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Machine Learning and Deep Learning Course

5/5
Machine Learning and Deep Learning Course
5.0 rating
4 to 360 hours of flexible workload
certificate valid in your country

What Will I Learn?

This Machine Learning and Deep Learning Course provides a quick, practical route to developing reliable support ticket AI. Learn to define problems, create high-quality datasets, and process text using modern embeddings. Gain expertise in classification and answer suggestion models, evaluation metrics, A/B testing, and optimisation. Lastly, integrate, monitor, and enhance systems with robust safety, privacy, and risk controls.

Elevify Advantages

Develop Skills

  • ML problem framing: convert messy support objectives into clear ML tasks quickly.
  • Data pipelines: design, clean, label, and split actual support ticket data.
  • Text modelling: develop sturdy classifiers using CNN, RNN, and Transformers.
  • Answer generation: create secure, fine-tuned retrieval-plus-generation processes.
  • MLOps for support: deploy, monitor, and refine ticket AI in production.

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.
Workload: between 4 and 360 hours

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... thank you for everything you do, I've already recommended you to others...
Giulio Carlo
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 Ferres
Mariana FerresPhotography Student
I like the content and the way the videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and easy to use. The variety of content and the supplementary videos really help with learning.
Giulio Carlo
Giulio CarloPrompt Engineering Student

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