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AI Engineering Course
Take your tech career to the next level with our AI Engineering Course, wey dem design am for tech people wey dey eager to be proper AI masters. You go dive deep inside model evaluation techniques like Recall, F1-Score, and cross-validation. Sharpen your skills for dey document things proper proper and explore machine learning algorithms for churn prediction, including decision trees and logistic regression. You go get proper expertise for inside data exploration, feature encoding, and how to optimize models well well. Join we so you fi turn data into things wey you fit use take do something and bring new ideas for your work.
- Master model evaluation: Make sure your models dey accurate well well with Recall, F1-Score, and Precision.
- Document effectively: Explain why you do am so and interpret the results make e clear for everybody to understand.
- Predict churn: Use Decision Trees, Random Forests, and Logistic Regression for know who go leave.
- Prepare data: Do exploratory analysis and handle data wey dey miss well well.
- Optimize models: Use ensemble methods and fine-tune hyperparameters for make your models work better.
flexible workload of 4 to 360h
certificate recognized by the MEC
What will I learn?
Take your tech career to the next level with our AI Engineering Course, wey dem design am for tech people wey dey eager to be proper AI masters. You go dive deep inside model evaluation techniques like Recall, F1-Score, and cross-validation. Sharpen your skills for dey document things proper proper and explore machine learning algorithms for churn prediction, including decision trees and logistic regression. You go get proper expertise for inside data exploration, feature encoding, and how to optimize models well well. Join we so you fi turn data into things wey you fit use take do something and bring new ideas for your work.
Elevify advantages
Develop skills
- Master model evaluation: Make sure your models dey accurate well well with Recall, F1-Score, and Precision.
- Document effectively: Explain why you do am so and interpret the results make e clear for everybody to understand.
- Predict churn: Use Decision Trees, Random Forests, and Logistic Regression for know who go leave.
- Prepare data: Do exploratory analysis and handle data wey dey miss well well.
- Optimize models: Use ensemble methods and fine-tune hyperparameters for make your models work better.
Suggested summary
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