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00:00:00 Introduction to Gen AI Full Course
00:08:08 What is Artificial Intelligence
00:08:53 What is Generative AI
00:19:32 Roadmap to become a Gen AI Engineer
00:33:07 Gen ai tools for job interview
00:48:31 Open ai chatgpt o1 model
00:50:21 AI Careers to explore
01:04:02 Deep Learning Tutorial
01:12:19 Search GPT Tutorial
01:14:34 Langchain Tutorial
01:37:28 Openai sora Tutorial
02:22:05 Generative Adversarial Tutorial
02:31:27 What are GANS
02:32:28 Transformers in AI
02:44:57 LSTM Tutorial
02:46:21 Large Language Models Tutorial
03:47:34 What is Machine Learning
04:44:06 Machine Learning Tutorial
06:49:29 Reinforcement Learning Tutorial
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10:40:56 LLM Benchmarking Tutorial
10:46:38 Open AI Strawberry Tutorial

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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
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Skills Covered:
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✅ Prompt Engineering
✅ Chatbot Development
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✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
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✅ Program Induction
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✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning with TensorFlow (IBM)
✅ Deep Learning Specialization
✅ Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ Advanced Generative AI
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• AI Fundamentals - LLMs, tokens, embeddings, and context windows
• LangChain - Simplify AI development with pre-built components
• Prompt Engineering - Zero-shot, few-shot, and chain-of-thought techniques
• Vector Databases - Semantic search with ChromaDB and Pinecone
• RAG (Retrieval Augmented Generation) - Build intelligent document search
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• MCP (Model Context Protocol) - Connect AI to external tools

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10:12 - Practice Labs - Your First AI API Call
14:57 - Practice Labs - LangChain
17:57 - Prompt Engineering Techniques
21:21 - Practice Labs - Master Prompt Engineering
24:46 - Vector Databases Deep Dive
31:27 - Practice Labs - Build Semantic Search Engine
35:15 - RAG (Retrieval Augmented Generation)
38:14 - Practice Labs - RAG Implementation
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MIT 18.642 Topics in Mathematics with Applications in Finance, Fall 2024
Instructors: Vasily Strela, Jake Xia, and Peter Kempthorne
View the complete course: https://ocw.mit.edu/courses/18....-642-topics-in-mathe
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This video provides an introductory overview of a course combining mathematical theory and real-world financial applications, featuring lectures by academics and industry experts. The instructors emphasize the practical use of mathematics in finance, covering topics like bond math, portfolio optimization, and machine learning, while utilizing tools such as RStudio Cloud for data analysis. Additionally, the course includes guest speakers from prominent financial institutions, offering students exposure to cutting-edge quantitative finance concepts and industry practices.

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Support OCW at http://ow.ly/a1If50zVRlQ

We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.

MIT 3.020 Thermodynamics of Materials, Spring 2021
Instructor: Rafael Jaramillo

View the complete course: https://ocw.mit.edu/courses/3-....020-thermodynamics-o
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This first class session introduces entropy and spontaneous processes, molecular interactions, and enthalpy, as well as the scope and use of thermodynamics.

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu
Support OCW at http://ow.ly/a1If50zVRlQ

We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments.

We're going to build a variational autoencoder capable of generating novel images after being trained on a collection of images. We'll be using handwritten digit images as training data. Then we'll both generate new digits and plot out the learned embeddings. And I introduce Bayesian theory for the first time in this series :)

Code for this video:
https://github.com/llSourcell/....how_to_generate_imag

Mike's Winning Code:
https://github.com/xkortex/how...._to_win_slot_machine

SG's Runner up Code:
https://github.com/esha-sg/Int....ro-DeepLearning-Sira

Please subscribe! And like. And comment. That's what keeps me going.

2 things
-The embedding visualization at the end would be more spread out if i trained it for more epochs (50 is recommended) but i just used 5.
-The code in the video doesn't fully implement the reparameterization trick (to save space) but check the GitHub repo for details on that.

More Learning resources:
https://jaan.io/what-is-variat....ional-autoencoder-va
http://kvfrans.com/variational....-autoencoders-explai
http://blog.fastforwardlabs.co....m/2016/08/12/introdu
http://blog.fastforwardlabs.co....m/2016/08/22/under-t
http://blog.evjang.com/2016/11..../tutorial-categorica
https://jmetzen.github.io/2015-11-27/vae.html

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🔥 Prompt Engineering with LLM Course: https://www.edureka.co/prompt-....engineering-generati
🔥Post Graduate Program in Generative AI and ML: https://www.edureka.co/executi....ve-programs/pgp-gene
🔥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

Dive into the world of artificial intelligence with this comprehensive LLM Prompt Engineering Full Course by edureka! in collaboration with Veranda Enterprise. In this course, you'll learn how to effectively communicate with large language models like ChatGPT by mastering the art of prompt engineering. From the fundamentals of zero-shot and few-shot prompting to advanced techniques like chain-of-thought and structured prompting, this course is designed to equip you with the practical skills needed to build powerful AI-driven applications. Whether you're a developer, data scientist, or complete beginner, this full course provides real-world examples, hands-on demos, and expert tips to help you unlock the full potential of generative AI. Start your journey into prompt engineering and take your AI skills to the next level.

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

Paper: https://arxiv.org/abs/1312.6114

The video focuses how to get started but particularly on the prompt engineering part to give you ideas and inspiration to what you can explore. Since Stable Diffusion was released couple of days ago this has been incorporated into MidJourney too which you can access by "—beta" argument which supposedly helps with face quality.

Resources mentioned:
https://github.com/willwulfken..../MidJourney-Styles-a

https://pitch.com/v/DALL-E-prompt-book-v1-tmd33y

https://docs.google.com/docume....nt/d/11WlzjBT0xRpQhP

Timestamps:
0:00 - Introduction to MJ and what you can do
8:17 - Resources for prompt inspiration
12:30 - How to iterate on the prompt/caption (prompt engineering)
29:40 - Other arguments you can use
32:26 - Final images result
33:25 - Ending

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This Edureka Data Science Full Course video will help you understand and learn Data Science Algorithms in detail. This Data Science Tutorial is ideal for both beginners as well as professionals who want to master Data Science Algorithms.
Below are the topics covered in this Data Science Full course tutorial:
00:00:00 Introduction
00:00:45 Agenda
00:02:59 What is Data Science
00:04:31 Data Science Basics
00:07:13 Walmart use cases
00:12:05 Who is a Data Scientist
00:13:47 Role of a Data Scientist
00:15:39 Technologies to learn for a Data scientist
00:44:16 Data Scientist Roadmap
01:00:55 Data Science Salary
01:09:44 Statistics and Probability
01:40:48 Use Case
01:50:43 Confusion matrix
02:00:15 Probability
02:15:56 Bayes Theorem
02:22:22 Inferntial Statistics
02:31:37 Use Case
02:42:20 What is Machine Learning
02:59:23 What is Regression in Machine Learning
03:08:05 Use Case
03:25:53 Logistic Regression
03:32:46 Use case
04:14:25 Decision Tree Algorithm
04:15:01 What is Classification
04:19:12 Types of Classification
04:28:28 What is Decision Tree
04:35:35 Decesion Tree Terminologies
04:59:50 Random Forest
05:03:11 Working of Random Forest
05:04:08 RandomSampling with Replacement
05:12:15 Advantages of Random Forest
05:15:37 Hands-on Random forest
05:27:01 KNN Algorithm
05:29:02 Features of KNN
05:37:17 How Does KNN Algorithm Works
05:42:50 Hands-on KNN Algorithm
05:59:30 Naive Bayes Classifier
06:19:50 Support Vector Machine
06:45:16 K-means clustering Algorithm
07:05:27 Apriori Algorithm
07:21:14 Hands-on
07:35:08 Reinforcement Learning
07:38:25 Reinforcement Learning - Counter strike example
07:56:36 Q Learning
07:57:34 Defining a problem statement
08:01:37 The Bellman Equation
08:19:25 What is Deep Learning
08:23:24 Why do we need Artificial Neuron
08:33:55 WHat is Tensorflow
08:43:50 Tensorflow Code Basics
08:55:45 What is Computational Graph
09:18:18 Limitation of a Single layer perception
09:25:54 Multi-layer Perceptron Use case
09:57:08 Data Scientist Resume
10:02:33 Data Science Interview Question & Answers

🔴 Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV

🔴 𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

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⏩ NEW Top 10 Technologies To Learn In 2023 - https://youtu.be/udD_GQVDt5g

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The topics covered in this business analyst full course are:
Introduction 00:00:00
Need for a Business Analyst 00:01:18
Who Is a Business Analyst 00:05:33
Business Analyst Responsibilities 00:11:50
Business Analyst Skills 00:14:01
Business Analyst Certification 00:25:06
Business Analyst Roadmap 00:30:29
Business Analysis Knowledge Areas 00:31:37
Agile Methodology 00:33:22
Scrum Methodology 00:35:01
Business Analyst Career 00:37:55
Business Analyst Tools 00:38:40
Business Analysis With Excel 00:39:08
Business Analyst vs Data Analyst 01:19:04

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A business analyst understands the business problems and identifies the solutions that will maximize the organization's value to its stakeholders. A business analyst is an individual who works closely with the technology team to improve the quality of the services being delivered. They ensure the customer needs are correctly interpreted and translated into application. They possess programming, SQL, and business intelligence skills to deliver data-driven solutions.

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