What you'll learn:
Understand How Neural Networks Work (Theory and Applications)
Understand How Convolutional Networks Work (Theory and Applications)
Understand how the Backpropagation algorithm works
Understand Weight Initialization and Regularization Techniques
Understand Loss Functions in Neural Networks
Visualize the Learning Process of Neural Networks
Build handwritten digit recognition AI with feedforward network
Build handwritten digit image classification using CNN AI
Build a Chatbot with Attention
Build a Chatbot using Transformers Architecture
Use OpenAI's open source GPT2
Finetune your own GPT2 for Q&A just like ChatGPT
Requirements:
Basic understanding of Python Programming
Description:
Welcome to the Complete Artificial Intelligence Bootcamp with ChatBot and ChatGPT in Python using PyTorch! This course is your one-stop-shop for mastering artificial intelligence, deep learning, and PyTorch. Whether you're a beginner or an experienced professional, this comprehensive bootcamp is designed to elevate your skills and give you a competitive edge in the AI field.What makes this course unique?Exclusive Content: Dive into materials and hands-on projects that are not available anywhere else online.Comprehensive Curriculum: Covering everything from the basics of PyTorch to advanced topics like transformer architecture and ChatBot creation.Hands-on Projects: Apply your learning with practical, real-world projects designed to reinforce each concept.Expert Instruction: Learn from an instructor with extensive experience in AI and deep learning.Interactive Quizzes: Test your knowledge with quizzes that challenge your understanding of each section.Course Overview:Section 1: IntroductionGet an overview of the course structure and objectives.Section 2: Introduction to PyTorchLearn about computational graphs, tensors, and tensor operations.Dive into tensor datatypes, math operations, and shape manipulation.Understand autograd and perform in-place operations.Section 3: Loss Functions in Deep LearningExplore various loss functions such as L1, L2, binary cross-entropy, and KL divergence.Section 4: Different Activation Functions in Deep LearningUnderstand the importance of activation functions like ReLU, Leaky ReLU, and PReLU.Section 5: Normalization and RegularizationLearn about regularization techniques and normalization methods.Section 6: Optimization in AIMaster optimization techniques including gradient descent and mini-batch SGD.Section 7: Building a Neural Network in PyTorchStep-by-step guide to designing, training, and testing a neural network using the MNIST dataset.Section 8: Custom PyTorch Dataset and DataloaderCreate and utilize custom datasets and dataloaders for efficient data processing.Section 9: Building an Image Classification CNN ModelBuild, train, and visualize a CNN model for handwritten digit classification.Section 10: Building a ChatBot using Transformer ArchitectureComprehensive guide to understanding and implementing transformer architecture for ChatBot development.Section 11: Building a ChatBot using Pre-Trained ChatGPTComprehensive guide to understanding and fine tuning pre-trained ChatGPT for question and answer (Q&A) purpose.Why Enroll?By the end of this course, you will:Have a deep understanding of AI and deep learning fundamentals.Be proficient in using PyTorch for various machine learning tasks.Be able to build and deploy neural networks and transformer models.Have the skills to create a functional ChatBot.This course is perfect for:Aspiring data scientists and machine learning engineers.Software developers looking to transition into AI roles.Professionals seeking to enhance their AI skillset.Enthusiasts eager to learn about cutting-edge AI technologies.Enroll now and gain an unfair advantage in the AI industry with exclusive content and practical experience that sets you apart from the rest!
Who this course is for:
Beginner Python programmer who wants learn everything about AI and GenAI
Anyone who in interested in learning about Neural Networks and Deep Learning
Anyone who wants to start their AI and GenAI journey

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