🔥 𝐓𝐨𝐩 𝟏𝟎 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐅𝐨𝐫 𝟐𝟎𝟐𝟒 (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): https://edrk.in/xK6MeNj
This Edureka video on "𝐓𝐨𝐩 𝟏𝟎 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐅𝐨𝐫 𝟐𝟎𝟐𝟒" video will introduce you to all the popular and trending IT certifications in the market which you should focus on in 2024 to get high paying job. These are the highest-paying certifications that you must bag in order to have a successful career in the year 2024. Let us know your list of Best IT Certifications For 2024 in the comment section below.

Below is the list of 𝐓𝐨𝐩 𝟏𝟎 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐅𝐨𝐫 𝟐𝟎𝟐𝟒 that you must get certified in to boost your career and paycheque:

00:00 Introduction to Top 10 Certifications For 2024
00:49 Cybersecurity Certifications
01:55 Cloud & DevOps Certifications
03:27 Project Management Certifications
04:21 Data Science Certifications
05:38 Scrum and Agile Certifications
06:28 Data Engineer Certifications
07:21 Business Intelligence Certifications
08:26 Automation and Testing Certifications
09:24 Full Stack Web Development Certifications
10:22 Digital Marketing Certifications

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📝Let us know your list of Top 10 Certifications For 2024 in the comment section.📝

#edureka #Top10Certifications #top10CertificationsFor2024 #Top10Certifications2024 #trendingCertifications2024 #trendingCertifications #bestCertifications #popularCertifications

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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🌕 Selenium Online Certification: https://edrk.in/Lt7ELSY
🔵 PMP Online Certification: https://edrk.in/baWg6pe
🌕 Salesforce Online Certification: https://edrk.in/EqlnJYd
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🌕 Java Online Certification: https://edrk.in/O6P3V2g
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🌕 Microservices Online Certification: https://edrk.in/JNoMEo8
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🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬

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📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟒 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩ NEW Top 10 Technologies To Learn In 2024 - https://www.youtube.com/watch?v=vaLXPv0ewHU

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
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📌𝐂𝐚𝐬𝐭𝐛𝐨𝐱: https://castbox.fm/networks/505?country=IN
📌𝐌𝐞𝐞𝐭𝐮𝐩: https://www.meetup.com/edureka/
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#AgileProjectManagementFullCourse #AgileCourse #AgileTraining #AgileTutorial #AgileCompleteCourse #WhatIsAgileProjectManagement #AgileTutorialForBeginners #AgileCompleteTutorial #Intellipaat

🔵 Following topics are covered in this session:
00:00:00 - Introduction to Agile Project Management
00:00:49 - What is SDLC
00:01:26 - Tenets of an Agile Approach
00:02:26 - Key Components
00:05:11 - Methods
00:07:35 - Who are the Users
00:08:44 - Benefits
00:10:19 - Models
00:19:28 - Why Agile
00:26:58 - Difference between Traditional vs Agile
00:40:55 - Agile Values
01:37:00 - Agile Roles
02:24:09 - What is Scrum
02:24:19 - Scrum Ceremonies
02:30:50 - Agile Planning Process
02:56:29 - Jira
03:26:33 - What is Product Backlog

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🔵 Why Agile is important

Agile Methodology is a development method in which requirements and solutions evolve in cross-functional teams through a collaborative effort. Its approach aligns project and product development with the requirements of the customer and overall company goals. It is a methodology based on iterative development. This process encourages frequent inspection and adaptation which helps in the rapid delivery of high-quality software. Agile methodology is developed for products and projects that require flexibility and speed- which actually means, almost every product and project is being managed today.

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🔥 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐂𝐨𝐮𝐫𝐬𝐞 𝐌𝐚𝐬𝐭𝐞𝐫 𝐏𝐫𝐨𝐠𝐫𝐚𝐦: https://www.edureka.co/masters....-program/machine-lea (𝐔𝐬𝐞 𝐂𝐨𝐝𝐞: 𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎)
This "Top 10 Applications of Machine Learning in 2021" video will give you an idea of how vast the machine learning is and how commonly you are using it in your day to day life.
Topics Covered:
00:00 Introduction
00:37 Google Map
02:02 Facebook
03:58 Uber/Uber Eats
05:12 Amazon
06:16 iPhone
07:51 Tesla
09:48 Netflix
10:25 Moley
11:38 Google Translate
12:42 Kuka
📝Feel free to comment your doubts in the comment section below, and we will be happy to answer📝

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

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---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐮𝐫𝐬𝐞𝐬---------

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--------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐏𝗼𝘀𝘁 𝗚𝗿𝗮𝗱𝘂𝗮𝘁𝗲 𝐂𝐨𝐮𝐫𝐬𝐞𝐬--------
🔵 Artificial and Machine Learning PGD with E & ICT Academy
NIT Warangal: https://bit.ly/3Kji6bb
🌕 Post Graduate Program in DevOps with Purdue University: https://bit.ly/3uoajDH

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟐 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢
⏩𝐓𝐨𝐩 𝟏𝟎 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐢𝐧 𝟐𝟎𝟐𝟮: https://bit.ly/3yhEs7S
⏩𝐓𝐨𝐩 𝟏𝟎 𝐇𝐢𝐠𝐡𝐞𝐬𝐭 𝐏𝐚𝐲𝐢𝐧𝐠 𝐉𝐨𝐛𝐬 𝐅𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3HcpPG6
⏩𝐓𝐨𝐩 𝟏𝟎 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬 𝐟𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3FW6F69
⏩𝐓𝐨𝐩 𝟏𝟎 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝟐𝟎𝟐𝟐: https://bit.ly/3gH57mr

📌𝐓𝐞𝐥𝐞𝐠𝐫𝐚𝐦: https://t.me/edurekaupdates
📌𝐓𝐰𝐢𝐭𝐭𝐞𝐫: https://twitter.com/edurekain
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📌𝐅𝐚𝐜𝐞𝐛𝐨𝐨𝐤: https://www.facebook.com/edurekaIN/
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📌𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐭𝐲: https://www.edureka.co/community/

About the Machine Learning with Python Training
Edureka’s Machine Learning Certification Training using Python is designed to make you grab the concepts of Machine Learning. This Machine Learning Certification 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. Furthermore, in this Machine Learning with Python Training, you will be taught Reinforcement Learning which in turn is an important aspect of Artificial Intelligence. You will be able to automate real-life scenarios using Machine Learning Algorithms. Towards the end of this Machine Learning online course, we will be discussing various practical use cases of Machine Learning with Python programming language to enhance your learning experience. Edureka offers the best Machine Learning Training online for those who want to be the best in Python. Enroll now with Edureka's online Machine Learning Certification to get trained with industrial experts.

What are the pre-requisites for this Machine Learning Certification Training ?
The pre-requisites for the Machine Learning Training include development experience with Python. Fundamentals of Data Analysis practiced over any of the data analysis tools like SAS/R will be a plus. However, Python would be more advantageous. You will be provided with complimentary “Python Statistics for Data Science Course” as a self-paced course once you enroll in the Machine Learning online course.

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In this video on Large Language Models Explainedwe will go through the basic understanding of what is large language model(LLM) in machine learning. In this machine learning video, we will cover topics like what is LLM, how large language model works, applications of large language models, and many more.
Below are the topics covered in this video:-
00:00 Large Language Models Explained
02:50 What are Large Language Models?
04:03 What are Large Language models used for?
04:27 How LLM trained
07:12 Applications of Large Language Models

🔵What are the large language models?
Large language models, such as GPT-3 (Generative Pre-trained Transformer 3), are advanced artificial intelligence systems designed to understand and generate human-like text. These models are built using deep learning techniques and have been trained on vast amounts of text data from the internet.

🔵What are large language models used for?

Large language models are utilized in scenarios where there is limited or no domain-specific data available for training. These scenarios include both few-shot and zero-shot learning approaches, which rely on the model's strong inductive bias and its capability to derive meaningful representations from a small amount of data or even no data at all.

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#LargeLanguageModels #LLM #MachineLearning #WhatisLargeLanguageModels #ChatGPT #AI #ArtificialIntelligence #Simplilearn

➡️ 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
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- 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…

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This KNN Algorithm in Machine Learningtutorial will help you understand what is KNN, why do we need KNN, and how KNN algorithm works using Python. You will learn how do we choose the factor 'K', when do we use KNN, with proper hands on demonstration to predict whether a person will have diabetes or not, using the KNN algorithm.

Below topics are explained in this K-Nearest Neighbor Algorithm (KNN Algorithm) tutorial:
00:00 Introduction to KNN(K Nearest Neighbor)
00:57 Why do we need KNN?
02:33 What is KNN?
03:51 How do we choose the factor 'K'?
05:46 When do we use KNN?
06:42 How does the KNN algorithm work?
09:19 Use case - Predict whether a person will have diabetes or not?


Dataset Link - https://drive.google.com/drive..../folders/1YylTjWxmkU

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You can also go through the slides here: https://goo.gl/XP6xcp

#KNNAlgorithmInMachineLearning #KNNAlgorithm #KNN #KNearestNeighbor #KNNMachineLearning #KNNAlgorithmPython #KNearestNegighborMachineLearning #MachineLearningAlgorithm #MachineLearning #Simplilearn

When Do We Use the KNN Algorithm?
The KNN algorithm is used in the following scenarios:
✅Data is labeled
✅Data is noise-free
✅Dataset is small, as KNN is a lazy learner

Pros and Cons of Using KNN
✅Pros: Since the KNN algorithm requires no training before making predictions, new data can be added seamlessly, which will not impact the accuracy of the algorithm.
KNN is very easy to implement. There are only two parameters required to implement KNN—the value of K and the distance function (e.g. Euclidean, Manhattan, etc.)
✅Cons: The KNN algorithm does not work well with large datasets. The cost of calculating the distance between the new point and each existing point is huge, which degrades performance.
Feature scaling (standardization and normalization) is required before applying the KNN algorithm to any dataset. Otherwise, KNN may generate wrong predictions.

➡️ 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
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Explore the capabilities of AI with our latest YouTube video on ChatGPT's revolutionary memory feature. In this How To Use ChatGPT Memory comprehensive video, we detail how ChatGPT remembers information from your past interactions to tailor and enhance your ongoing experiences. We'll guide you through how this memory mechanism captures essential information and seamlessly integrates it into future discussions. Through vivid real-life scenarios, we demonstrate the practical applications of this technology—from improving project management to customizing educational content and remembering personal preferences. This video is perfect for anyone curious about the practical impacts of AI in daily life and those interested in the technical aspects of how AI can adapt and learn over time. Tune in to discover how ChatGPT's memory is making AI interactions more intuitive and impactful.

In this How To Use ChatGPT Memory video, we start with:
00:00:00 Introduction to ChatGPT Memory Feature
00:01:18 Features of ChatGPT's Memory Feature
00:01:48 How to enable and Manage ChatGPT's Memory Feature
00:03:39 Introducing Temporary Chat Feature
00:06:21 Applications of ChatGPT's Memory Feature using prompts
00:10:52 Delete or Remove ChatGPT's Memory
00:15:31 Other Examples of ChatGPT's Memory Feature using prompts

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⏩ Check out More AI Videos By Simplilearn: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULyr_

➡️ 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…

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This chatgpt for digital marketing course will guide you will essential techniques for seo and content creation for your digital marketing needs.
ChatGPT revolutionizes digital marketing by streamlining content creation across platforms through its engaging blogs, social media posts, and persuasive copywriting, while also fostering customer engagement via instant responses on social media, personalized user experiences, and efficient automated customer support; it further aids in SEO efforts by suggesting relevant keywords, enables trend analysis for strategic insights, assists in content localization for global reach, facilitates the creation of interactive content like quizzes and polls, and even contributes to A/B testing variations, all of which collectively empower marketers to enhance efficiency, engagement, and overall campaign success.

00:00 ChatGPT For Digital Marketing
04:03 ChatGPT for marketing
14:22 How to use chatgpt for SEO
01:06:00 ChatGPT for content creation
01:10:20 Master SEO Content with ChatGPT
01:20:00 ChatGPT use cases
01:47:40 ChatGPT for Business
01:51:50 How to make money using chatgpt

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⏩ Check out the Machine Learning training videos: https://youtube.com/playlist?l....ist=PLEiEAq2VkUULYYg

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➡️ 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…

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Are you overwhelmed by complex data and unsure of how to interpret it? Do you want to enhance your data analysis skills? You've come to the right place! Our course is designed to teach you the essentials of Business Intelligence using Power BI.

Whether you're a student, a young professional, or a manager, this course is tailored for you. Led by expert instructor, you'll learn everything from connecting to data sources to creating interactive dashboards and visualizations. You'll discover how to transform and clean data, and how to use advanced features like tooltips, animations, and bookmarks to make your data more engaging. Additionally, you'll learn to design effective dashboards.

By the end of this course, you'll be proficient in analyzing and visualizing data, empowering you to make informed, data-driven decisions. You'll be equipped to elevate your data analysis skills and advance your career.

Don't miss this chance to unlock the full potential of your data. Start learning today! This educational YouTube series is a full course on Power BI, covering all essential features and functions. It's perfect for business analysts, data analysts, and anyone interested in Business Intelligence and data analytics. Led by Mr. Pavan Lalwani, this tutorial will guide you from the basics to advanced usage, helping you effectively utilize Power BI for data analysis and visualization.

You'll learn how to enhance your visualizations with Power BI tooltips, animations, and bookmarks, and design impactful dashboards. This course will provide you with the knowledge and skills needed to confidently analyze and present data using Power BI.

➡️ About PL-300 Microsoft Power BI Certification Training
* Aligned with PL-300: Microsoft Power BI Data Analyst certification
* Topics include Power BI Desktop layouts, BI reports, dashboards, DAX commands, and functions
* Learn to experiment, refine, prepare, and present data with ease
* Explore comprehensive Power BI training for hands-on applied learning
* Learn through a practical approach to help you gain expertise


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30+ hours of blended learning
Industry-based projects for experiential learning
Dedicated live sessions by faculty of industry experts
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- Desktop Layout
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In this tutorial, we’ll explore how GitHub Copilot can revolutionize your coding experience. We’ll show you step-by-step how to set it up in Visual Studio Code and use it to build a JavaScript application . From generating code snippets to solving logic problems, Copilot acts as your AI-powered coding partner. Get ready to see how Copilot makes coding faster, smarter, and more fun!

00:00 Introduction
01:35 What is Github Copilot ?
02:31 How does Copilot works ?
01:35 What is Github Copilot ?
04:41 Installing Github Copilot
09:31 Building a Javascript based Application using Github Copilot


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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
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

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

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

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

How to build your own Tiny Language Model from scratch - Luca Gilli - PyCon Italia 2025

Elevator Pitch:
Join us to discover Tiny Language Models: ultra-compact, resource-efficient AI tools that deliver impressive results. In this session, you’ll learn how to create your own model, from data preparation to training. These models combine innovation with efficiency, making AI more accessible than ever.

Learn more: https://2025.pycon.it/event/ho....w-to-build-your-own-

#MachineLearning #DeepLearning #NaturalLanguageProcessing

Want to get resources from this livestream? Sign up here so I can email them to you: https://www.lonelyoctopus.com/workshop

🤝 Business Inquiries: https://tally.so/r/mRDV99

🖱️Links mentioned in video
========================

🔗Affiliates
========================
My SQL for data science interviews course (10 full interviews):
https://365datascience.com/lea....rn-sql-for-data-scie

365 Data Science:
https://365datascience.pxf.io/WD0za3 (link for 57% discount for their complete data science training)

Check out StrataScratch for data science interview prep:
https://stratascratch.com/?via=tina

🎥 My filming setup
========================
📷 camera: https://amzn.to/3LHbi7N
🎤 mic: https://amzn.to/3LqoFJb
🔭 tripod: https://amzn.to/3DkjGHe
💡 lights: https://amzn.to/3LmOhqk

⏰Timestamps
========================
00:00 intro

📲Socials
========================
instagram: https://www.instagram.com/hellotinah/
linkedin: https://www.linkedin.com/in/tinaw-h/
discord: https://discord.gg/5mMAtprshX

🎥Other videos you might be interested in
========================
How I consistently study with a full time job:
https://www.youtube.com/watch?v=INymz5VwLmk

How I would learn to code (if I could start over):
https://www.youtube.com/watch?v=MHPGeQD8TvI&t=84s

🐈‍⬛🐈‍⬛About me
========================
Hi, my name is Tina and I'm an ex-Meta data scientist turned internet person!

📧Contact
========================
youtube: youtube comments are by far the best way to get a response from me!
linkedin: https://www.linkedin.com/in/tinaw-h/
email for business inquiries only: [email protected]

========================
Some links are affiliate links and I may receive a small portion of sales price at no cost to you. I really appreciate your support in helping improve this channel! :)

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

To learn more about enrolling in this course visit: https://online.stanford.edu/co....urses/cs336-language

To follow along with the course schedule and syllabus visit: https://stanford-cs336.github.io/spring2025/

Percy Liang
Associate Professor of Computer Science
Director of Center for Research on Foundation Models (CRFM)

Tatsunori Hashimoto
Assistant Professor of Computer Science

View the entire course playlist: https://www.youtube.com/playli....st?list=PLoROMvodv4r

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

Explore the future of artificial intelligence with Agentic AI! In this video, we dive into the exciting developments and advancements that are set to shape the industry in 2026. 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 2026. Whether you're an AI enthusiast, a business leader, or simply curious about the future of technology, this video is for you. Stay ahead of the curve and discover what's next for Agentic AI!

00:00:00 Introduction
00:01:28 What is Agentic AI?
00:12:20 Agentic AI vs Generative AI
00:33:33 Alexa+ Powered by Generative AI
00:44:47 Agentic AI Roadmap
00:51:15 Introduction to Artificial Intelligence
01:10:03 Introduction to Deep Learning
02:27:26 Artificial Neural Network
02:59:26 Transformers Explained Using Generative AI
03:07:05 Transformers Neural Networks Explained
03:14:29 What are Large Language Models?
03:35:28 What is Multimodal AI?
03:52:46 LLM vs SLM
03:58:14 What is LangChain?
04:15:29 Langchain Agents Explained
04:22:44 What is RAG?
04:45:32 LLMOps: The Future of AI Development
04:51:55 Prompt Engineering
05:06:09 Natural Language Processing (NLP) & Text Mining using NLTK
05:44:52 KNN Algorithm using Python
06:03:11 Alibaba’s Qwen 2.5-Max Just Beat GPT-4 & DeepSeek?
06:07:35 DeepSeek Training Cost: How China Built AI for Less
06:13:04 DeepSeek vs OpenAI: Who Wins the AI Race?
06:25:36 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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📌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/

- - - - - - - - - - - - - -

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.

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

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This video on Agentic AI Full Course 2026 by Simplilearn will help you learn Agentic AI from beginner to advanced level and understand how autonomous AI systems can plan, reason, make decisions, and execute complex tasks with minimal human intervention. The course begins with an introduction to Agentic AI and explains how AI agents differ from traditional AI models by combining reasoning, planning, memory, tool usage, and goal-oriented execution. You will learn key concepts such as AI agents, large language models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), tool calling, agent workflows, multi-agent systems, memory management, and orchestration frameworks.

Following are the topics covered in the Agentic AI Full Course 2026

00:00:00 - Introduction To Agentic AI Full Course 2026
00:03:54 - Basics of Agentic AI
00:08:06 - Core Concepts of Agentic AI
00:15:15 - Agentic AI Frameworks & Libraries
00:22:09 - Memory and Long-Term Context
00:30:01 - Planning & Decision Chains
00:36:25 - Advanced Use-Cases of Agentic AI
00:39:48 - Agent Evaluation and Prompt Optimization
00:43:50 - Risks, Ethics, and Future of Agentic AI
00:47:27 - Hands-On Project
04:08:49 - Top Hacks To Speed Up Your AI Coding Workflow
05:51:53 - Generative Adversarial Tutorial
06:52:32 - Emergent AI App Builder Tutorial For Beginners
07:03:58 - Top 5 AI Automation Tools 2026
07:15:15 - How To Build WhatsApp AI Agent Using n8n
08:14:34 - Mobile App Development In 12 Minutes Using AI
09:40:37 - LangSmith Tutorial For Beginners 2026
10:14:58 - LangChain Tutorial For Beginners 2026
11:00:54 - LangGraph vs LangChain vs LangFlow vs LangSmith 2026
11:10:27 - Build LLM Apps Using Langchain
12:37:42 - Build a Chatbot Using Langchain
13:43:40 - What Is Miro And How To Use It?
13:59:30 - MetaGPT Tutorial For Beginners
14:56:55 - Streamlit Tutorial For Beginners
15:23:37 - Prompt Engineering Tutorial For Beginners
15:57:03 - LLM scale and deployment
16:07:26 - Large language models overview
16:14:53 - Features, tokens, and model choice
16:21:24 - AI tools across industries
16:26:32 - Resume and job matching demo
16:37:05 - Prompt engineering fundamentals
16:54:41 - Everyday prompt use cases
17:04:21 - Multimodal AI capabilities
18:19:50 - Key takeaways and next steps
18:26:41 - Effective prompt design principles
19:08:36 - Gen AI For Data Analytics
20:53:11 - Data integrity and EDA setup
21:42:42 - Data modeling with genAI
22:07:34 - Modeling techniques and use cases
23:46:43 - Future trends and wrap-up
24:03:57 - Gen AI Powered SQL For Data Analytics
25:09:42 - ER model fundamentals
26:26:15 - Database commands and basic setup
27:04:37 - Table creation and constraints
28:33:57 - Query logic and aggregation
29:00:27 - SQL functions introduction
30:19:37 - Using ChatGPT for SQL practice
30:22:09 - Agentic AI Projects For Beginners 2026
30:46:15 - What Is GenAI?
30:50:35 - How To Become Generative AI Engineer?
31:00:40 - Generative AI Vs Agentic AI Vs AI Agents
32:37:26 - LLM As Operating System
33:30:16 - LLM Benchmarking
34:46:06 - Prompt engineering with GPT-4
35:41:26 - Vibe coding tools comparison
36:06:01 - Generative AI learning roadmap
36:58:56 - AI for research and content
37:22:52 - Data insights and AI workflows
38:12:03 - Gemini CLI versus Claude Code
38:37:03 - ChatGPT attempts LeetCode problems
40:56:55 - Prompt library foundations
41:11:56 - Reasoning with o1 models
42:57:42 - Prompt library recap
43:56:35 - How To Build AI Automations Using n8n
44:26:47 - How To Build a Self Learning AI Agent
46:20:12 - Top 30 Generative AI Interview Questions 2026

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Want to dive deeper? This curriculum is covered in the following online courses:
- Agentic AI professional education course: https://stanford.io/4zOyjPN
- XCS329 graduate course: https://online.stanford.edu/co....urses/cs329a-self-im

A similar curriculum is covered in XCS329z https://online.stanford.edu/co....urses/cs329z-enginee

Follow along with the course schedule and syllabus: https://cs329a.stanford.edu/

View the course playlist: https://www.youtube.com/playli....st?list=PLangBM27OtE

Video Summary:
This first lecture videoof Stanford's CS329A, Self-Improving AI Agents, taught by Aakanksha Chowdhery and Azalia Mirhoseini on September 22, 2025, opens with an overview of scaling laws that link model parameters, training compute, and dataset size to lower test loss in large language models from GPT-2 through GPT-4. It covers few-shot and zero-shot learning, the emergence of chain-of-thought reasoning in larger models, and the role of instruction tuning and reinforcement learning from human feedback in the development of ChatGPT. The lecture introduces inference-time scaling through the Large Language Monkeys project, which repeatedly samples a model's outputs and selects correct answers with a verifier to improve performance without retraining. It then traces the shift from single-turn chatbots to agent workflows such as prompt chaining, routing, parallelization, and orchestrator-worker patterns, using Claude Code and deep research tools as examples. The session closes with logistics for the course.

Speaker Bios:
Aakanksha Chowdhery
Adjunct Professor of Computer Science, Stanford University

Dr. Aakanksha Chowdhery is pushing the frontier of agentic LLMs, focusing on recursive self-improvement and long-horizon agents that learn and deploy in the real world. She is one of the few researchers globally who has led frontier model training end-to-end, across both dense and mixture-of-experts (MoE) architectures. At Google, she led the 540B PaLM model, the largest densely trained language model in the world at the time. She subsequently drove pre-training and scaling of Gemini's MoE models across multiple generations, and contributed key components to PaLM-E, Med-PaLM, and the Pathways infrastructure underpinning Google's large-model efforts. She went on to build and lead pretraining teams for open intelligence efforts at Reflection and Meta. Earlier, she held research roles at Microsoft Research and Princeton. At Stanford, where she earned her PhD, she teaches CS329A (Self-Improving AI Agents) and serves as Program Chair for MLSys 2026.

Azalia Mirhoseini
Assistant Professor of Computer Science, Stanford University

Azalia Mirhoseini is a co-founder of Ricursive Intelligence, a frontier lab dedicated to recursive self-improvement through AI that designs the chips that fuel it. She is also an Assistant Professor of Computer Science at Stanford University where she directs Scaling Intelligence, a lab focused on developing scalable and self-improving AI systems and methodologies toward the goal of artificial general intelligence. Previously, she spent several years in industry AI labs, including Google Brain, Anthropic, and Google DeepMind, working on the development of Claude and Gemini. Her past work includes Mixture-of-Experts (MoE) neural architectures, now predominantly used in leading generative AI models; AlphaChip, a pioneering work on deep reinforcement learning for layout optimization used in the design of advanced chips like Google AI accelerators (TPUs) and data center CPUs; as well as pioneering research on LLM Test-Time Scaling. Her work has been recognized through the Okawa Research Grant, the Google ML and Systems Junior Faculty Award, MIT Technology Review's 35 Under 35 Award, the Best ECE Thesis Award at Rice University, publications in flagship venues such as Nature, and coverage by various media outlets, including WSJ, NYT, Forbes, MIT Technology Review, IEEE Spectrum, WIRED, and TechCrunch.

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