Data Science : Begineer to Advance

Chapters

1Data Science Foundations and Workflow

2Python Programming Essentials for Data Science

3Working with Data Sources and SQL

CSV JSON and Parquet Reading and Writing Data Web Scraping Basics REST APIs and Requests Authentication and Rate Limits Handling Missing and Corrupt Files SQL Basics Select and Joins Aggregations and Window Functions Subqueries and CTEs Indexes and Query Optimization Database Design Basics Transactions and ACID ORMs and Python DB APIs Data Warehouses and Lakes ETL vs ELT Concepts

4Data Wrangling with NumPy and Pandas

5Data Cleaning and Preprocessing

6Exploratory Data Analysis and Visualization

7Probability and Statistics for Data Science

8Machine Learning Foundations

9Supervised Learning Algorithms

10Unsupervised Learning and Dimensionality Reduction

11Model Evaluation, Validation, and Tuning

12Feature Engineering and ML Pipelines

13Time Series Analysis and Forecasting

14Natural Language Processing

15Deep Learning, Deployment, and MLOps

Courses/Data Science : Begineer to Advance/Working with Data Sources and SQL

Working with Data Sources and SQL

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Acquire, access, and manage data from files, web APIs, and relational databases. Write efficient SQL and design robust data access patterns.

Content

15 of 15

ETL vs ELT Concepts

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