This course focuses on advanced methods for data cleaning, preparation, and optimization using AI-assisted tools. You'll learn to generate synthetic data, address privacy concerns and data limitations in your projects. Discover how to leverage AI to identify and resolve complex data quality issues, ensuring your datasets are primed for analysis.


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该课程共有5个模块
Explain the process of generating synthetic data using generative AI, identifying its applications and potential benefits in addressing data limitation
涵盖的内容
10个视频8篇阅读材料6个作业
Apply generative AI tools to identify and resolve complex data quality issues, such as outliers, inconsistencies, and errors,ensuring data integrity for accurate analysis.
涵盖的内容
7个视频6篇阅读材料6个作业
Analyze the impact of data preparation on subsequent analysis and utilize generative AI tools to automate and optimize preprocessing steps, ensuring data readiness for analysis
涵盖的内容
6个视频6篇阅读材料6个作业
Describe the key components of a well-structured dataset and the role of generative AI in enhancing data quality for analysis
涵盖的内容
7个视频7篇阅读材料6个作业
Evaluate the ethical implications of data processing and synthetic data generation, developing strategies to mitigate biases and ensure responsible and transparent data practices.
涵盖的内容
10个视频6篇阅读材料4个作业
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显示 3/20 个
已于 Mar 20, 2025审阅
Please include more practical on synthetic data generation, data cleaning and feature engineering. It was hell lot of theories especially from Ethical considerations of GenAI.
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