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AI Engineering Course
Take your tech career higher with our AI Engineering Course, yaffe. It's made for tech experts who are serious about mastering AI. You'll go deep into model evaluation using things like Recall, F1-Score, and cross-validation. Sharpen your skills at proper documentation and check out machine learning algorithms for figuring out churn (when customers leave), including decision trees and logistic regression. Become a proper expert in data exploration, feature encoding, and ways to optimize your models. Join us and change data into proper insights and make new things happen in your work, mazima!
- Master model evaluation: Improve your accuracy with Recall, F1-Score, and Precision, surely.
- Document effectively: Explain your choices well and understand the results clearly.
- Predict churn: Use Decision Trees, Random Forests, and Logistic Regression to see who is going to chaka.
- Prepare data: Do proper exploratory analysis and handle missing data well.
- Optimize models: Put ensemble methods in place and fine-tune your hyperparameters properly.

flexible workload from 4 to 360h
certificate recognized by MEC
What will I learn?
Take your tech career higher with our AI Engineering Course, yaffe. It's made for tech experts who are serious about mastering AI. You'll go deep into model evaluation using things like Recall, F1-Score, and cross-validation. Sharpen your skills at proper documentation and check out machine learning algorithms for figuring out churn (when customers leave), including decision trees and logistic regression. Become a proper expert in data exploration, feature encoding, and ways to optimize your models. Join us and change data into proper insights and make new things happen in your work, mazima!
Elevify advantages
Develop skills
- Master model evaluation: Improve your accuracy with Recall, F1-Score, and Precision, surely.
- Document effectively: Explain your choices well and understand the results clearly.
- Predict churn: Use Decision Trees, Random Forests, and Logistic Regression to see who is going to chaka.
- Prepare data: Do proper exploratory analysis and handle missing data well.
- Optimize models: Put ensemble methods in place and fine-tune your hyperparameters properly.
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
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