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In this video, I break down how to build AI agents better than 99% of people by understanding what is an AI agent and how it actually works. You’ll learn AI agents explained step by step, follow a practical AI agents tutorial and AI agent tutorial, and see exactly how to build AI agents for real use cases. Whether you're looking for a structured AI agents course or want to build AI agents from scratch, this guide covers everything you need to get started.

00:00 - Intro: Building AI Agents Better Than 99% of People
01:28 - Free Base44 AI App Development Masterclass
02:01 - Chatbots vs AI Agents: The Mindset Shift
02:40 - Base44 Super Agents vs General Chat
04:32 - Natural Language Programming with Claude Opus 4.6
05:05 - Removing Technical Friction: No Servers or APIs
06:00 - Use Case 1: Automated AI Executive Assistant
06:55 - 24/7 Cloud Execution & AI Reliability
07:42 - Use Case 2: Market Scout & Travel Coordinator
10:12 - ChatGPT vs Zapier vs Base44 Execution
10:46 - Use Case 3: Full-Cycle Sales & CRM Agent
11:51 - Agent Memory: Training AI on Business SOPs
13:16 - Frictionless AI: Operating Inside WhatsApp & Slack
16:14 - Use Case 4: High-Speed Lead Nurturing Agent
17:28 - Use Case 5: Business Intelligence Data Analyst
20:26 - Live Build: Creating the Lead Pilot Super Agent
22:04 - Integration 1: Connecting Gmail to Base44
22:36 - Integration 2: Connecting HubSpot CRM
22:52 - Integration 3: Connecting WhatsApp Web
23:46 - Task Execution: Automating the Lead Workflow
24:38 - Live Testing the Automated Lead Pipeline
27:10 - Common Beginner Mistakes with AI Agents
28:33 - Cumulative Intelligence: Correcting AI Errors

For inquiries: Mikey (at) ytmedia.group

Want to learn more? I’m hosting a 6-week live BootCamp for AI Builders.
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This is the 6th video in a series on using large language models (LLMs) in practice. Here, I review key aspects of developing a foundation LLM based on the development of models such as GPT-3, Llama, Falcon, and beyond.

More Resources:
▶️ Series Playlist: https://www.youtube.com/playli....st?list=PLz-ep5RbHos Read more: https://towardsdatascience.com..../how-to-build-an-llm

[1] BloombergGPT: https://arxiv.org/pdf/2303.17564.pdf
[2] Llama 2: https://ai.meta.com/research/p....ublications/llama-2-
[3] LLM Energy Costs: https://www.statista.com/stati....stics/1384401/energy
[4] arXiv:2005.14165 [cs.CL]
[5] Falcon 180b Blog: https://huggingface.co/blog/falcon-180b
[6] arXiv:2101.00027 [cs.CL]
[7] Alpaca Repo: https://github.com/gururise/AlpacaDataCleaned
[8] arXiv:2303.18223 [cs.CL]
[9] arXiv:2112.11446 [cs.CL]
[10] arXiv:1508.07909 [cs.CL]
[11] SentencePience: https://github.com/google/sent....encepiece/tree/maste
[12] Tokenizers Doc: https://huggingface.co/docs/tokenizers/quicktour
[13] arXiv:1706.03762 [cs.CL]
[14] Andrej Karpathy Lecture: https://www.youtube.com/watch?v=kCc8FmEb1nY&t=5307s
[15] Hugging Face NLP Course: https://huggingface.co/learn/n....lp-course/chapter1/7
[16] arXiv:1810.04805 [cs.CL]
[17] arXiv:1910.13461 [cs.CL]
[18] arXiv:1603.05027 [cs.CV]
[19] arXiv:1607.06450 [stat.ML]
[20] arXiv:1803.02155 [cs.CL]
[21] arXiv:2203.15556 [cs.CL]
[22] Trained with Mixed Precision Nvidia: https://docs.nvidia.com/deeple....arning/performance/m
[23] DeepSpeed Doc: https://www.deepspeed.ai/training/
[24] https://paperswithcode.com/method/weight-decay
[25] https://towardsdatascience.com..../what-is-gradient-cl
[26] arXiv:2001.08361 [cs.LG]
[27] arXiv:1803.05457 [cs.AI]
[28] arXiv:1905.07830 [cs.CL]
[29] arXiv:2009.03300 [cs.CY]
[30] arXiv:2109.07958 [cs.CL]
[31] https://huggingface.co/blog/ev....aluating-mmlu-leader
[32] https://www.cs.toronto.edu/~hi....nton/absps/JMLRdropo

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Intro - 0:00
How much does it cost? - 1:30
4 Key Steps - 3:55
Step 1: Data Curation - 4:19
1.1: Data Sources - 5:31
1.2: Data Diversity - 7:45
1.3: Data Preparation - 9:06
Step 2: Model Architecture (Transformers) - 13:17
2.1: 3 Types of Transformers - 15:13
2.2: Other Design Choices - 18:27
2.3: How big do I make it? - 22:45
Step 3: Training at Scale - 24:20
3.1: Training Stability - 26:52
3.2: Hyperparameters - 28:06
Step 4: Evaluation - 29:14
4.1: Multiple-choice Tasks - 30:22
4.2: Open-ended Tasks - 32:59
What's next? - 34:31

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#MachineLearningInterviewQuestions #MLInterviewQuestions #MLInterviewPreparation #MachineLearningEngineerInterviewQuestions #MachineLearningInterview #MachineLearningInterviewQuestionsForFreshers #Intellipaat

This video, Top 30 Machine Learning Interview Questions 2025, brings you the most frequently asked questions and detailed answers to ace your next job interview. Whether you're a fresher or an experienced professional, these machine learning interview questions are designed to help you prepare effectively for roles like Machine Learning Engineer, Data Scientist, or AI Specialist.

Discover insights into key ML concepts, algorithms, and problem-solving techniques that hiring managers value. Learn about important machine learning interview questions and their answers. With this ML interview questions and answers for experienced and freshers guide, become confident in answering questions about various machine learning concepts. Look into the critical questions around concepts such as supervised and unsupervised learning, feature selection, model evaluation, and advanced ML techniques. Don't miss this video, because this is going to enhance your understanding of machine learning and going to help you crack your dream job. Watch now and get ready to shine in your ML interviews!

📖Below are the pointers covered in this 'ML Interview Questions and Answers' video:

🥇 00:00:00 - Introduction to Machine Learning Interview Questions

👨‍💻 ML Interview Questions for Freshers (Basic Level Machine Learning Engineer Interview Questions):
Q1. What is Machine Learning, and why is it important?
Q2. Differentiate between supervised, unsupervised, and reinforcement learning.
Q3. What is a model in machine learning, and how is it used?
Q4. Explain overfitting and underfitting with examples.
Q5. What is a confusion matrix, and how is it used in evaluating models?
Q6. Define cross-validation. Why is it important in model evaluation?
Q7. What is the role of precision and recall in evaluating a model?
Q8. What is the F1 score, and how is it calculated?
Q9. What is the purpose of regularization in machine learning?
Q10. Explain the bias-variance trade-off.

👨‍💻 Intermediate Level Machine Learning Interview Questions:
Q11. What is feature engineering, and why is it crucial in machine learning?
Q12. Example of when a False positive is more crucial than a false negative and vice versa
Q13. What does naivety stand for in naive Bayes?
Q14. Give an example where the median is a better measure than the mean.
Q15. What are the key differences between bagging and boosting in ensemble methods?
Q16. How does a decision tree work in machine learning?
Q17. What is the principal component analysis (PCA), and when should it be used?
Q18. How does a support vector machine (SVM) classify data?
Q19. What is a dropout in neural networks, and how does it prevent overfitting?
Q20. Differentiate between batch gradient descent and stochastic gradient descent.

👨‍💻 Advanced Level Machine Learning Interview Questions for Experienced:
Q21. You notice that your model is overfitting on the training data. What steps would you take to address this issue?
Q22. How would you evaluate a model's performance using a Receiver Operating Characteristic (ROC) curve?
Q23. Describe a situation where regularization (L1 or L2) significantly improved your model's performance.
Q24. You are given a dataset with imbalanced classes. How would you handle this during model training?
Q25. Explain GAN.
Q26. Explain CNN.
Q27. Explain how recurrent neural networks (RNNs) are used for time-series data. Provide an example.
Q28. What strategy would you use to tune hyperparameters for a Random Forest or gradient-boosting model?
Q29. Describe a real-world scenario where reinforcement learning could be applied effectively.
Q30. How would you optimize the training of a deep neural network on a large-scale dataset with limited computational resources?

✅ How do I prepare for a machine learning interview?
Preparing for a machine learning interview involves mastering the fundamentals of ML concepts like supervised and unsupervised learning, algorithms, and model evaluation techniques. Work on real-world ML projects to showcase hands-on experience and build a strong portfolio.

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Unlock the potential of ChatGPT in your data analysis journey! 📊

In this video, we delve into how ChatGPT, a powerful language model, can be a game-changer for interpreting and extracting insights from your data. From understanding its capabilities to implementing it in real-world scenarios, we've got you covered. Whether you're a seasoned data analyst or just getting started, join us to explore the fusion of AI and data analytics. Subscribe for in-depth tutorials and stay ahead in the world of data science!

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➡️ About Post Graduate Program In Data Analytics
This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

✅ Key Features
- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 8X higher live interaction in live online classes by industry experts
- Capstone from 3 domains and 14+ Data Analytics Projects with Industry datasets from Google PlayStore, Lyft, World Bank etc.
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Resume preparation and LinkedIn profile building
- 1:1 mock interview
- Career accelerator webinars

✅ Skills Covered
- Data Analytics
- Statistical Analysis using Excel
- Data Analysis Python and R
- Data Visualization Tableau and Power BI
- Linear and logistic regression modules
- Clustering using kmeans
- Supervised Learning

👉 Learn More At: https://www.simplilearn.com/post-graduate-program-data-science?utm_campaign=28Jan2024ChatGPTForDataAnalytics&utm_medium=Description&utm_source=youtube

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A quantum computer in the next decade could crack the encryption our society relies on using Shor's Algorithm. Head to https://brilliant.org/veritasium to start your free 30-day trial, and the first 200 people get 20% off an annual premium subscription.

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A huge thank you to those who helped us understand this complex field and ensure we told this story accurately - Dr. Lorenz Panny, Prof. Serge Fehr, Dr. Dustin Moody, Prof. Benne de Weger, Prof. Tanja Lange, PhD candidate Jelle Vos, Gorjan Alagic, and Jack Hidary.

A huge thanks to those who helped us with the math behind Shor’s algorithm - Prof. David Elkouss, Javier Pagan Lacambra, Marc Serra Peralta, and Daniel Bedialauneta Rodriguez.

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References:
Joseph, D., et al. (2022). Transitioning organizations to post-quantum cryptography. Nature, 605(7909), 237-243. - https://ve42.co/Joseph2022

Bernstein, D. J., & Lange, T. (2017). Post-quantum cryptography. Nature, 549(7671), 188-194. - https://ve42.co/Bernstein2017

An Insight, An Idea with Sundar Pichai - Quantum Computing, Wold Economic Forum via YouTube - https://ve42.co/QCWEFyt

Migrating to Post-Quantum Cryptography, The White House - https://ve42.co/PQCWhiteHouse

Kotas, W. A. (2000). A brief history of cryptography. University of Tennessee - https://ve42.co/Kotas2000

Hellman, M. (1976). New directions in cryptography. IEEE transactions on Information Theory, 22(6), 644-654. - https://ve42.co/Hellman1976

Rivest, R. L., Shamir, A., & Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21(2), 120-126. - https://ve42.co/Rivest1978

Kak, A. (2023). Lecture 12: Public-Key Cryptography and the RSA Algorithm - https://ve42.co/Kak2023

Calderbank, M. (2007). The RSA Cryptosystem: History, Algorithm, Primes. University of Chicago. - https://ve42.co/Calderbank2007

Cryptographic Key Length Recommendation, Keylength - https://ve42.co/KeyLength

Coppersmith, D. (2002). An approximate Fourier transform useful in quantum factoring. arXiv preprint quant-ph/0201067. - https://ve42.co/Coppersmith2002

Quantum Fourier Transform, Qiskit - https://ve42.co/Qiskit

Shor, P. W. (1994, November). Algorithms for quantum computation: discrete logarithms and factoring. In Proceedings 35th annual symposium on foundations of computer science (pp. 124-134). IEEE. - https://ve42.co/Shor1994

Shor’s algorithm, Wikipedia - https://ve42.co/ShorWiki

Euler’s totient function, Wikipedia - https://ve42.co/EulerWiki

Asfaw, A. (2020). Shor’s Algorithm Lecture Series, Qiskit Summer School - https://ve42.co/ShorYT

How Quantum Computers Break Encryption, minutephysics via YouTube - https://ve42.co/PQCmpyt

Breaking RSA Encryption - an Update on the State-of-the-Art, QuintessenceLabs - https://ve42.co/QuintessenceLabs

O'Gorman, J., & Campbell, E. T. (2017). Quantum computation with realistic magic-state factories. Physical Review A, 95(3), 032338. - https://ve42.co/OGorman2017

Gidney, C., & Ekerå, M. (2021). How to factor 2048 bit RSA integers in 8 hours using 20 million noisy qubits. Quantum, 5, 433. - https://ve42.co/Gidney2021

2021 Quantum Threat Timeline Report, Global Risk Institute - https://ve42.co/QuantumRisk

The IBM Quantum Development Roadmap, IBM - https://ve42.co/IBMQC

Post-Quantum Cryptography, Computer Security Resource Center (NIST) - https://ve42.co/CSRCPQC

Alagic, G., et al. (2022). Status report on the third round of the NIST post-quantum cryptography standardization process. US Department of Commerce, NIST. - https://ve42.co/Alagic2022

Thijs, L. (2015). Lattice cryptography and lattice cryptanalysis - https://ve42.co/Thijs2015

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Written by Casper Mebius & Derek Muller
Edited by Trenton Oliver
Filmed by Raquel Nuno
Animated by Ivy Tello & Mike Radjabov
Additional video/photos supplied by Getty Images & Pond5
Music from Epidemic Sound & Jonny Hyman
Produced by Derek Muller, Petr Lebedev, & Emily Zhang

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This Machine Learning tutorial video is ideal for beginners to learn Machine Learning from scratch. By the end of this tutorial video, you will learn why Machine Learning is so important in our lives, what is Machine Learning, the various types of Machine Learning (Supervised, Unsupervised and Reinforcement learning), .

This Machine Learning tutorial will cover the following topics:
1. Life without Machine Learning ( 01:06 )
2. Life with Machine Learning ( 02:29 )
3. What is Machine Learning ( 04:35 )
4. Machine Learning Process ( 05:27 )
5. Types of Machine Learning ( 06:14 )
6. Supervised Vs Unsupervised ( 09:32 )
7. The right Machine Learning solutions ( 10:35 )
8. Machine Learning Algorithms ( 13:33 )
9. Use case - Predicting the price of a house using Linear Regression ( 23:24 )

What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

Subscribe to our channel for more Machine Learning tutorial videos: https://www.youtube.com/user/S....implilearn?sub_confi

Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning, and follow the path towards your dream career- https://www.simplilearn.com/machine-learning-career-guide-pdf?utm_campaign=Machine-Learning-Tutorial-G7fPB4OHkys&utm_medium=Tutorials&utm_source=youtube

You can also go through the Slides here: https://goo.gl/aNmKbQ

Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Machine-Learning-Tutorial-G7fPB4OHkys&utm_medium=Tutorials&utm_source=youtube

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#MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse

- - - - - - - -

➡️ 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:




- - - - - - -

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

Einstein was wrong about black holes, what else? Use code veritasium at the link below to get an exclusive 60% off an annual Incogni plan: https://incogni.com/veritasium

A massive thank you to Prof. Geraint F. Lewis and Prof. Juan Maldacena for their expertise and help with this video.

A huge thank you to those who helped us understand this complicated topic: Dr. Suddhasattwa Brahma, Prof. Carlo Rovelli, Dr. Hal Haggard, Prof. Martin Bojowald, Dr. Francesca Vidotto, Prof. Andrew Hamilton, and Dr. Carl-Fredrik Nyberg Brodda.

A special thanks to Alessandro Roussel from ScienceClic for his spectacular simulations and feedback on the video. Check out his channel here: https://ve42.co/ScienceClic

An excellent book on this topic and an inspiration for this video: Cox, B., & Forshaw, J. (2023). Black holes: the key to understanding the universe.

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Special thanks to our Patreon supporters! Join the community to help us keep our videos free, forever: https://ve42.co/PatreonDE

Adam Foreman, Anton Ragin, Balkrishna Heroor, Bertrand Serlet, Bill Linder, Blake Byers, Burt Humburg, Chris Harper, Dave Kircher, David Johnston, Evgeny Skvortsov, Garrett Mueller, Gnare, gpoly, I. H., John H. Austin, Jr., john kiehl, Josh Hibschman, Juan Benet, KeyWestr, Kyi, Lee Redden, Marinus Kuivenhoven, Martin, Matthias Wrobel, Max Paladino, Meekay, meg noah, Michael Krugman, Orlando Bassotto, Paul Peijzel, Richard Sundvall, Sam Lutfi, Stephen Wilcox, Tj Steyn, Toni , TTST, Ubiquity Ventures, wolfee

If you’re looking for a molecular modeling kit, try Snatoms, a kit I invented where the atoms snap together magnetically - https://ve42.co/SnatomsV

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References:
Thorne, K. (1995). Black Holes & Time Warps: Einstein's Outrageous Legacy.
Relativity Playlist by ScienceClic - https://ve42.co/SCPlaylist
Hamilton, A. J. S. (2021). General Relativity, Black Holes, and Cosmology - https://ve42.co/Hamilton2021
Black Hole Events by PBS Space Time - https://youtu.be/vNaEBbFbvcY?l....ist=PLsPUh22kYmNBl4h
Newton’s Letters via The Newton Project - https://ve42.co/NewtonMail
Einstein, A. (1915). Die feldgleichungen der gravitation. - https://ve42.co/Einstein1915
Why Time and Space Swap by ScienceClic - https://youtu.be/GQZ3R81iyE0
Schwarzschild, K. (1916). Über das Gravitationsfeld eines Massenpunktes nach der Einsteinschen Theorie. - https://ve42.co/Schwarzschild1916
Wali, K. C. (1982). Chandrasekhar vs. Eddington—an unanticipated confrontation. - https://ve42.co/Wali1982
How to Build a Black Hole by PBS Space Time - https://www.youtube.com/watch?v=xx4562gesw0
Oppenheimer, J. R., & Volkoff, G. M. (1939). On massive neutron cores. - https://ve42.co/TOVLimit
Oppenheimer, J. R., & Snyder, H. (1939). On continued gravitational contraction. - https://ve42.co/Oppenheimer1939
Schwarzschild Geometry by Andrew Hamilton - https://ve42.co/SchwarzGeom
Why all world maps are wrong by Vox - https://www.youtube.com/watch?v=kIID5FDi2JQ
Hamilton, A. J., & Lisle, J. P. (2008). The river model of black holes. - https://ve42.co/HamiltonLisle2008
Mapping The Multiverse by PBS Space Time - https://www.youtube.com/watch?v=4v9A9hQUcBQ
Rotating black hole via Wikipedia - https://ve42.co/WikiRBH
Wormhole Travel by PBS Space Time - https://www.youtube.com/watch?v=ldVDM-v5uz0
Morris, M. S., & Thorne, K. S. (1988). Wormholes in spacetime and their use for interstellar travel. - https://ve42.co/MorrisThorne1988

Images & Video:
D3 Geo Projection Library by Mike Bostock https://ve42.co/d3geo
Interrupted Maps by Jason Davies https://ve42.co/DaviesMaps
Kazmierczak, J. et al. (2021). NASA’s NICER Tests Matter’s Limits. - https://ve42.co/NasaNICER
Bridgman, T. et al. (2024). M5.1 flare 'Double Whammy', at Active Regions 13559 and 13561. NASA SVS. - https://ve42.co/NasaFlare
Schnittman, J. et al. (2019). Black Hole Accretion Disk Visualization. - https://ve42.co/NasaAccrDisk
Wiessinger, S. et al. (2020). A Decade of Sun. NASA SVS. - https://ve42.co/NasaSunDecade
Skelly, C. et al. (2017). What is a Neutron Star? NASA SVS. - https://ve42.co/NasaNeutron
What would we see if we fell into a black hole by ScienceClic - https://youtu.be/4rTv9wvvat8
Earth texture - https://ve42.co/NASAEarth
First image of Sgr A* - https://ve42.co/EHT1
Image of M87 - https://ve42.co/EHT2
Polarized light image of Sgr A* - https://ve42.co/EHT3

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Directed by Casper Mebius
Written by Casper Mebius, Derek Muller and Will Wood
Edited by Trenton Oliver
Animated by Fabio Albertelli, Ivy Tello, Mike Radjabov, David Szakaly, Jonny Hyman, and Alessandro Roussel
Illustrated by Jakub Misiek
Filmed by Derek Muller
Additional research by Gregor Čavlović
Produced by Casper Mebius, Derek Muller, Will Wood, Giovanna Utichi, Rob Beasley Spence, Gregor Čavlović, and Emily Taylor

Thumbnail contributions by Jakub Misiek, Ren Hurley and Peter Sheppard
Additional video/photos supplied by Getty Images, Storyblocks, and NASA SVS
Music from Epidemic Sound

🔥𝐄𝐝𝐮𝐫𝐞𝐤𝐚'𝐬 𝐀𝐖𝐒 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞 "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") - https://www.edureka.co/aws-certification-training.
The "AWS Architect Full Course" is a thorough learning experience designed to help aspiring AWS architects gain essential knowledge. This Full Course covers core AWS services, best practices, security, and advanced topics such as serverless computing, giving you practical insights into designing and managing scalable solutions on the AWS cloud.

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟒 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
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In this AWS DevOps training video, you will learn everything about AWS and DevOps from basic to advanced levels. This video on AWS DevOps Tutorial For Beginners includes an introduction to DevOps, AWS, why DevOps with AWS, AWS code pipeline, hands-on project, and interview preparation. This is a must-watch session for everyone who wishes to learn AWS DevOps and make a career in the cloud domain.

00:00:00 Introduction
00:01:32 What is Data Engineering?
00:19:30 How to Become a Data Engineer?
00:21:03 Introduction to Big Data
00:53:02 How To Become A Big Data Engineer?
01:07:30 Hadoop Ecosystem
01:25:22 AWS services for data engineering
01:38:27 How to create EC2 Instances in AWS?
02:20:05 Amazon Virtual Private Cloud (VPC)
03:12:19 Amazon CloudWatch
03:41:20 AWS CloudFormation
03:58:24 AWS S3
04:38:04 Amazon Redshift
05:10:37 AWS Kinesis
05:31:32 AWS Lambda
05:38:20 AWS EMR
05:54:17 Getting Started with AWS Glue ETL
06:13:56 Apache Hive
07:14:27 Apache Sqoop Tutorial
07:32:19 AWS Interview Questions and Answers
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Hadoop is a famous Big Data framework; this video on Hadoop will acquaint you with the term Big Data and help you understand the importance of Hadoop. Here, you will also learn about the three main components of Hadoop, namely, HDFS, MapReduce, and YARN. In the end, we will have a quiz on Hadoop. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let's get started and learn all about Hadoop.

Don't forget to take the quiz at 05:11!

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➡️ Post Graduate Program In Data Engineering
This Data Engineering course is ideal for professionals, covering critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data on AWS, and Azure cloud infrastructures. This program is delivered via live sessions, industry projects, masterclasses, IBM hackathons, and Ask Me Anything sessions.

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This JavaScript Full Course 2023 by Simplilearn will take you through the most basic and advanced level concepts of JavaScript, and you'll be able to learn JavaScript in 12 hours only. In this JavaScript for Beginners video, we have covered everything you need to know and understand about the most essential block of web development. Additionally, you will also learn to create some fantastic projects with the help of all you will learn in this JavaScript Full Course 2023. Below are the topics we have covered in this JavaScript for Beginners video.

00:00:00 JavaScript Full Course 2023
00:03:56 Introduction To JavaScript
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➡️ About Post Graduate Program In Full Stack Web Development
This program will give you the foundation for building full-stack web apps using the Java programming language. You'll begin with the basics of JavaScript, and then venture into some of the more advanced concepts like Angular, Spring Boot, Hibernate, JSPs, and MVC. Now is the perfect time to get started on your career as a full-stack web developer!

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In this video, we’re diving into the Top 5 FREE AI Writing Tools for 2025 that can transform your content creation process. Whether you're writing blog posts, social media ads, or even fiction, these AI tools can help you write faster and smarter. From tools like Jasper and Rytr to Sudowrite and ChatGPT, we explore how each one can level up your writing game without breaking the bank.

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➡️ 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
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✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
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Skills Covered:
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✅ 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
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✅ 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
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✅ 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

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In this video on What is Search Engine Marketing, embark on a journey into the realm of Search Engine Marketing (SEM). Explore the fundamental concepts, unraveling the importance of SEM in today's digital landscape. We'll dive into the SEM vs. SEO comparison, understanding the nuances between these crucial strategies. Discover the inner workings of SEM, from the selection of keywords to the dynamics of ad auctions. Learn about essential SEM tools that empower successful campaigns. Gain insights into the intriguing world of ad auctions and explore effective SEM campaign strategies to enhance online visibility.

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This digital marketing course is meant for professionals looking to pursue a Digital Marketing career, know the fundamentals, and gain hands-on experience, as well as experienced marketers keen on learning the latest Digital Marketing skills. The Harvard Business case studies and projects on Google and Facebook add real-world experience.

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- And Many More
Note: 1 year of experience is preferred

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The Content Marketing Full Course by Simplilearn covers key areas such as creating content strategies, improving SEO, and using AI tools to boost marketing efforts. It begins with a Content Marketing Tutorial and explains how Google ranks websites through SEO audits and keyword research. The course features WordPress tutorials, MailChimp integration, and using ChatGPT for blogging, SEO optimization, and content creation. It also explores how to become a copywriter, sell ebooks using AI, and create digital products, highlighting modern methods to maximize digital marketing success.

Following are the topics covered in the Content Marketing Full Course:

00:00:00 - Introduction to Content Marketing Full Course 2025
00:01:53 - What is Digital Marketing
00:24:02 - Content Marketing for beginners
00:36:43 - Top 10 Digital Marketing Certifications For 2025
03:05:56 - Content Marketing Tutorial
04:14:40 - Content Marketing Strategy
04:21:57 - How does a Google rank Websites
04:36:09 - AEO Vs SEO
05:02:15 - Create Website using AI
05:10:35 - Keyword Research Tutorial
05:12:24 - Blogging with Chatgpt
05:27:27 - ChatGPT made SEO Easy
06:08:22 - Social Media marketing
06:29:16 - Youtube seo Optimization
06:37:33 - MailChimp Tutorial
07:02:12 - How to become copywriter
07:03:24 - Sell Ebooks using ChatGPT
07:39:59 - Create and sell digital products using AI
07:54:33 - ChatGPT for digital marketing
08:58:36 - DM Interview questions

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➡️ About Post Graduate Program In Digital Marketing:
Get a hands-on Live Interactive Learning experience with this Digital Marketing Course. Learn via fundamental and advanced material, preparing you for your Digital Marketing Career. Get a Meta Certified Digital Marketing Associate exam voucher worth USD $99 to showcase your skills.

Key Features
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Joint Purdue-Simplilearn Digital Marketer Certificate
✅ Become eligible to be part of the Purdue University Alumni Association
✅ Masterclasses delivered by Purdue faculty
✅ Harvard Business Publishing Cases
✅ Build your website & learn real-world hands-on digital marketing techniques
✅ Master sessions by Meta Blueprint trainer
✅ 6-credit transfer for the Purdue Online MS in Communication program
✅ Meta Certified Digital Marketing Associate exam voucher worth USD $99
✅ 5 Capstone problem statements and 15+ course-end projects
✅ 10+ case studies from brands like Adidas, KFC, Nike, Intel, etc.
✅ 35+ digital marketing tools
✅ Boost productivity with ChatGPT and AI tools (Blue Willow, Stable Fusion & Well Said Labs)
✅ Course aligned with Hootsuite and SE Ranking certification
✅ Learn using Meta Business Coach Chatbot
✅ Live classes delivered by Industry Experts along with self-paced content

Skills Covered
✅ Website Creation
✅ Behavioral Marketing
✅ Keyword Research
✅ Search Engine Optimization
✅ Search Engine Marketing
✅ Campaign Management
✅ Social Media Marketing
✅ Mobile Marketing
✅ Content Marketing
✅ Content Strategy
✅ Strategies for Paid Campaigns
✅ Analytics ROI and Evaluation
✅ AI Automation and Emerging Technology

👉Learn more at: https://www.simplilearn.com/advanced-digital-marketing-certification-training-course?utm_campaign=LXFtOs3qn7o&utm_medium=Lives&utm_source=youtube

🔥Artificial Intelligence Engineer (IBM) - https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=ML9AeEYLt0E&utm_medium=DecriptionFirstFold&utm_source=Youtube
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This Introduction to Artificial Intelligence Full Course by Simplilearn provides the best tutorial to learning AI. This AI Full Course begins with an Introduction to Artificial Intelligence that provides a complete overview of AI and its applications. The AI tutorial then proceeds by explaining what artificial intelligence is, followed by the AI engineer roadmap and insights into the future of artificial intelligence. You’ll learn core concepts like deep learning, machine learning, and the differences between AI, ML, and DL. The course highlights Gen AI, advanced tools like OpenAI Strawberry, and explains how to run Lama privately. You'll also explore LLM benchmarking, multimodal AI, and technologies like Transformers and LangChain. Key topics like AI bias, reinforcement learning, and recurrent neural networks are covered in-depth. Practical insights include AI coding tools, top AI certifications, beginner-friendly AI and ML projects, and tips to build a career in AI. By the end, you'll have the skills to tackle AI interview questions, build websites with AI, and advance in this dynamic field.

Following are the Topics covered in this AI Full Course 2025 by Simplilearn:

00:00:00 Introduction to Artificial Intelligence Full Course
00:08:08 What is Artificial Intelligence
00:16:33 Artificial Intelligence Engineer Roadmap
00:25:39 Future of Artificial Intelligence
00:32:38 Introduction to Deep Learning
00:44:42 Best Artificial Intelligence Coding tools
00:53:11 Top 7 Highest Paying AI Certificatsions
01:02:49 Top to learn technologies to learn
01:09:31 AI Carrers
01:10:16 What is Gen AI
01:20:48 AI Engieer Roadmap
01:35:53 How to get Job in Artificial Intelligence
02:32:30 What is Machine Learning
02:38:11 AI Bias
02:43:53 Open AI Strawberry
02:50:04 Difference between AI ML and DL
02:51:11 Run Lama Privately
02:59:55 Introduction to LLM
03:13:24 LLM Benchmarkeing
03:19:01 Mutimodel Artificial Intelligence
03:38:52 Chatgpt analyse
03:39:53 Transformers in Artificial Intelligence
07:04:07 Reinforcement Learning
07:04:57 Q Learning
07:27:58 Langchain Explained
07:38:57 Cursor AI
09:55:07 Recurrent Neural Network
10:12:52 ML Projects for Beginners
10:38:33 Build Website with AI
10:51:52 AI Projects For Beginners

✅Subscribe to our Channel to learn more about the top Technologies: https://www.youtube.com/user/Simplilearn

⏩ Check out the Artificial Intelligence tutorial videos: https://www.youtube.com/watch?v=ad79nYk2keg&list=PLEiEAq2VkUULyr_ftxpHB6DumOq1Zz2hq

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➡️ About Professional Certificate Course in Generative AI and Machine Learning

This AI ML program is designed to enhance your career in AI and ML by demystifying concepts like ML, DL, NLP, computer vision, generative AI, prompt engineering, and more. You'll also receive access to dedicated live sessions led by industry experts covering the latest trends in AI, such as generative modeling, ChatGPT, explainable AI, and more.

Key Features
✅ Program completion certificate from Purdue University and Simplilearn
✅ Live-online masterclasses delivered by Purdue faculty and IBM experts
✅ Live interactive sessions on the latest AI trends, such as ChatGPT, generative AI, prompt engineering, and more
✅ Core curriculum delivered in live classes by industry experts
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies
✅ Gain exposure to ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools
✅ 3 capstones and 25+ hands-on projects from various industry domains
✅ Access to Purdue’s alumni association membership on completion

👉Learn more at- https://www.simplilearn.com/iitk-professional-certificate-course-ai-machine-learning?utm_campaign=ML9AeEYLt0E&utm_medium=Decription&utm_source=Youtube