Machine Learning and Deep Learning Course
5/5
This course equips learners with practical skills to build and deploy AI solutions for support ticket automation using machine learning and deep learning techniques.

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.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 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 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 supplementary videos really help with learning.

Giulio CarloPrompt Engineering Student
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