Advanced Neural Network Techniques
Completed by Diya Singh
March 9, 2026
10 hours (approximately)
Diya Singh's account is verified. Coursera certifies their successful completion of Advanced Neural Network Techniques
What you will learn
Analyze and implement Recurrent Neural Networks (RNNs) to process sequence data and solve tasks like time series prediction and language modeling.
Explore autoencoders for data compression, feature extraction, and anomaly detection, along with their applications in diverse fields.
Develop and evaluate generative models, such as GANs, understanding their mathematical foundations and deployment challenges.
Apply reinforcement learning techniques using Markov Chains and deep neural networks to tackle complex decision-making problems.
Skills you will gain
- Category: Deep Learning
- Category: Reinforcement Learning
- Category: Generative AI
- Category: Unsupervised Learning
- Category: Markov Model
- Category: Data Ethics
- Category: Artificial Neural Networks
- Category: Generative Model Architectures
- Category: Responsible AI
- Category: Recurrent Neural Networks (RNNs)
- Category: Autoencoders
- Category: Generative Adversarial Networks (GANs)
