Data Processing and Optimization with Generative AI

Overview

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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. Upon completion of this course, you'll be able to: Generate synthetic data using generative AI models Implement advanced data cleaning techniques with AI assistance Optimize datasets for improved analysis efficiency Apply ethical considerations in data processing and synthetic data generation

Syllabus

Synthetic data generation

Explain the process of generating synthetic data using generative AI, identifying its applications and potential benefits in addressing data limitation

Advanced data cleaning techniques

Apply generative AI tools to identify and resolve complex data quality issues, such as outliers, inconsistencies, and errors,ensuring data integrity for accurate analysis.

Dataset preparation

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

Datasets optimization

Describe the key components of a well-structured dataset and the role of generative AI in enhancing data quality for analysis

Ethical considerations in data processing

Evaluate the ethical implications of data processing and synthetic data generation, developing strategies to mitigate biases and ensure responsible and transparent data practices.