Learn to build and train powerful image recognition models using convolutional neural networks and TensorFlow, combining deep learning theory with hands-on coding and real-world datasets.
DeepLearning.AI via Coursera
16 hours 33 minutes
Paid Certificate Available
Simplified introduction to neural networks, covering architectures and training for AI applications.
via Udemy
2 hours
Develop advanced AI models using CNNs, transfer learning, and RNNs for complex tasks.
Packt via Coursera
11 hours
Paid Certificate Available
Build RNN models for natural language processing tasks like sentiment analysis using AI techniques.
Packt via Coursera
7 hours 58 minutes
Paid Certificate Available
Explore RNN architectures using TensorFlow to build advanced AI models for sequence data like text and time series.
Packt via Coursera
5 hours 6 minutes
Paid Certificate Available
Gain practical skills building and training neural networks using PyTorch for AI development.
Packt via Coursera
7 hours 37 minutes
Paid Certificate Available
Dive deeper into Recurrent Neural Networks with advanced concepts and practical AI projects.
Packt via Coursera
6 hours 28 minutes
Paid Certificate Available
Understand and implement neural networks and random forests, key machine learning algorithms for classification and regression tasks.
LearnQuest via Coursera
10 hours 16 minutes
Paid Certificate Available
Learn foundational concepts of DNNs and RNNs. Build deep learning models using Python to analyze structured and sequential data with real-world applications in AI.
Packt via Coursera
6 hours 36 minutes
Paid Certificate Available
Learn core deep learning techniques for healthcare applications, focusing on neural network models to improve diagnostics, patient monitoring, and trustworthy clinical decision support.
University of Illinois at Urbana-Champaign via Coursera
22 hours
Paid Certificate Available