Overview
Curriculum
Data cleaning is the process of identifying and correcting or removing errors, inconsistencies, and irrelevant information from a dataset. The goal of data cleaning is to prepare the data for further analysis, modeling, or visualization by ensuring that it is accurate, consistent, and relevant.
Courses you might be interested in
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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24 Lessons
$100.00
This module will equip you with the foundational programming knowledge and theory needed to excel in the bootcamp. By covering essential Python concepts and tools, we aim to ensure a...
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13 Lessons
$100.00
In this module, you will explore the world of large language models (LLMs), including their components, how they process information, and the challenges of adopting them in enterprise settings. You...
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7 Lessons
$100.00
In this module, you will explore key concepts of transformer architecture, embeddings, attention mechanisms, and tokenization. You’ll gain a deeper understanding of semantic similarity and how it is calculated using...
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5 Lessons
$100.00