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Artificial Intelligence A-Z 2024: Build 7 AI + LLM & ChatGPT

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Kirill Eremenko,Ligency I Team,Ligency Team,Hadelin de Ponteves,Luka Anicin

14:02:00

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  • 1 - Welcome Challenge.html
  • 2 - Why AI.mp4
    05:10
  • 3 - Course Structure.html
  • 4 - EXTRA Use ChatGPT to Build AI More Efficiently.html
  • 5 - Welcome to Part 0 Fundamentals of Reinforcement Learning.html
  • 6 - Plan of Attack.mp4
    04:04
  • 7 - What is reinforcement learning.mp4
    11:26
  • 8 - The Bellman Equation.mp4
    18:25
  • 9 - The Plan.mp4
    02:12
  • 10 - Markov Decision Process.mp4
    16:27
  • 11 - Policy vs Plan.mp4
    12:55
  • 12 - Adding a Living Penalty.mp4
    09:47
  • 13 - QLearning Intuition.mp4
    14:46
  • 14 - Temporal Difference.mp4
    19:27
  • 15 - A QLearning Implementation for Process Optimization.html
  • 15 - A-Q-Learning-Implementation-for-Process-Optimization.zip
  • 16 - Welcome to Part 1 Deep QLearning.html
  • 17 - Plan of Attack.mp4
    02:17
  • 18 - Deep QLearning Intuition Learning.mp4
    15:15
  • 19 - Deep QLearning Intuition Acting.mp4
    06:06
  • 20 - Experience Replay.mp4
    15:45
  • 21 - Action Selection Policies.mp4
    16:23
  • 22 - Get the Codes here.html
  • 22 - Part-1-Deep-Q-Learning.zip
  • 23 - Deep QLearning Implementation Step 1.mp4
    06:59
  • 24 - Deep QLearning Implementation Step 2.mp4
    06:25
  • 25 - Deep QLearning Implementation Step 3.mp4
    08:23
  • 26 - Deep QLearning Implementation Step 4.mp4
    03:58
  • 27 - Deep QLearning Implementation Step 5.mp4
    05:45
  • 28 - Deep QLearning Implementation Step 6.mp4
    03:55
  • 29 - Deep QLearning Implementation Step 7.mp4
    02:44
  • 30 - Deep QLearning Implementation Step 8.mp4
    03:07
  • 31 - Deep QLearning Implementation Step 9.mp4
    08:17
  • 32 - Deep QLearning Implementation Step 10.mp4
    07:39
  • 33 - Deep QLearning Implementation Step 11.mp4
    07:35
  • 34 - Deep QLearning Implementation Step 12.mp4
    08:59
  • 35 - Deep QLearning Implementation Step 13.mp4
    08:55
  • 36 - Deep QLearning Implementation Step 14.mp4
    06:47
  • 37 - Deep QLearning Implementation Step 15.mp4
    02:09
  • 38 - Deep QLearning Implementation Step 16.mp4
    05:38
  • 39 - Deep QLearning Implementation Step 17.mp4
    09:39
  • 40 - Deep QLearning Implementation Step 18.mp4
    20:26
  • 41 - Deep QLearning Implementation Step 19.mp4
    05:19
  • 41 - video.mp4
    00:11
  • 42 - Deep QLearning Implementation Step 20.mp4
    05:44
  • 43 - Welcome to Part 2 Deep Convolutional QLearning.html
  • 44 - Plan of Attack.mp4
    03:27
  • 45 - Deep Convolutional QLearning Intuition.mp4
    07:12
  • 46 - Eligibility Trace.mp4
    08:38
  • 47 - Get the Codes here.html
  • 47 - Part-2-Deep-Convolutional-Q-Learning.zip
  • 48 - Deep Convolutional QLearning Implementation Step 1.mp4
    05:17
  • 49 - Deep Convolutional QLearning Implementation Step 2.mp4
    05:30
  • 50 - Deep Convolutional QLearning Implementation Step 3.mp4
    11:06
  • 51 - Deep Convolutional QLearning Implementation Step 4.mp4
    04:33
  • 52 - Deep Convolutional QLearning Implementation Step 5.mp4
    07:14
  • 53 - Deep Convolutional QLearning Implementation Step 6.mp4
    04:05
  • 54 - Deep Convolutional QLearning Implementation Step 7.mp4
    02:03
  • 55 - Deep Convolutional QLearning Implementation Step 8.mp4
    08:20
  • 56 - Deep Convolutional QLearning Implementation Step 9.mp4
    09:48
  • 57 - Deep Convolutional QLearning Implementation Step 10.mp4
    07:37
  • 58 - Deep Convolutional QLearning Implementation Step 11.mp4
    14:13
  • 59 - Deep Convolutional QLearning Implementation Step 12.mp4
    03:54
  • 59 - video.mp4
    00:27
  • 60 - Deep Convolutional QLearning Implementation Step 13.mp4
    05:24
  • 61 - Welcome to Part 3 A3C.html
  • 62 - Plan of Attack.mp4
    03:39
  • 63 - The three As in A3C.mp4
    04:44
  • 64 - ActorCritic.mp4
    06:36
  • 65 - Asynchronous.mp4
    11:43
  • 66 - Advantage.mp4
    15:21
  • 67 - LSTM Layer.mp4
    15:36
  • 68 - Get the Codes here.html
  • 68 - Part-3-A3C.zip
  • 69 - A3C Implementation Step 1.mp4
    06:06
  • 70 - A3C Implementation Step 2.mp4
    05:53
  • 71 - A3C Implementation Step 3.mp4
    11:46
  • 72 - A3C Implementation Step 4.mp4
    08:26
  • 73 - A3C Implementation Step 5.mp4
    05:48
  • 74 - A3C Implementation Step 6.mp4
    07:14
  • 75 - A3C Implementation Step 7.mp4
    11:51
  • 76 - A3C Implementation Step 8.mp4
    18:28
  • 77 - A3C Implementation Step 9.mp4
    02:06
  • 78 - A3C Implementation Step 10.mp4
    09:59
  • 79 - A3C Implementation Step 11.mp4
    07:22
  • 80 - A3C Implementation Step 12.mp4
    09:59
  • 81 - A3C Implementation Step 13.mp4
    03:46
  • 82 - A3C Implementation Step 14.mp4
    20:21
  • 82 - video.mp4
    00:39
  • 83 - A3C Implementation Step 15.mp4
    13:16
  • 84 - THANK YOU Video.mp4
    02:40
  • 85 - What is Deep Learning.mp4
    12:34
  • 86 - Plan of Attack.mp4
    02:52
  • 87 - The Neuron.mp4
    16:15
  • 88 - The Activation Function.mp4
    08:29
  • 89 - How do Neural Networks work.mp4
    12:47
  • 90 - How do Neural Networks learn.mp4
    12:59
  • 91 - Gradient Descent.mp4
    10:13
  • 92 - Stochastic Gradient Descent.mp4
    08:44
  • 93 - Backpropagation.mp4
    05:22
  • 94 - Plan of Attack.mp4
    03:31
  • 95 - What are convolutional neural networks.mp4
    15:49
  • 96 - Step 1 Convolution Operation.mp4
    16:38
  • 97 - Step 1b ReLU Layer.mp4
    06:41
  • 98 - Step 2 Pooling.mp4
    14:13
  • 99 - Step 3 Flattening.mp4
    01:52
  • 100 - Step 4 Full Connection.mp4
    19:25
  • 101 - Summary.mp4
    04:19
  • 102 - Softmax CrossEntropy.mp4
    18:20
  • 103 - Extra Section Intro.html
  • 103 - q-learning-rl-2.zip
  • 104 - Extra Section Q Learning.mp4
    01:15
  • 105 - Extra Section Q Learning Part II.mp4
    04:07
  • 106 - Extra Section Q Learning Part III.mp4
    07:04
  • 107 - AI-Bonus-Section-4.mp4
    04:40
  • 107 - Extra Section Q Learning Part IV.mp4
    04:40
  • 108 - Extra Section Q Learning Part V.html
  • 109 - Extra Section Q Learning Section VI.mp4
    08:05
  • 110 - Huge Congrats for completing the challenge.html
  • 111 - BONUS Cloud Skills for ML AI COUPON inside.html
  • Cryptocurrency.pdf
  • MyBlogs.pdf
  • Description


    Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!

    What You'll Learn?


    • Build 7 different AIs for 7 different applications
    • Understand the theory behind Artificial Intelligence
    • Master the State of the Art AI models
    • Solve Real World Problems with AI
    • Q-Learning
    • Deep Q-Learning
    • Deep Convolutional Q-Learning
    • A3C (Asynchronous Advantage Actor-Critic)
    • PPO (Proximal Policy Optimization)
    • SAC (Soft Actor-Critic)
    • LLMs
    • Transformers
    • Low-Rank Adaptation (LoRA) and Quantization (QLoRA)
    • NLP techniques for Chatbots: Tokenization and Padding
    • Fine-Tuning an LLM with Knowledge Augmentation
    • As Extras: DDPG, Full World Model, Evolution Strategies & Genetic Algorithms

    Who is this for?


  • Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning
  • What You Need to Know?


  • High School Maths
  • Basic Python knowledge
  • More details


    Description

    Welcome to Artificial Intelligence A-Z!


    Learn key AI concepts with intuition lectures to get you quickly up to speed with all things AI and practice them by building 7 different AIs:


    1. Build an AI with a Q-Learning model and train it to optimize warehouse flows in a Process Optimization case study.

    2. Build an AI with a Deep Q-Learning model and train it to land on the moon.

    3. Build an AI with a Deep Convolutional Q-Learning model and train it to play the game of Pac-Man.

    4. Build an AI with an A3C (Asynchronous Advantage Actor-Critic) model and train it to fight Kung Fu.

    5. Build an AI with a PPO (Proximal Policy Optimization) model and train it for a Self-Driving Car.

    6. Build an AI with a SAC (Soft Actor-Critic) model and train it for a Self-Driving Car.

    7. Build an AI by fine-tuning a powerful pre-trained LLM (Llama 2 by Meta) with Hugging Face and re-train it to chat with you about medical terms. Simply put, we build here an AI Doctor Chatbot.


    But that's not all... Once you complete the course, you will get 3 extra AIs: DDPG, Full World Model, and Evolution Strategies & Genetic Algorithms. We build these AIs with ChatGPT for a Self-Driving Car and a Humanoid application. For each of these extra AIs you will get a long video lecture explaining the implementation, a mini PDF, and the Python code.


    Besides, you will get a free 3-hour extra course on Generative AI and LLMs with Cloud Computing as a Prize for completing the course.


    And last but not least, here is what you will get with this course:


    1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.

    2. Hassle-Free Coding and Code templates – We will build all our AIs in Google Colab, which means that we will have absolutely NO hassle installing libraries or packages because everything is already pre-installed in Google Colab notebooks. Plus, you’ll get downloadable Python code templates (in .py and .ipynb) for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.

    3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in AI for much better results down the line.

    4. Real-world solutions – You’ll achieve your goal in not only one AI model but in 5. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.

    5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.


    So, are you ready to embrace the fascinating world of AI?

    Come join us, never stop learning, and enjoy AI!

    Who this course is for:

    • Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning

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    Kirill Eremenko
    Kirill Eremenko
    Instructor's Courses
    My name is Kirill Eremenko and I am super-psyched that you are reading this!Professionally, I come from the Data Science consulting space with experience in finance, retail, transport and other industries. I was trained by the best analytics mentors at Deloitte Australia and since starting on Udemy I have passed on my knowledge to thousands of aspiring data scientists.From my courses you will straight away notice how I combine my real-life experience and academic background in Physics and Mathematics to deliver professional step-by-step coaching in the space of Data Science. One of the strongest sides of my teaching style is that I focus on intuitive explanations, so you can be sure that you will truly understand even the most complex topics.To sum up, I am absolutely and utterly passionate about Data Science and I am looking forward to sharing my passion and knowledge with you!
    Ligency I Team
    Ligency I Team
    Instructor's Courses
    Hi there,We are the Ligency team. You will be hearing from us when new Ligency courses are released, when we publish new podcasts, blogs, share cheatsheets and more!We are here to help you stay on the cutting edge of Data Science and Technology. See you in class,Sincerely,Ligency Team!
    Ligency Team
    Ligency Team
    Instructor's Courses
    Hi there,We are the Ligency PR and Marketing team. You will be hearing from us when new courses are released, when we publish new podcasts, blogs, share cheatsheets and more!We are here to help you stay on the cutting edge of Data Science and Technology.See you in class,Sincerely,The Real People at Ligency
    Hadelin de Ponteves
    Hadelin de Ponteves
    Instructor's Courses
    Hadelin is an online entrepreneur who has created 30+ top-rated educational e-courses to the world on new technology topics such as Artificial Intelligence, Machine Learning, Deep Learning, Blockchain and Cryptocurrencies. He is passionate about bringing this knowledge to the world and help as much people as possible. So far more than 1.6 million students have subscribed to his courses.
    Meet Luka Anicin, an internationally recognized expert in AI and Machine Learning. He kickstarted his career as a Computer Vision Researcher and quickly became a leading Machine Learning Engineer at BlueLife AI. His entrepreneurial spirit led him to launch Scooby AI in 2020, and later sell it. Luka had an amazing opportunity to work in Photomath creating OCR algorithm for scanning mathematical tasks, that currently benefits over 280 million students worldwide.Luka founded Datablooz, a global technical project consultancy, helping businesses harness the power of AI. As a passionate educator, he's guided over 300,000 students across 197 countries in understanding complex technical topics. Recognized by Google among the top 150 machine learning experts, Luka is a powerhouse of AI, focused on leveraging technology to transform businesses. Let him be a part of your journey into the realm of AI and Machine Learning.
    Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.
    • language english
    • Training sessions 100
    • duration 14:02:00
    • English subtitles has
    • Release Date 2024/03/16