Deep Learning Courses and Certifications

Whizlabs

Fundamentals of Deep Learning

Master neural networks, CNNs, and transfer learning through hands-on training and evaluation of deep learning models for real-world image classification problems.

• Coursera
• 5 hours 30 minutes
• Self-Paced
• Paid Course

Packt

Deep Learning, NLP, and AI Applications

Explore neural networks, CNNs, RNNs, and transformers to build AI applications for image classification, NLP tasks, and real-world projects using TensorFlow and PyTorch.

• Coursera
• 18 hours 11 minutes
• Self-Paced
• Paid Course

Packt

Deep Learning & Modern AI Architectures

Master cutting-edge neural networks, CNNs, RNNs, and Transformers with hands-on projects in TensorFlow, Keras, and PyTorch for real-world AI applications.

• Coursera
• 15 hours 19 minutes
• Self-Paced
• Paid Course

Packt

Deep Learning and Advanced Techniques

Master advanced deep learning with ensemble methods, neural networks, and frameworks like TensorFlow, PyTorch, XGBoost for real-world AI applications and model deployment.

• Coursera
• 9 hours 23 minutes
• Self-Paced
• Paid Course

EDUCBA

Deep Learning with R: Build & Predict Neural Networks

Master neural network development in R through hands-on data preparation, visualization, regression modeling, and deep learning implementation with practical predictive applications.

• Coursera
• 9 hours 48 minutes
• Self-Paced
• Paid Course

EDUCBA

Deep Learning: Build & Optimize Neural Networks

Master neural networks from foundations to advanced applications including computer vision, NLP with transformers, and recommender systems using PyTorch and real-world projects.

• Coursera
• 17 hours 3 minutes
• Self-Paced
• Paid Course

LearnKartS

Become AI-Ready: Deep Learning Fundamentals

Discover how deep learning powers modern AI systems like ChatGPT through hands-on neural network training, backpropagation, and sequence modeling with RNNs and LSTMs.

• Coursera
• 8 hours 22 minutes
• Self-Paced
• Paid Course

Coursera

Optimize Deep Learning Models for Peak AI

Master transfer learning, model fine-tuning, and optimization techniques to deploy efficient deep learning models in production environments with balanced accuracy and performance.

• Coursera
• 1 hour 58 minutes
• Self-Paced
• Paid Course

Board Infinity

Deep Learning: Train Neural Networks and Deploy with Docker

Master the full deep learning pipeline—design and train neural networks with PyTorch and TensorFlow, track experiments, serve models via FastAPI, and deploy scalable apps using Docker.

• Coursera
• 15 hours
• Self-Paced
• Paid Course

EDUCBA

Analyze and Apply Deep Learning for Computer Vision

Master deep learning architectures and computer vision techniques to solve real-world visual intelligence problems through hands-on implementation and modern AI workflows.

• Coursera
• 5 hours 15 minutes
• Self-Paced
• Paid Course

Packt

Modern Deep Learning Foundations

Unlock the foundations of deep learning, covering neural networks, CNNs, RNNs, Transformers, and deployment with TensorFlow and PyTorch to build and optimize real-world AI models.

• Coursera
• 4 hours
• Self-Paced
• Paid Course

Coursera

Optimize Deep Learning: Stabilize and Diagnose Models

Master deep learning optimization by stabilizing and diagnosing models, exploring techniques to improve performance, identify issues, and build resilient neural networks for real-world applications.

• Coursera
• 1 hour 57 minutes
• Self-Paced
• Paid Course

Hands-on Deep Learning

Master practical deep learning by building neural networks, CNNs, transformers, and generative AI models for real-world applications with unstructured data.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Deep Learning

Master neural networks, CNNs, RNNs, transformers, and generative models with theory and applications in computer vision, NLP, and robotics from MIT.

• MIT OpenCourseWare
• Self-Paced
• Free Online Course

Career Certificate

Deep Learning

986 ratings at Udacity

Master deep learning by building neural networks, CNNs, Transformers, GANs, and Diffusion Models using PyTorch, with hands-on projects in image classification, NLP, and generative AI.

• Udacity
• 50 hours
• Self-Paced
• Paid Course