security
4:00: How Song self-designed a reading program structured around representational learning
13:22: How computer security can help deep learning
17:03: Song’s research on how to build resilient machine learning systems
21:55 How a “consistency check” approach can defend against attacks
25:31: Song’s work in AI and data privacy
27:49: How deep learning can help computer security
30:16: How Song’s startup, Oasis Labs, is creating privacy-preserving smart contracts
34:42: Song’s advice for learners breaking into a new field


Want to build your own career in deep learning? Get started by taking the Deep Learning Specialization.

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Graduation is not just a day when your studies formally end, but it is a testament to your hard work and dedication. Congratulations to the hardest-working candidates. Join us at our LIVE Graduation ceremony on the 23rd of March at 8PM

Welcome to the Online Convocation for Purdue - Simplilearn on 23rd March 2023.
Congratulations on your well-deserved success! Wishing you all great success ahead!

Our Guests of Honor are:

Prof Bart Collins, Purdue University
✅ Professor of Practice
✅ Director of Graduate Studies at Brian Lamb School of Communication
✅ Purdue University

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✅ Co-founder
✅ Chief Business Officer
✅ Simplilearn

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ChatGPT, an extraordinary creation of artificial intelligence. Born from the brilliance of OpenAI's GPT-3.5 architecture, ChatGPT is designed to engage, educate, and entertain. With a vast expanse of knowledge and the ability to adapt to individual preferences, ChatGPT is here to provide valuable insights, answer questions, and spark captivating conversations. From exploring various subjects to assisting with creative endeavors, ChatGPT is ready to embark on a journey of discovery with you. Whether you are a marketing expert, cybersecurity expert, a developer or a blogger, ChatGPT is all you need!
This full course on chatgpt, will help you to excel in it in digital marketing domain, cybersecurity, ui ux, content creation, seo. With this we will also put a light on how to use ChatGPT to make money!

00:00 Introduction to ChatGPT
06:16 How does ChatGPT work?
11:32 What is GPT 4?
15:11 Automate Excel using ChatGPT
01:27:57 How to use ChatGPT for SEO?
02:17:28 Chat GPT for Content Creation
02:26:21 Master SEO Content Using ChatGPT
02:28:08 ChatGPT for Marketing
02:38:50 How to Build a Website Using ChatGPT
03:20:50 How To Use ChatGPT For Web Development
03:36:57 Chat GPT for Programming
03:45:17 Can ChatGPT Solve LeetCode Problems?
05:11:49 Create a Telegram Bot Using ChatGPT
05:50:30 How To Integrate ChatGPT With Whatsapp
Automate WhatsApp using ChatGPT
06:06:14 Build a Game using Python and ChatGPT
06:38:44 ChatGPT in Cybersecurity
07:00:29 ChatGPT for UI/UX Design
07:47:42 Top 10 Chat GPT Use Cases
08:13:46 6 Reasons Why ChatGPT Can Make Your Business
08:23:19 9 Ways to Make Money Online Using ChatGPT
08:43:48 Bing vs Bard vs ChatGPT : Comparison
09:08:34 Will ChatGPT and Bard Take Over SEO?

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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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- Simplilearn's JobAssist helps you get noticed by top hiring companies
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- 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
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- Ensemble Learning
- Computer Vision

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This video on the "Artificial Intelligence full course" video cover all the topics you need to know to become a master in AI and ML. It covers all the basics of Machine Learning, the different types of Machine Learning, and the various applications of Machine Learning used in different industries. This video will also help us understand the basics of artificial intelligence. We will look at the future of AI and listen to some of the industry experts and learn what they have to say about AI. Finally, you will learn the Top 10 Artificial Intelligence Technologies In 2022.
Below are the topics covered in this AI and ML full course:

00:00:00 Artificial Intelligence Full Course 2022
00:01:45 Artificial Intelligence Basics
00:14:46 Top 10 AI Technologies 2022
00:24:47 Top 10 AI Companies for 2022
00:53:10 Machine Learning Algorithms
00:53:23 Linear Regression
01:02:08 Decision Tree
01:10:26 SVM
01:38:48 Clustering
01:39:31 K-means Clustering
02:09:11 Logistic Regression
02:35:34 KNN
05:04:16 Perceptron
07:19:27 RNN
08:13:01 Keras
09:25:19 CNN classification
10:06:38 Sequential Model

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#ArtificialIntelligenceFullCourse #AIFullCourse #AIAndMLFullCourse #MachineLearning #AIAndMachineLearning #ArtificialIntelligenceFullCourse #MachineLearningFullCourse #MachineLearningTutorial #AITutorial #AIAndML #Simplilearn

What Exactly is Machine Learning?
A good start at a Machine Learning definition is that it is a core sub-area of Artificial Intelligence (AI). ML applications learn from experience (data) like humans without direct programming. When exposed to new data, these applications learn, grow, change, and develop by themselves.

What is Artificial Intelligence?
Artificial Intelligence is a method of making a computer, a computer-controlled robot, or software think intelligently like the human mind. AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems.

➡️ About Post Graduate Program In AI And Machine Learning
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.

✅ Key Features
- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered
- ChatGPT
- Generative AI
- Explainable AI
- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
- And Many More…

👉Learn more at: https://www.simplilearn.com/artificial-intelligence-masters-program-training-course?utm_campaign=AIMLFC2oct2022&utm_medium=Description&utm_source=youtube

🎓Enhance your expertise in the below technologies to secure lucrative, high-paying job opportunities:
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Learn how to get your website online with a custom URL and website hosting.

The template website referenced in this video is down. Get the template here: https://drive.google.com/file/....d/1Zr80JIe30eJEUIx_8

In this course, you will first learn how to create a simple website using HTML, CSS, and JavaScript, starting with a website template. (If you already have a website—great! Just skip this section and go to the next one.) Then, you will learn how to get a custom URL. Finally, you will learn how to host your website files and make your custom URL point to your website files. You will learn two different ways to host your website, including a way to host your website for free!

This course was created by Beau Carnes.

🔗 Get a .TECH domain name: https://get.tech

🔗 Learn more about HTML and CSS: https://www.youtube.com/playli....st?list=PLWKjhJtqVAb

⭐️ Course Contents ⭐️
⌨️ (00:00) Introduction
⌨️ (00:34) Creating a website
⌨️ (38:41) Getting a custom URL
⌨️ (42:45) Getting web hosting
⌨️ (48:25) Creating a custom email address
⌨️ (48:25) Updating Nameservers
⌨️ (51:35) Hosting for free with GitHub Pages
⌨️ (56:08) Updating DNS Settings
⌨️ (59:15) Conclusion

⭐️ Special thanks to our Champion supporters! ⭐️
🏆 Loc Do
🏆 Joseph C
🏆 DeezMaster

This course was made possible in part by a grant from Radix, who own the .tech TLD.

Welcome to Micromouse, the fastest maze-solving competition on Earth. Join Onshape’s community of over 3 million CAD users by creating a free account here: https://Onshape.pro/Veritasium.

▀▀▀
A huge thank you to Peter Harrison for all of his help introducing us to the world of Micromouse – check out https://ukmars.org & https://micromouseonline.com.
Thank you to David Otten, APEC, and the All-Japan Micromouse Competition for having us.
Thank you to Juing-Hei (https://www.youtube.com/@suhu9379) & Derek Hall (https://www.youtube.com/@MicroMouse) for usage of their micromouse videos.
Thank you to John McBride, Yusaku Kanagawa, and Katie Barnshaw for their help with Japanese translations.

▀▀▀
References:
Claude Shannon Demonstrates Machine Learning, AT&T Tech Channel Archive - https://ve42.co/ClaudeShannon
Mighty mouse, MIT News Magazine - https://ve42.co/MightyMouse
History, Micromouse Online Blog - https://ve42.co/MMHistory
Christiansen, D. (1977). Spectral lines: Announcing the Amazing Micro-Mouse Maze Contest. IEEE Spectrum, vol. 14, no. 5, pp. 27-27 - https://ve42.co/Christiansen1977
Allan, R. (1979). Microprocessors: The amazing micromice: See how they won: Probing the innards of the smartest and fastest entries in the Amazing Micro-Mouse Maze Contest. IEEE Spectrum, vol. 16, no. 9, pp. 62-65, - https://ve42.co/Allan1979
1977-79 – “MOONLIGHT SPECIAL” Battelle Inst. (American), CyberNetic Zoo - https://ve42.co/MoonlightSpecial
Christiansen, D. (2014). The Amazing MicroMouse Roars On. Spectral Lines - https://ve42.co/Christiansen2014
1986 - MicroMouse history, competition & how it got started in the USA, via YouTube - https://ve42.co/MMArchiveYT
The first World Micromouse Contest in Tsubuka, Japan, August 1985 [1/2] by TKsTclip via YouTube - https://ve42.co/MMTsukubaYT
IEEE. (2018). Micromouse Competition Rules - https://ve42.co/IEEERules
Tondra, D. (2004). The Inception of Chedda: A detailed design and analysis of micromouse. University of Nevada - https://ve42.co/Tondra2004
Braunl, T. (1999). Research relevance of mobile robot competitions. IEEE Robotics & Automation Magazine, vol. 6, no. 4, pp. 32-37 - https://ve42.co/Braunl1999
All Japan Micromouse 2017 by Peter Harrison, Micromouse Online - https://ve42.co/RedComet
Winning record of the national competition micromouse (half size) competition. mm3sakusya @ wiki (Google translated from Japanese) - https://ve42.co/JapanFinishTimes
The Fosbury Flop—A Game-Changing Technique, Smithsonian Magazine - https://ve42.co/FosburyFlop
Gold medal winning heights in the Men's and Women's high jump at the Summer Olympics from 1896 to 2020, Statistica - https://ve42.co/HighJump
Zhang, H., Wang, Y., Wang, Y., & Soon, P. L. (2016). Design and realization of two-wheel micro-mouse diagonal dashing. Journal of Intelligent & Fuzzy Systems, 31(4), 2299-2306. - https://ve42.co/Zhang2016
Micromouse Turn List, Keri’s Lab - https://ve42.co/MMTurns
Green Ye via YouTube - https://ve42.co/Greenye
Classic Micromouse, Excel 9a. Demonstrate fan suction, by TzongYong Khiew via YouTube - https://ve42.co/MMFanYT
Vacuum Micromouse by Eliot, HACKADAY - https://ve42.co/MMVacuum

▀▀▀
Special thanks to our Patreon supporters:
Emil Abu Milad, Tj Steyn, meg noah, Bernard McGee, KeyWestr, Amadeo Bee, TTST, Balkrishna Heroor, John H. Austin, Jr., john kiehl, Anton Ragin, Diffbot, Gnare, Dave Kircher, Burt Humburg, Blake Byers, Evgeny Skvortsov, Meekay, Bill Linder, Paul Peijzel, Josh Hibschman, Mac Malkawi, Juan Benet, Ubiquity Ventures, Richard Sundvall, Lee Redden, Stephen Wilcox, Marinus Kuivenhoven, Michael Krugman, Sam Lutfi.

▀▀▀
Written by Tom Lum and Emily Zhang
Edited by Trenton Oliver
Animated by Ivy Tello
Coordinated by Emily Zhang
Filmed by Yusaku Kanagawa, Emily Zhang, and Derek Muller
Additional video/photos supplied by Getty Images and Pond5
Music from Epidemic Sound
Thumbnail by Ren Hurley and Ignat Berbeci
References by Katie Barnshaw
Produced by Derek Muller, Petr Lebedev, and Emily Zhang

Prepare for the course

🔥Edureka Machine Learning Certification Training: https://www.edureka.co/machine....-learning-certificat
This Edureka video on 'Statistics For Machine Learning' is the second class in the Python Machine Learning Series which gives a brief introduction to Statistics and Probability for Machine learning.

🟠 𝐂𝐥𝐚𝐬𝐬 𝐒𝐜𝐡𝐞𝐝𝐮𝐥𝐞 🟠

[𝗦𝗮𝘁𝘂𝗿𝗱𝗮𝘆 - 𝟭𝟱𝘁𝗵 𝗔𝘂𝗴𝘂𝘀𝘁]
Class 1 - Introduction To Machine Learning
Class 2 - Statistics For Machine Learning
Class 3 - Data Exploration 1 - ETL
Class 4 - Data Exploration 2 - Visualization
Class 5 - Data Exploration 3 - Data Cleaning
[𝐒𝐮𝐧𝐝𝐚𝐲 - 𝟏𝟔𝐭𝐡 𝐀𝐮𝐠𝐮𝐬𝐭]
Class 6 - Data Modeling 1 - Feature Engineering
Class 7 - Data Modeling 2 - Training The Model
Class 8 - Data Modeling 3 - Model Evaluation
Class 9 - Machine Learning Example
Class 10 - Advanced Machine Learning

Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s

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--------------------------
How it Works?

Edureka’s Machine Learning Course using Python is designed to make you grab the concepts of Machine Learning. Machine Learning training will provide a deep understanding of Machine Learning and its mechanism. As a Data Scientist, you will be learning the importance of Machine Learning and its implementation in the python programming language and many more.
--------------------------
Why Learn Machine Learning using Python?

Data Science is a set of techniques that enables computers to learn the desired behavior from data without explicitly being programmed. It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science. This course exposes you to different classes of machine learning algorithms like supervised, unsupervised and reinforcement algorithms.
--------------------------
Who should go for this Machine Learning Certification Training using Python?
- Developers aspiring to be a ‘Machine Learning Engineer'
- Analytics Managers who are leading a team of analysts
- Business Analysts who want to understand Machine Learning (ML) Techniques
- Information Architects who want to gain expertise in Predictive Analytics
- 'Python' professionals who want to design automatic predictive models
--------------------------
For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775

🔥Edureka Tensorflow Training (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"):
https://www.edureka.co/ai-deep....-learning-with-tenso
This Edureka "𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫𝐬 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐞𝐝" video will help you in understanding why we need Transformers and what exactly it is. It also explains few issues with training a Recurrent Neural Network and how to overcome those challenges using Transformers.

🔹Check our complete Deep Learning With TensorFlow playlist here: https://goo.gl/cck4hE
🔹Check our complete Deep Learning With TensorFlow Blog Series: http://bit.ly/2sqmP4s
🔴Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV

00:00 Introduction
00:41 Introduction to Deep Learning
04:48 NLP Using RNN
06:16 Scaling up NLP Task
08:13 Transformers Walk Through
10:16 Top Language Models


📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/
00:00 Agenda
01:28 Introduction to Deep Learning
08:24 What is Deep Learning
13:02 NLP using RNN
15:59 Scaling up NLP task
16:49 Transformers WalkThrough
19:51 Top Language Models

#Edureka #EdurekaDeepLearning #Transformersxplained #TransformerNeuralNetworks #DeepLearningLanguageModels #DeepearningTutorial #EdurekaTraining

---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------

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🔵 Microsoft Azure Online Training: https://bit.ly/3wsAhV4
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---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐬𝐭𝐞𝐫𝐬 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐬---------

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🔵 Data Scientist Masters Program: http://bit.ly/3qaVZJA
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🔵 Machine Learning Engineer Masters Program: http://bit.ly/3bxAhLG
🌕 Business Intelligence Masters Program: http://bit.ly/3byBhiS
🔵 Python Developer Masters Program: http://bit.ly/3nw4Rb2
🌕 RPA Developer Masters Program: http://bit.ly/3nw4Rb2

----------------------------------
How it Works?

1. This is 21 hrs of Online Live Instructor-led course. Weekend class: 7 sessions of 3 hours each.
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!

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About the Course
Edureka's Deep learning with Tensorflow course will help you to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions. This concept is then explored in the Deep Learning world. You will evaluate the common, and not so common, deep neural networks and see how these can be exploited in the real world with complex raw data using TensorFlow. In addition, you will learn how to apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained. Finally, the course covers different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.

Delve into neural networks, implement Deep Learning algorithms, and explore layers of data abstraction with the help of this Deep Learning with TensorFlow course.

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Why Learn Deep Learning With TensorFlow?
TensorFlow is one of the best libraries to implement Deep Learning. TensorFlow is a software library for numerical computation of mathematical expressions, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.

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

For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: https://stanford.io/ai

November 11, 2025
This lecture covers agents, prompts, and RAG.

To learn more about enrolling in this course, visit: https://online.stanford.edu/co....urses/cs230-deep-lea

Please follow along with the course schedule and syllabus: https://cs230.stanford.edu/syllabus/

More lectures will be published regularly.
View the playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

NOTE: There was no class on November 4, 2025 (Lecture 7). The previous lecture is Lecture 6.

Andrew Ng
Founder of DeepLearning.AI
Adjunct Professor, Stanford University’s Computer Science Department

Kian Katanforoosh
CEO and Founder of Workera
Adjunct Lecturer, Stanford University’s Computer Science Department

📌Generative AI Course: Masters Program : https://www.edureka.co/masters....-program/generative-
🔥Integrated MS+PGP Program in Data Science & AI:https://www.edureka.co/dual-ce....rtification-programs

Learn the fundamentals of generative artificial intelligence in this beginner-friendly course (2025 edition). We’ll cover what generative AI is, how it differs from traditional AI, key architectures (GANs, VAEs, Transformers), hands-on examples, prompt engineering, and real-world applications you can build today. No prior AI or deep-learning experience required.

✅ What you’ll learn:

What is generative AI & why it matters in 2026
Core models: GAN (Generative Adversarial Network), VAE (Variational Autoencoder)
Transformer architecture and large language models (LLMs)
Text-, image-, and audio-generation use cases
Basics of prompt-engineering and building your own simple GenAI app
Ethical, bias, and safety considerations for generative systems

📌 By the end of this course you’ll be equipped to explore your own generative-AI experiments and skill up for deeper tools.

🔔 If you enjoyed this video, Subscribe & hit the bell icon so you won’t miss further AI-tutorials in 2026. Leave a comment if you have questions or want to see a project walkthrough.

🔴 𝐋𝐞𝐚𝐫𝐧 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐅𝐨𝐫 𝐅𝐫𝐞𝐞! 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐂𝐡𝐚𝐧𝐧𝐞𝐥: https://edrk.in/DKQQ4Py

📝Feel free to share your comments below.📝

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🌕 RPA Online Training: http://bit.ly/3GFHKYB
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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

🔵 DevOps Engineer Masters Program: http://bit.ly/3Oud9PC
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🔵 Data Scientist Masters Program: http://bit.ly/3tUAOiT
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🔵 Machine Learning Engineer Masters Program: http://bit.ly/3AEq4c4
🌕 Business Intelligence Masters Program: http://bit.ly/3UZPqJz
🔵 Python Developer Masters Program: http://bit.ly/3EV6kDv
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🔵 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3Ov52lT

🌕 Advanced Certificate Program in Data Science with E&ICT Academy, IIT Guwahati: http://bit.ly/3V7ffrh

🔵 Advanced Certificate Program in Cloud Computing with E&ICT Academy, IIT Guwahati: https://bit.ly/43vmME8

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📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
📌𝐋𝐢𝐧𝐤𝐞𝐝𝐈𝐧: https://www.linkedin.com/company/edureka
📌𝐈𝐧𝐬𝐭𝐚𝐠𝐫𝐚𝐦: https://www.instagram.com/edureka_learning/
📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
📌𝐒𝐥𝐢𝐝𝐞𝐒𝐡𝐚𝐫𝐞: https://www.slideshare.net/EdurekaIN
📌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: +18885487823 (toll-free) for more information.

Get started with @GensparkProduct and get unlimited access to AI usage: https://bit.ly/4tBYC7v

New registered users can get free credits. What’s wild, Genspark is offering unlimited use of AI chat and AI image for all paid users in 2026. Unlimited subject to abuse guardrails.

Most people are still using AI like it's 2023 — open ChatGPT, ask a question, copy the answer. But there are actually four levels of AI usage, and the majority of people are stuck on level one without even knowing the other three exist. In this video, I'll walk through real demos of each level so you can see exactly how to apply them, including a live example of an AI agent that researches, builds, and deploys a full landing page — completely on its own.

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⏳ Timestamps ⏳
00:00 | Overview
01:16 | AI Framework
04:20 | Level 1 - Chat
06:00 | Level 2 - Tools
09:15 | Level 3 - Workflows
14:15 | Level 4 - Claw/Agents
18:32 | When to Use Each
19:56 | Genspark Usage

Hashtags
#Genspark #AIAgents #WorkwithGenspark

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