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.
Get certificate
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
-
Introduction to Neural Networks and PyTorch Course – Build a solid foundation in neural networks and PyTorch fundamentals, ideal for beginners entering AI development.
-
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.
Related Reading
-
What Does a Data Engineer Do? – Understand how data engineering supports AI workflows, model training, and scalable deployment.
Last verified: March 12, 2026
