Deep Learning with Python Course
Gain expertise in deep learning using Python to create short text classifiers with CNNs, RNNs, and transformers. Master data preparation, feature engineering, model tuning, performance evaluation, explainability, and deployment of production-grade NLP models for practical tech solutions, ensuring reliability and ethics.
flexible workload of 4 to 360h
valid certificate in your country
What will I learn?
This course teaches building precise short-text classifiers end-to-end using Python. Learners explore datasets, preprocess text via cleaning and tokenisation, craft features, and implement CNN, RNN, and transformer models. It covers hyperparameter tuning, managing class imbalance, apt evaluation metrics, model explainability, and deploying efficient models with monitoring and ethical practices.
Elevify advantages
Develop skills
- Build strong short-text classifiers using CNN, RNN, and transformer architectures.
- Develop effective text features through tokenisation, embeddings, and data cleaning.
- Create reliable NLP pipelines with proper data splits, versioning, and augmentation techniques.
- Optimise deep learning models via hyperparameter tuning and performance monitoring.
- Deploy efficient, ethical short-text classifiers with low latency and high explainability.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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