Global Certificate Math Education: A Data-Driven Approach
-- ViewingNowThe Global Certificate Math Education: A Data-Driven Approach is a comprehensive course designed to empower educators with the latest data-driven teaching strategies in mathematics. This course emphasizes the importance of data analysis in enhancing students' learning experience, ensuring better understanding and retention of mathematical concepts.
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⢠Data Analysis and Probability: Understanding the basics of data analysis, including data collection, organization, and interpretation. Exploring fundamental probability concepts such as events, outcomes, and probability rules.
⢠Statistical Inference: Learning about statistical inference methods, such as hypothesis testing, confidence intervals, and p-values.
⢠Regression Analysis: Studying the principles of regression analysis, including simple linear regression, multiple linear regression, and logistic regression.
⢠Descriptive Statistics: Analyzing data using descriptive statistics, including mean, median, mode, variance, and standard deviation.
⢠Data Visualization: Understanding the principles of data visualization and how to create effective charts, graphs, and plots to communicate data insights.
⢠Machine Learning: Introducing the foundations of machine learning, including supervised and unsupervised learning, clustering, and classification.
⢠Data Preprocessing: Learning techniques for data preprocessing, including data cleaning, data transformation, and feature engineering.
⢠Experimental Design: Exploring the principles of experimental design, including randomization, replication, and blocking.
⢠Data Ethics and Privacy: Examining ethical and privacy issues related to data collection, storage, and analysis.
Note: These units are not listed in any specific order.
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