Data Processing and Optimization with Generative AI

Microsoft via Coursera

Coursera based on 14 ratings

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Overview

"Data Processing and Optimization with Generative AI" is a comprehensive course designed to equip learners with the knowledge and skills to leverage generative AI for efficient data handling and optimization tasks. As businesses increasingly rely on massive datasets to drive decisions, understanding how to streamline and enhance data workflows using AI becomes critical. This course delves into how generative AI models can be applied to automate data cleaning, transformation, synthesis, and augmentation. Participants will learn techniques to process structured and unstructured...

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.