Introduction to Deep Learning & Neural Networks with Keras
Completed by Eduardo Jose Graterol Mendez
February 11, 2026
10 hours (approximately)
Eduardo Jose Graterol Mendez's account is verified. Coursera certifies their successful completion of Introduction to Deep Learning & Neural Networks with Keras
What you will learn
Describe the foundational concepts of deep learning, neurons, and artificial neural networks to solve real-world problems
Explain the core concepts and components of neural networks and the challenges of training deep networks
Build deep learning models for regression and classification using the Keras library, interpreting model performance metrics effectively.
Design advanced architectures, such as CNNs, RNNs, and transformers, for solving specific problems like image classification and language modeling
Skills you will gain
- Category: Model Optimization
- Category: Network Architecture
- Category: Recurrent Neural Networks (RNNs)
- Category: Convolutional Neural Networks
- Category: Natural Language Processing
- Category: Applied Machine Learning
- Category: Autoencoders
- Category: Keras (Neural Network Library)
- Category: Model Training
- Category: Deep Learning
- Category: Artificial Neural Networks
- Category: Machine Learning
