- Prompt Engineering
- Artificial Neural Networks
- PyTorch (Machine Learning Library)
- Deep Learning
- Generative AI
- Natural Language Processing
- Keras (Neural Network Library)
- LLM Application
- Machine Learning Algorithms
- Network Architecture
- Large Language Modeling
- Artificial Intelligence
Deep Learning for Natural Language Processing
Completed by SK. Yeasin Ahsanullah Al-Galib
October 6, 2025
20 hours (approximately)
SK. Yeasin Ahsanullah Al-Galib'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
