Machine Learning Crash Course
Machine Learning Quick Start Guide equips tech workers to transform chaotic support tickets into sharp priority forecasts. Using hands-on models, text processing tricks, and deploy-ready metrics, you'll slash response times and boost customer satisfaction right away. Perfect for fast results in busy teams handling real-world data challenges.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This quick-start course takes you from raw data like text and details to solid models that predict ticket priorities. You'll master cleaning data, handling categories, preparing text, and creating features using TF-IDF, embeddings, and key flags. Build and check models with simple metrics, error checks, and cut-offs, then add them to daily work with tracking, updates, and risk checks.
Elevify advantages
Develop skills
- Define ML models for tickets: set inputs, outputs, labels, and goals quickly.
- Create speedy text features: tidy data, code categories, use TF-IDF.
- Build simple proof models: regression, trees, basic team-ups.
- Assess wisely: choose key metrics, spot errors, adjust limits.
- Roll out easy ML: track changes, handle risks, improve with team input.
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 lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of my interest without needing to change 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 way videos are presented and transcribed, which speeds up the process!
Luciana AlvarengaNail Design Student
The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.
André FelipePrompt Engineering Student
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