Global Certificate in Data Science Essentials: Analytical Techniques
-- ViewingNowThe Global Certificate in Data Science Essentials: Analytical Techniques is a comprehensive course that imparts critical data science skills in high demand by today's industries. This program equips learners with essential knowledge in data manipulation, visualization, and analytical techniques using real-world data, empowering them to derive valuable insights and make data-driven decisions.
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โข Data Collection Techniques: An introduction to various data collection methods, including surveys, web scraping, interviews, and experiments. Emphasis on selecting the appropriate method based on the research question and data type.
โข Data Cleaning and Pre-processing: Techniques for cleaning and preparing datasets for analysis, such as handling missing values, outliers, and inconsistent data.
โข Data Visualization: An overview of data visualization techniques, including chart types, color theory, and best practices for creating effective visualizations.
โข Exploratory Data Analysis: Methods for exploring and summarizing datasets, including measures of central tendency, variability, and correlation.
โข Statistical Inference: Foundational concepts of statistical inference, including hypothesis testing, confidence intervals, and p-values.
โข Regression Analysis: Techniques for modeling relationships between variables using linear and logistic regression. Includes an introduction to assumptions, diagnostics, and model selection.
โข Machine Learning Fundamentals: Overview of machine learning approaches, including supervised, unsupervised, and reinforcement learning.
โข Experimental Design and Causal Inference: Methods for designing experiments to test causal relationships, including randomized controlled trials and natural experiments.
โข Ethics in Data Science: Discussion of ethical considerations in data science, including privacy, bias, and fairness in algorithmic decision-making.
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