Advanced Neural Network Techniques
Completed by Julia Yi
April 4, 2025
10 hours (approximately)
Julia Yi'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: Artificial Neural Networks
- Category: Unsupervised Learning
- Category: Generative AI
- Category: Markov Model
- Category: Data Ethics
- Category: Generative Model Architectures
- Category: Deep Learning
- Category: Reinforcement Learning
- Category: Generative Adversarial Networks (GANs)
- Category: Responsible AI
- Category: Recurrent Neural Networks (RNNs)
- Category: Autoencoders
