Master Artificial Intelligence with hands-on projects. Build your own ChatBot and Finetune your own ChatGPT!!
What you will 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
Why take this course?
🎉 Master Artificial Intelligence with Practical Projects! 🚀
Course Overview:
Complete GenAI Course | Build 4 Projects | ChatBot & ChatGPT in Python using PyTorch
Welcome to the Complete Artificial Intelligence Bootcamp with ChatBot and ChatGPT in Python using PyTorch! This course is your ultimate guide to mastering AI, deep learning, and the powerful PyTorch library. Whether you’re a complete beginner or an experienced professional aiming to sharpen your skills, this comprehensive bootcamp will elevate your expertise in the field of artificial intelligence.
Why This Course?
🏆 Unique Content: Gain access to exclusive materials and hands-on projects that you won’t find anywhere else online!
📚 Comprehensive Curriculum: From the foundational concepts of PyTorch to advanced topics like transformer architecture for ChatBots, our curriculum is all-encompassing.
🛠️ Hands-on Projects: Reinforce your learning with practical, real-world projects designed to solidify each concept you learn.
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🧑🏫 Expert Instruction: Learn from Gaurav K. Verma, an instructor with extensive experience in AI and deep learning, who will guide you through every step of the way.
🦙 Interactive Quizzes: Test your knowledge with quizzes that challenge you to think deeply about each section and ensure you’re ready to move on to the next.
Course Breakdown:
Section 1: Introduction
- Overview of course structure and objectives.
Section 2: Introduction to PyTorch
- Computational graphs, tensors, and tensor operations.
- Tensor datatypes, math operations, and shape manipulation.
- Understanding autograd for in-place operations.
Section 3: Loss Functions in Deep Learning
- Explore various loss functions such as L1, L2, binary cross-entropy, and KL divergence.
Section 4: Different Activation Functions in Deep Learning
- Importance of activation functions like ReLU, Leaky ReLU, and PReLU.
Section 5: Normalization and Regularization
- Regularization techniques and normalization methods for robust models.
Section 6: Optimization in AI
- Master optimization techniques including gradient descent and mini-batch SGD.
Section 7: Building a Neural Network in PyTorch
- Design, train, and test a neural network using the MNIST dataset.
Section 8: Custom PyTorch Dataset and Dataloader
- Create and utilize custom datasets and dataloaders for efficient data processing.
Section 9: Building an Image Classification CNN Model
- Build, train, and visualize a Convolutional Neural Network (CNN) model for handwritten digit classification.
Section 10: Building a ChatBot using Pre-Trained ChatGPT
- Comprehensive guide to fine-tuning pre-trained ChatGPT for question and answer (Q&A) purposes.
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 join the ranks of professionals who are not just keeping pace with the rapid advancements in artificial intelligence but are driving them forward! 🚀💻✨
