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AI ML Course
Unlock di power of AI and machine learning for business intelligence wit our full Ai ML Course. Understand how customer dem dey go (churn), look well for how to prepare data, and master classification algorithms like logistic regression and decision trees. Learn how to get proper ideas wey you fit use, make models work better, and give advice based on data. E perfect for professionals wey wan make dem skills for data collection, model evaluation, and to know which customer go comot (churn prediction) strong. Dis course dey give practical, high-quality learning as you like.
- Master customer dem dey go (churn): Analyze and reduce how churn dey affect business.
- Data preparation: Manage missing data and arrange features well for correct analysis.
- Predictive modeling: Use logistic regression and decision trees to know which customer go comot (churn prediction).
- Model evaluation: Check accuracy, precision, recall, and F1-score well-well.
- Optimize models: Use cross-validation and hyperparameter tuning to make results better.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Unlock di power of AI and machine learning for business intelligence wit our full Ai ML Course. Understand how customer dem dey go (churn), look well for how to prepare data, and master classification algorithms like logistic regression and decision trees. Learn how to get proper ideas wey you fit use, make models work better, and give advice based on data. E perfect for professionals wey wan make dem skills for data collection, model evaluation, and to know which customer go comot (churn prediction) strong. Dis course dey give practical, high-quality learning as you like.
Elevify advantages
Develop skills
- Master customer dem dey go (churn): Analyze and reduce how churn dey affect business.
- Data preparation: Manage missing data and arrange features well for correct analysis.
- Predictive modeling: Use logistic regression and decision trees to know which customer go comot (churn prediction).
- Model evaluation: Check accuracy, precision, recall, and F1-score well-well.
- Optimize models: Use cross-validation and hyperparameter tuning to make results better.
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
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