Certificate in Predictive Modeling Fundamentals: Smart Decisions
-- ViewingNowThe Certificate in Predictive Modeling Fundamentals: Smart Decisions is a comprehensive course that empowers learners with the essential skills needed to make informed, data-driven decisions in today's data-centric world. This course covers the fundamentals of predictive modeling, a critical skill set in high demand across various industries, including finance, healthcare, marketing, and technology.
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⢠Introduction to Predictive Modeling: Defining predictive modeling, its importance, and real-world applications. Understanding the data mining process.
⢠Data Preparation: Data collection, cleaning, and preprocessing techniques. Feature selection and engineering.
⢠Regression Techniques: Simple and multiple linear regression, polynomial regression, and regularization methods.
⢠Classification Algorithms: Logistic regression, decision trees, random forests, and Support Vector Machines (SVMs).
⢠Unsupervised Learning: Clustering methods like K-means, hierarchical clustering, and dimensionality reduction with Principal Component Analysis (PCA).
⢠Model Evaluation: Performance metrics, including accuracy, precision, recall, F1 score, ROC curves, and confusion matrices.
⢠Model Selection and Tuning: Cross-validation, grid search, and other techniques to optimize model performance.
⢠Time Series Analysis: ARIMA, exponential smoothing, and decomposition methods for time series forecasting.
⢠Deep Learning Fundamentals: Introduction to neural networks, backpropagation, and convolutional neural networks.
⢠Ethics in Predictive Modeling: Addressing fairness, accountability, and transparency in predictive models.
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