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AI ML Course
Unlock the power of AI and machine learning for business intelligence with our well-structured AI/ML Course (Ghana). Enter into understanding customer leaving (churn), explore how to prepare data, and become good at using classification algorithms like logistic regression and decision trees. Learn how to get useful information, make models better, and give data-driven advice. This course dey be perfect for professionals wey dey look to improve their skills for data collection, model evaluation, and predicting customer leaving. E dey offer practical, top-quality learning wey you go fit do for your own time.
- Master customer leaving (churn): Analyze and reduce how customer leaving dey affect business success.
- Data preparation (preprocessing): Deal with missing values and scale features for better analysis.
- Predictive modeling: Use logistic regression and decision trees to predict customer leaving.
- Model evaluation: Check accuracy, precision, recall, and F1-score well well.
- Optimize models: Use cross-validation and hyperparameter tuning to make models better.

flexible workload of 4 to 360h
certificate recognized by the MEC
What will I learn?
Unlock the power of AI and machine learning for business intelligence with our well-structured AI/ML Course (Ghana). Enter into understanding customer leaving (churn), explore how to prepare data, and become good at using classification algorithms like logistic regression and decision trees. Learn how to get useful information, make models better, and give data-driven advice. This course dey be perfect for professionals wey dey look to improve their skills for data collection, model evaluation, and predicting customer leaving. E dey offer practical, top-quality learning wey you go fit do for your own time.
Elevify advantages
Develop skills
- Master customer leaving (churn): Analyze and reduce how customer leaving dey affect business success.
- Data preparation (preprocessing): Deal with missing values and scale features for better analysis.
- Predictive modeling: Use logistic regression and decision trees to predict customer leaving.
- Model evaluation: Check accuracy, precision, recall, and F1-score well well.
- Optimize models: Use cross-validation and hyperparameter tuning to make models 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 workloadWhat our students say
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