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Before data can be analyzed, it needs to be clean, structured, and ready for use. This module covers essential data wrangling techniques to handle missing values, remove duplicates, merge datasets,...
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8 Lessons
$100.00
In this module, we’ll explore how to turn raw data into compelling visual stories. We’ll learn how to choose the right visualizations for different data types, and apply tools like...
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12 Lessons
$100.00
In this module, we’ll explore how to use predictive modelling to create real business impact. We’ll learn to identify the right opportunities for machine learning, translate business goals into actionable...
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8 Lessons
$100.00
In this module, we’ll focus on data exploration, visualization, and feature engineering—essential steps in preparing data for analysis. We’ll learn how to use techniques like summary statistics and visual tools...
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13 Lessons
$100.00
In this module, we will explore how to build efficient data pipelines for integrating, transforming, and managing data from various sources. We will cover the fundamentals of RESTful APIs, HTTP...
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9 Lessons
$100.00
Access the full recordings from the 5-day LLM Bootcamp to catch up on missed content or revisit critical discussions. These recordings allow you to review key concepts and techniques at...
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21 Lessons
$10.00
Data manipulation refers to the process of transforming raw data into a format that is more suitable for analysis and modeling. The goal of data manipulation is to clean, organize,...
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33 Lessons
Free
Data enrichment is the process of enhancing, refining, and improving raw data by adding more information to it from external sources. This can include adding additional fields, filling in missing...
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15 Lessons
Free
Data validation is the process of ensuring that data is accurate, complete, and consistent. It involves verifying that data meets certain criteria, such as data type, value range, and formatting...
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26 Lessons
Free