Learning Deep Learning: Unit 2
Completed by Syed Hamdani
January 25, 2026
7 hours (approximately)
Syed Hamdani's account is verified. Coursera certifies their successful completion of Learning Deep Learning: Unit 2
What you will learn
Build and optimize convolutional neural networks for advanced image classification tasks using TensorFlow and PyTorch.
Apply recurrent neural networks and LSTMs to sequential data problems, including time series forecasting and text autocompletion.
Develop neural language models and implement word embeddings for robust natural language processing.
Design and implement encoder-decoder architectures and Transformer models for machine translation and sequence-to-sequence tasks.
Skills you will gain
- Category: Convolutional Neural Networks
- Category: Transfer Learning
- Category: Tensorflow
- Category: Deep Learning
- Category: Natural Language Processing
- Category: Recurrent Neural Networks (RNNs)
- Category: Generative Model Architectures
- Category: Model Training
- Category: PyTorch (Machine Learning Library)
- Category: Embeddings
- Category: Artificial Neural Networks
- Category: Time Series Analysis and Forecasting
