Coursera MOOC / Non-credit 0

Predictive Models: Build, Explore Data & Deploy

Name: Predictive Models: Build, Explore Data & Deploy
Price: 49 USD
Availability: InStock

About this course

Build practical skills in predictive modeling by working through the complete model development lifecycle using a real-world banking use case. In this course, you will define a business problem, explore and interpret data through Exploratory Data Analysis (EDA), and prepare datasets using data imputation and variable selection techniques. Next, you will develop predictive models using Information Value (IV) analysis and multicollinearity checks to identify meaningful variables. You will evaluate model performance with ranking techniques, decile analysis, KS statistics, AUC, and Lift, then improve model performance through monotonic binning and tree-based optimization methods. The course concludes by validating models on unseen datasets and deploying them to a simulated production environment, giving you practical experience with the end-to-end predictive modeling workflow. Whether you are a learner interested in predictive analytics, machine learning workflows, or data-driven decision-making, this course provides a structured, hands-on approach to building, evaluating, optimizing, validating, and deploying predictive models using established statistical techniques and real-world business scenarios.

68/100

CourseAsk score

What the provider tells you: 32/45
Who stands behind it: 20/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

define business problems for predictive modeling
conduct Exploratory Data Analysis (EDA)
prepare datasets using data imputation
perform variable selection
develop predictive models
evaluate model performance with various techniques
improve model performance through optimization methods
validate models on unseen datasets
deploy models in a simulated production environment

Machine Learning #data-driven decision making #model evaluation #predictive modeling #exploratory data analysis #variable selection #model validation #multicollinearity #lift #data imputation #information value #ranking techniques #decile analysis #ks statistics #auc #monotonic binning #tree-based optimization

$49.00

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