Machine Learning Crash Course
This quick course provides hands-on experience in building, evaluating, and deploying machine learning models for ticket prioritization, focusing on text data processing and practical integration.

flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
Machine Learning Quick Course offers you a swift, hands-on route from raw text and details to dependable ticket priority models. Learn data cleaning, categorical encoding, text preprocessing, and feature engineering using TF-IDF, embeddings, and keyword flags. Build and assess models with straightforward metrics, error analysis, and thresholding, then integrate them securely into actual workflows with monitoring, iteration, and risk awareness.
Elevify advantages
Develop skills
- Frame ML ticket models: define inputs, outputs, labels, and success in days.
- Build fast text features: clean text, encode metadata, and apply TF-IDF.
- Train quick POC models: logistic regression, trees, and simple ensembles.
- Evaluate safely: pick business-aware metrics, analyze errors, tune thresholds.
- Deploy lightweight ML: monitor drift, manage risks, and refine with human feedback.
Suggested summary
Before starting, you can change the chapters and 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 several topics I'm interested in without having to switch platforms... I appreciate everything you do, I've already recommended you to others...

Giulio CarloDigital Marketing Student
I like how the lessons are 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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