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Full Stack AI and Data Science Professional

Chapters

1Foundations of AI and Data Science

2Python for Data and AI

3Math for Machine Learning

4Data Acquisition and Wrangling

Data collection strategies Web scraping APIs and REST JSON and XML handling Data validation Missing data Imbalanced data handling Feature engineering basics Text cleaning Time series preprocessing Image preprocessing Geospatial data basics Data augmentation Anomaly detection prep Data labeling strategies

5SQL and Data Warehousing

6Exploratory Data Analysis and Visualization

7Supervised Learning

8Unsupervised Learning and Recommendation

9Deep Learning and Neural Networks

10NLP and Large Language Models

11MLOps and Model Deployment

12Data Engineering and Cloud Pipelines

Courses/Full Stack AI and Data Science Professional/Data Acquisition and Wrangling

Data Acquisition and Wrangling

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Techniques to gather, validate, clean, and prepare diverse data for modeling.

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Data collection strategies

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