Machine Learning Crash Course
This crash course provides a practical introduction to machine learning, focusing on building and deploying models for ticket priority prediction using text and metadata.

4 to 360h flexible workload
certificate valid in your country
What will I learn?
Machine Learning Crash Course gives you a fast, practical path from raw text and metadata to reliable ticket priority models. Learn data cleaning, categorical encoding, text preprocessing, and feature engineering with TF-IDF, embeddings, and keyword flags. Build and evaluate models using clear metrics, error analysis, and thresholding, then integrate them safely into real 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 the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students are saying
Your classes are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to switch platforms... I thank you for everything you do, I've already recommended you to other people...

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

Mariana FerresPhotography Student
I like the content and the presentation style and video transcription, which speeds up the process!

Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos really help with learning.

André FelipePrompt Engineering Student
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