AI Engineering Full Course (PyTorch) 2026 UPDATED | Beginner to Advanced | One Shot | Sagar Chouksey
Masters In Data-Analytics with GenAI (Super 30 Batch) - https://codingwise.in/program/data-an... Python for Data Science - https://programs.codingwise.in/python... Resources - https://programs.codingwise.in/data-s... Other Data-Science Lectures: Machine Learning Course - • Machine Learning Full Course with Scikit‑L... Complete Python (Beginner to Advanced) : • Python Full Course For Beginners| Job Read... Matplotlib for Data Visualisation - • Matplotlib Full Course in 1 Shot | Data Vi... Database Using SQL for Data Science - • SQL Full Course | Beginners to Advanced | ... Pandas Library for Data Science : • Pandas for Data Analysis In Python | Sagar... Numpy Library for Data Science : • Numpy for Data Science | Full Course | Sag... Flask Framework for Data Science - • Flask Tutorial for Web Development and Dat... Python Project for Beginners - • Build 3 Python Projects Step-by-Step 🔥 | P... PowerBI Tutorial - • Power BI Tutorial for Beginners | Job Read... Advanced Excel - • Excel for Data Analysis Full Course 2025 |... OpenCV Computer Vision - • OpenCV Tutorial | Computer Vision | Full O... Learn AI Engineering from scratch using PyTorch in one complete video. Beginner to advanced concepts, real AI projects, and clear explanations - perfect for anyone who wants to become an AI Engineer. If you’re searching for AI Engineering full course, PyTorch tutorial, machine learning with PyTorch, deep learning for beginners, or AI projects, this video covers everything from beginner to advanced level in one complete roadmap. Timestamps: 0:00 – 3:03 → Course Introduction & What You’ll Learn 3:03 – 48:01 → AI Foundations & Prerequisites (What is AI, ML vs DL, Flow, Big Picture, PyTorch Overview, Key Terms) 48:01 – 1:27:53 → PyTorch Tensors & Setup (Installation, Tensor Basics, Shapes, Indexing, NumPy ↔ PyTorch, GPU Usage) 1:27:53 – 2:28:06 → Autograd & Training Models (Automatic Differentiation, Loss Functions, Optimizers, Training Loop) 2:28:06 – 3:54:30 → Neural Networks with nn.Module & DataLoaders (Layers, Activations, MNIST Classifier) 3:54:30 – 4:49:10 → CNNs & Computer Vision (Conv Layers, Transfer Learning, Image Classification Projects) Tools Used: Python, PyTorch, NumPy, Matplotlib, CUDA (GPU Acceleration) Skills You’ll Gain: Building AI models from scratch using PyTorch Understanding AI, Machine Learning, and Deep Learning clearly Training neural networks with real-world workflows Implementing CNNs for computer vision tasks Confidence to build job-ready AI projects without math fear Connect with us: LinkedIn - / sagarchouksey4840 Instagram - / codingwithsagar Telegram - https://telegram.me/sagar4840 Youtube - / @codingwithsagarcw Website - https://codingwise.in/ #AIEngineering #PyTorch #MachineLearning #DeepLearning #ArtificialIntelligence
