{"id":4160,"date":"2025-08-06T10:22:32","date_gmt":"2025-08-06T10:22:32","guid":{"rendered":"https:\/\/uplatz.com\/blog\/?p=4160"},"modified":"2025-08-06T10:22:32","modified_gmt":"2025-08-06T10:22:32","slug":"data-science-flashcards","status":"publish","type":"post","link":"https:\/\/uplatz.com\/blog\/data-science-flashcards\/","title":{"rendered":"Data Science Flashcards"},"content":{"rendered":"
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Data Wrangling<\/div>\n
Cleaning, transforming, and organizing raw data into a usable format.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Exploratory Data Analysis (EDA)<\/div>\n
Analyzing datasets to summarize key characteristics using statistics and visualizations.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Data Visualization<\/div>\n
Using visual tools like graphs and charts to communicate data insights.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Statistics<\/div>\n
Understanding mean, median, standard deviation, distributions, and hypothesis testing.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Probability<\/div>\n
Foundation of inferential statistics and machine learning \u2013 deals with uncertainty in data.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Machine Learning<\/div>\n
Training algorithms to find patterns in data and make predictions or decisions.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Feature Engineering<\/div>\n
Creating new features or transforming existing ones to improve model performance.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Model Evaluation<\/div>\n
Using metrics like accuracy, precision, recall, and ROC-AUC to assess model performance.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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SQL for Data<\/div>\n
Querying databases to extract, manipulate, and analyze structured data efficiently.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Big Data Tools<\/div>\n
Technologies like Hadoop, Spark, and Hive used to process large-scale data.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Python & R<\/div>\n
Popular programming languages for data analysis, visualization, and modeling.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n
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Data Ethics<\/div>\n
Ensuring data privacy, fairness, and transparency in data science projects and models.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Data Wrangling Cleaning, transforming, and organizing raw data into a usable format. Exploratory Data Analysis (EDA) Analyzing datasets to summarize key characteristics using statistics and visualizations. Data Visualization Using visual Read More …<\/a><\/span><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[143,2392],"tags":[],"class_list":["post-4160","post","type-post","status-publish","format-standard","hentry","category-data-science","category-flashcards"],"yoast_head":"\nData Science Flashcards | Uplatz Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/uplatz.com\/blog\/data-science-flashcards\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data Science Flashcards | Uplatz Blog\" \/>\n<meta property=\"og:description\" content=\"Data Wrangling Cleaning, transforming, and organizing raw data into a usable format. Exploratory Data Analysis (EDA) Analyzing datasets to summarize key characteristics using statistics and visualizations. 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