Global Certificate in Fashion Data Analysis Techniques
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โข Data Analysis Fundamentals: Understanding data types, data wrangling, data visualization, and statistical analysis.
โข Fashion Data Acquisition Techniques: Scraping, APIs, and data mining for fashion-related data.
โข Data Cleaning and Preparation: Data validation, missing data imputation, and feature engineering for fashion data.
โข Exploratory Data Analysis (EDA): Descriptive statistics, data distribution, and correlations for fashion data.
โข Predictive Data Analysis: Regression, classification, and time series forecasting for fashion trends.
โข Natural Language Processing (NLP): Text preprocessing, topic modeling, and sentiment analysis for fashion text data.
โข Computer Vision for Fashion: Image processing, object detection, and image classification for fashion images.
โข Machine Learning Operations (MLOps): Model deployment, monitoring, and maintenance for fashion data analysis.
โข Ethics and Bias in Fashion Data Analysis: Understanding and mitigating ethical concerns, biases, and fairness issues in fashion data analysis.
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