Natural Language Processing Course
This course teaches practical NLP techniques to analyze reviews and ratings, covering text preprocessing, feature extraction, sentiment analysis, topic modeling, and reporting insights for product improvement.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This Natural Language Processing Course shows you how to turn raw reviews and ratings into clear, data-driven insights. You will clean and preprocess text, run exploratory analysis, build sentiment and classification models, extract topics, and design robust pipelines. Learn essential Python tools, evaluate performance, and present concise, actionable findings that improve products and user experience.
Elevify advantages
Develop skills
- Practical text cleaning: tokenise, normalise, and prep reviews for fast NLP.
- Hands-on feature extraction: build TF-IDF, n-grams, and embeddings that work.
- Applied sentiment modelling: train, tune, and explain review classifiers quickly.
- Topic modelling in practice: LDA, NMF, and clustering for clear customer themes.
- Insight reporting: turn NLP outputs into sharp, data-driven product actions.
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
Your classes are perfect. I got the one-year package and finally have the chance to follow a range of topics I'm interested in without having to switch platforms... thank you for everything you do, I've already recommended you to others...

Giulio CarloDigital Marketing Student
I like how the lessons get straight to the point and how I can switch chapters and skip content I don't need.

Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the extra videos really help with learning.

Giulio CarloPrompt Engineering Student
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