Master PyTorch, Transformers, Deep Learning:Zero to Gen AI

Master PyTorch, Transformers, Deep Learning:Zero to Gen AI
Published 4/2025
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 19h 5m | Size: 8.21 GB

From Python basics to transformers with PyTorch! Master deep learning, CNNs, and attention. Build Generative AI Project

What you’ll learn
Learn Python and Pytorch programming from scratch with practical examples and real-world use cases.
Master NumPy, Pandas, and Matplotlib for data analysis and visualization.
Build machine learning models like linear and logistic regression using Python and PyTorch.
Understand deep learning fundamentals and create neural networks from scratch.
Learn the transformer architecture and build it step-by-step using PyTorch.
Create a real-world RAG agent project using DeepSeek and PyTorch.

Requirements
No Prerequisite

Description
.Master Python, PyTorch & Transformers: From Basics to Advanced AI ProjectsCourse Highlights:Master Python & Core LibrariesLearn Python basics (syntax, data structures, OOP).Manipulate data with Pandas, crunch numbers with NumPy, and visualize insights with Matplotlib.Build Machine Learning FoundationsCode ANNs, linear/logistic regression from scratch in Python (no frameworks!).Reimplement models using PyTorch to leverage tensor operations and autograd.Dive into Transformers & Modern AIDecode the Transformer paper (attention mechanisms, positional encoding, self-attention).Build a Transformer from scratch in PyTorch-layer by layer!Industry-Ready Projects Project 1: Build a Transformer Model End-to-EndTrain it on real data for tasks like text generation or translation.Project 2: RAG (Retrieval-Augmented Generation) Agent with DeepSeekIntegrate retrieval models + transformers to create an AI agent that answers questions using external knowledge.Handle data pipelines, fine-tuning, and deployment.Why This Course Stands Out?Zero to Advanced: Start with Python basics, end with cutting-edge AI.Code Without Frameworks First: Deepen understanding before using PyTorch shortcuts.Paper-to-Practice: Implement the Transformer architecture exactly as described in the seminal paper.Portfolio Boost: Showcase your RAG agent and Transformer projects to employers. Perfect For:Aspiring AI/ML engineers, data scientists, or developers.Learners who want hands-on projects (not just theory!).Anyone aiming to crack NLP roles or build LLM-powered apps.You’ll Leave With:Fluency in Python, PyTorch, and transformer theory.A deployed RAG agent project + full Transformer implementation.Confidence to tackle real-world AI challenges. Enroll Now – Transform Code into Intelligent Systems!

Who this course is for
Generative AI and Deep Learning Developer