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Predictive Analytics Analyst Course
Unlock di power wey dey inside Predictive Analytics wit our full training programme wey we design for Business Intelligence professionals dem. Enter inside data exploration, sabi data cleaning strategies well well, and learn how to build feature engineering so dat your model go dey more accurate. Get experience in selecting and training predictive models dem, including linear regression, decision trees, and advanced techniques like random forests. Develop skills in interpreting results and making fine fine reports to give business insights wey people fit use. Elevate your career wit practical, high-quality learning.
- Master data cleaning: Learn how to handle missing data and correct inconsistencies properly.
- Develop feature engineering: Create new features and put economic indicators inside.
- Select predictive models: Choose and use linear regression and decision trees.
- Train and evaluate models: Use data splitting methods to make dem perform well.
- Interpret model results: Give business insights wey people fit use and analyze important things wey dey drive results.

from 4 to 360h flexible workload
certificate recognized by MEC
What will I learn?
Unlock di power wey dey inside Predictive Analytics wit our full training programme wey we design for Business Intelligence professionals dem. Enter inside data exploration, sabi data cleaning strategies well well, and learn how to build feature engineering so dat your model go dey more accurate. Get experience in selecting and training predictive models dem, including linear regression, decision trees, and advanced techniques like random forests. Develop skills in interpreting results and making fine fine reports to give business insights wey people fit use. Elevate your career wit practical, high-quality learning.
Elevify advantages
Develop skills
- Master data cleaning: Learn how to handle missing data and correct inconsistencies properly.
- Develop feature engineering: Create new features and put economic indicators inside.
- Select predictive models: Choose and use linear regression and decision trees.
- Train and evaluate models: Use data splitting methods to make dem perform well.
- Interpret model results: Give business insights wey people fit use and analyze important things wey dey drive results.
Suggested summary
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