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Machine Learning and Deep Learning Course

4.3/5
Machine Learning and Deep Learning Course
4.3 in the evaluation
4 to 360 hours flexible workload
valid certificate in your country

What will I learn?

This Machine Learning and Deep Learning Course provides a swift, practical route to developing dependable support ticket AI. Learn to formulate problems, create high-quality datasets, and process text using contemporary 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: turn messy support goals into clear ML tasks fast.
  • Data pipelines: design, clean, label, and split real support ticket data.
  • Text modelling: build robust classifiers with CNN, RNN, and Transformers.
  • Answer generation: craft safe, tuned retrieval-plus-generation workflows.
  • MLOps for support: deploy, monitor, and improve 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 lessons are perfect. I purchased the one-year package and finally have the opportunity to follow various topics of interest without needing to change platforms... I'm grateful for everything you do, I've already recommended you to other people...
Giulio Carlo
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 Ferres
Mariana FerresPhotography Student
I like the content and the way videos are presented and transcribed, which speeds up the process!
Luciana Alvarenga
Luciana AlvarengaNail Design Student
The platform is fast and simple to use. The diversity of content and complementary videos really help with learning.
André Felipe
André FelipePrompt Engineering Student

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