Convolutional Networks Courses and Certifications

Career Certificate

Learning Deep Learning

Master neural networks, CNNs, RNNs, transformers, and LLMs using TensorFlow and PyTorch for real-world AI applications like image classification and language translation.

• Coursera
• 4 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 3 courses

Coursera

TensorFlow for Beginners: Basic Binary Image Classification

Learn to build and train a neural network for classifying cat and dog images using TensorFlow. Covers data preprocessing, CNN architecture, hyperparameter tuning, and model evaluation techniques.

• Coursera
• 3 hours 12 minutes
• Self-Paced
• Paid Course

Packt

Advanced Generative Adversarial Networks (GANs)

Master AI-driven image synthesis with GANs. Learn architectures, implement models, and optimize performance using popular datasets. Apply knowledge to generate realistic images for practical applications.

• Coursera
• 12 hours 46 minutes
• Self-Paced
• Paid Course

Packt

Advanced Machine Learning and Deep Learning

Master advanced machine learning and deep learning techniques, from neural networks to CNNs and RNNs. Apply knowledge through hands-on labs, covering regression, classification, and specialized topics like autoencoders and transfer learning.

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

Packt Career Certificate

AI Engineering Masterclass: From Zero to AI Hero

Master AI engineering from Python basics to advanced neural networks, deep learning, and real-world applications like image classification and sentiment analysis.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Coursera Career Certificate

Satellite Imagery, Remote Sensing & Machine Learning

Master satellite imagery analysis and machine learning to transform raw Earth observation data into actionable environmental insights for GIS, climate, and sustainability applications.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 8 courses

Edureka

Practical Deep Learning with Python

Master deep learning fundamentals and advanced architectures like CNNs, RNNs, and LSTMs through hands-on Python implementation. Build, optimize, and evaluate models for real-world AI applications.

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

Deep Learning Frameworks and Neural Networks Simplified

Master advanced deep learning skills with TensorFlow, Keras, and neural networks. Build cutting-edge AI models, implement RNNs and LSTMs, and develop practical solutions for real-world challenges.

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

Master custom neural network design by comparing CNNs, RNNs, and Transformers, then build optimized PyTorch architectures with proper layers, activations, and regularization techniques.

• Coursera
• 1 hour 44 minutes
• Self-Paced
• Paid Course

Packt Career Certificate

Modern Natural Language Processing

Master neural networks, probability models, and Transformers for text classification, NER, POS tagging, and advanced NLP applications using TensorFlow and Python.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 3 courses

Packt

Advanced CNNs, Transfer Learning, and Recurrent Networks

Master advanced CNNs, transfer learning, and RNNs. Apply cutting-edge techniques to real-world datasets, from medical imaging to text generation. Gain practical skills through hands-on case studies and industry-relevant projects.

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

Packt

Natural Language Processing - Deep Learning Models in Python

Master deep learning models for NLP with Python, implementing neural networks, CNNs, and RNNs for text classification, embeddings, and sequential data processing using TensorFlow.

• Coursera
• 10 hours 33 minutes
• Self-Paced
• Paid Course

Packt

Deep Learning - Computer Vision for Beginners Using PyTorch

Master PyTorch and deep learning for computer vision. Build neural networks, implement CNNs, and apply skills to real-world datasets. Includes optional Python basics and data science libraries.

• Coursera
• 9 hours 40 minutes
• Self-Paced
• Paid Course

Edureka

Neural Networks and Computer Vision Foundations

Master neural networks and computer vision by building models from scratch, applying CNNs, optimization, and regularization to solve real-world image classification and detection tasks.

• Coursera
• 11 hours 29 minutes
• Self-Paced
• Paid Course

Coursera

Building and Optimizing AI Models

Master the full AI model lifecycle—design neural networks, apply transfer learning, optimize deep learning workflows, and benchmark performance using Python and TensorFlow.

• Coursera
• 7 hours 33 minutes
• Self-Paced
• Paid Course