Professional Certificate in Data Science for Software Testers
-- ViewingNowThe Professional Certificate in Data Science for Software Testers is a crucial course designed to meet the growing industry demand for data-driven software testing professionals. This certificate course empowers learners with essential data science skills, enabling them to apply statistical methods and machine learning algorithms to software testing, thereby increasing automation efficiency and defect detection.
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⢠Introduction to Data Science: Understanding the basics of data science, its importance, and the role of software testers in data science projects.
⢠Statistical Analysis: Learning fundamental statistical concepts, including data exploration, probability distributions, statistical inference, and hypothesis testing.
⢠Data Visualization: Techniques for creating informative and engaging visual representations of data, such as bar charts, line charts, scatter plots, and heatmaps.
⢠Data Preprocessing: Techniques for cleaning and preparing data for analysis, including data imputation, outlier detection, and data normalization.
⢠Machine Learning for Software Testers: Understanding the basics of machine learning, including supervised and unsupervised learning, model evaluation, and hyperparameter tuning.
⢠Python for Data Science: Learning the basics of Python programming and popular data science libraries, such as NumPy, Pandas, and Matplotlib.
⢠SQL for Data Science: Understanding the basics of SQL and how to query databases to extract data for analysis.
⢠Data Science Project Management: Best practices for managing data science projects, including setting project goals, managing timelines, and communicating results.
⢠Ethics in Data Science: Understanding the ethical considerations involved in data science projects, including data privacy, bias, and fairness.
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