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AI Engineering Course
Step up yo tech game wit our AI Engineering Course, design special for tech people wey sabi road but wan sabi AI betta. Dig di ground inside model evaluation like Recall, F1-Score, and cross-validation. Sharpen yo hand for how to write things down proper, and check out machine learning ways dem for tellin' who go comot (churn prediction), like decision trees and logistic regression. Get correct correct knowledge for how to check data well, change features to number, and make models run fine. Join we so we fit turn data into something wey go help we make correct decisions and bring new ideas for yo work.
- Sabi model evaluation well well: Make sure yo work correct wit Recall, F1-Score, and Precision.
- Write things down clear: Explain why you do am so, and tell people weh you see plain.
- Tell who go comot: Use Decision Trees, Random Forests, and Logistic Regression for know dem.
- Prepare data fine: Check di data well and handle data wey loss quick quick.
- Make models run fine: Use different methods wey join bodi and tune dem well well.
from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Step up yo tech game wit our AI Engineering Course, design special for tech people wey sabi road but wan sabi AI betta. Dig di ground inside model evaluation like Recall, F1-Score, and cross-validation. Sharpen yo hand for how to write things down proper, and check out machine learning ways dem for tellin' who go comot (churn prediction), like decision trees and logistic regression. Get correct correct knowledge for how to check data well, change features to number, and make models run fine. Join we so we fit turn data into something wey go help we make correct decisions and bring new ideas for yo work.
Elevify advantages
Develop skills
- Sabi model evaluation well well: Make sure yo work correct wit Recall, F1-Score, and Precision.
- Write things down clear: Explain why you do am so, and tell people weh you see plain.
- Tell who go comot: Use Decision Trees, Random Forests, and Logistic Regression for know dem.
- Prepare data fine: Check di data well and handle data wey loss quick quick.
- Make models run fine: Use different methods wey join bodi and tune dem well well.
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 workloadWhat our students say
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