Deep Learning for Natural Language Processing
Completed by Chang Jin Lynn
January 11, 2026
21 hours (approximately)
Chang Jin Lynn's account is verified. Coursera certifies their successful completion of Deep Learning for Natural Language Processing
What you will learn
Define feedforward networks, recurrent neural networks, attention, and transformers.
Implement and train feedforward networks, recurrent neural networks, attention, and transformers.
Describe the idea behind transfer learning and frequently used transfer learning algorithms.
Design and implement their own neural network architectures for natural language processing tasks.
Skills you will gain
- Category: Fine-tuning
- Category: Recurrent Neural Networks (RNNs)
- Category: Transfer Learning
- Category: Model Optimization
- Category: Generative Model Architectures
- Category: Large Language Modeling
- Category: Model Training
- Category: Deep Learning
- Category: Artificial Neural Networks
- Category: Embeddings
- Category: Prompt Engineering
- Category: Natural Language Processing
