What will you in PyTorch: Deep Learning and Artificial Intelligence Course
Understand the foundations of deep learning and neural networks.
Master PyTorch for building, training, and evaluating deep learning models.
Work with real-world datasets for image and tabular data classification.
Implement advanced topics such as transfer learning and custom CNNs.
Build and train neural networks using hands-on coding exercises.
Program Overview
Module 1: Introduction to Deep Learning & PyTorch
⏳ 30 minutes
Overview of AI, deep learning, and the PyTorch framework.
Installing PyTorch and setting up the environment.
Module 2: PyTorch Fundamentals
⏳ 45 minutes
Tensors, automatic differentiation, and key PyTorch operations.
Building a simple neural network from scratch.
Module 3: Neural Network Training Workflow
⏳ 60 minutes
Data loaders, loss functions, and optimization steps.
Training loops, validation, and evaluation metrics.
Module 4: Image Classification Projects
⏳ 60 minutes
Building a CNN for classifying image datasets.
Model improvement techniques: data augmentation, dropout, and batch normalization.
Module 5: Tabular Data Modeling
⏳ 60 minutes
Working with structured data using PyTorch.
Preprocessing and building dense neural networks for regression and classification.
Module 6: Transfer Learning with Pre-trained Models
⏳ 60 minutes
Using models like ResNet and VGG for new tasks.
Fine-tuning and feature extraction in PyTorch.
Module 7: Saving, Loading & Deployment
⏳ 45 minutes
Saving models with TorchScript and loading them for inference.
Deploying trained models using simple APIs.
Module 8: Final Project: Build an End-to-End Deep Learning App
⏳ 75 minutes
Combining all concepts in a complete app.
Training, evaluating, and deploying your own DL solution.
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Job Outlook
High Demand: Deep learning engineers are sought after in AI, healthcare, finance, and autonomous tech.
Career Advancement: Great for data scientists, ML engineers, and AI researchers.
Salary Potential: $100K–$170K+ depending on experience and specialization.
Freelance Opportunities: Projects in computer vision, NLP, and AI-based app development.
Explore More Learning Paths
Advance your deep learning and AI skills with these expertly curated programs designed to deepen your understanding of neural networks, PyTorch, and practical AI applications.
Related Courses
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IBM Deep Learning with PyTorch, Keras, and TensorFlow Professional Certificate Course – Master deep learning frameworks, implement advanced models, and gain hands-on experience with real-world AI projects.
PyTorch for Deep Learning Bootcamp Course – Learn to develop, train, and deploy PyTorch models through practical exercises and project-based learning.
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Specification: PyTorch: Deep Learning and Artificial Intelligence Course
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