Machine Learning and Deep Learning Course
4.3/5
Master machine learning and deep learning for support ticket AI. Learn data design, text preprocessing, model training, evaluation, and deployment to build accurate, safe, and scalable classification and answer-suggestion systems for real-world tech environments. This course equips you with practical skills to create reliable AI solutions for handling support tickets efficiently in production settings.
4.3 in the evaluation
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Machine Learning and Deep Learning Course gives you a fast, practical path to building reliable support ticket AI. Learn to frame problems, design high-quality datasets, and prepare text with modern embeddings. Master classification and answer suggestion models, evaluation metrics, A/B testing, and optimization. Finally, integrate, monitor, and improve systems with strong 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 modeling: 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 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
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The platform is fast, simple to use. The diversity of content and complementary videos help a lot with learning.
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