Global Certificate in Predictive Analytics for Students
-- ViewingNowThe Global Certificate in Predictive Analytics for Students course is a comprehensive program designed to equip learners with the essential skills required in the rapidly growing field of predictive analytics. This course is of utmost importance due to the increasing demand for predictive analytics in various industries, including healthcare, finance, marketing, and technology.
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⢠Introduction to Predictive Analytics: Defining predictive analytics, understanding its importance, and exploring real-world applications.
⢠Data Preparation for Predictive Modeling: Data collection, data cleaning, data transformation, and feature selection for predictive models.
⢠Statistical Analysis: Descriptive statistics, inferential statistics, probability distributions, statistical testing, and regression analysis.
⢠Machine Learning Fundamentals: Supervised learning, unsupervised learning, reinforcement learning, model evaluation metrics, and bias-variance trade-off.
⢠Predictive Modeling Techniques: Linear regression, logistic regression, decision trees, random forests, and support vector machines.
⢠Time Series Analysis: Autoregressive integrated moving average (ARIMA), exponential smoothing, seasonal decomposition, and anomaly detection.
⢠Natural Language Processing: Text preprocessing, sentiment analysis, topic modeling, and named entity recognition.
⢠Deep Learning for Predictive Analytics: Artificial neural networks, convolutional neural networks, recurrent neural networks, and long short-term memory networks.
⢠Ethical Considerations and Bias Mitigation: Understanding ethical implications, detecting and mitigating biases, ensuring fairness, transparency, and accountability in predictive analytics.
⢠Deployment and Maintenance of Predictive Models: Model deployment, monitoring, updating, and maintaining in production environments.
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