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This course is designed to provide learners with the fundamental skills needed for data engineering using Python. The objective is to introduce anyone interested in the topic to Python's data engineering-related features.

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Python for Data Engineering Course

01: Python Basics

02: Data Manipulation, Analysis and Visualization

04: Web Scraping and APIs

05: Working with Data Sources, Storages, and Serialization

06: Object-Oriented Programming

07: SQL & NoSQL Databases with Python

Working with SQL Databases

  • Introduction to SQL and relational databases
  • SQL basics (SELECT, FROM, WHERE, JOIN)
  • Creating and managing databases, tables, and indexes
  • CRUD operations (Create, Read, Update, Delete)
  • Connecting to databases
  • Executing SQL queries
  • Fetching and manipulating data with SQL
  • Using SQLAlchemy for database interaction

Working with NoSQL Databases

  • Understanding NoSQL databases (e.g., MongoDB, Redis)
  • Connecting to NoSQL databases
  • Querying and manipulating data in NoSQL databases
  • Handling document-based and key-value data models

Assignment: Ass7

08: Building Data Pipelines

Data Pipelines

  • ETL (Extract, Transform, Load)
  • Understanding data pipelines and their components
  • Designing and architecting data pipelines
  • Implementing data ingestion, transformation, and loading (ETL)

Assignment: Ass8

Capstone Project

Project Development

  • Apply all the concepts learned in a real-world data engineering project
  • Work with various data sources including web data and APIs
  • Implement ETL pipelines, data processing, and analysis using Python libraries and tools

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This course is designed to provide learners with the fundamental skills needed for data engineering using Python. The objective is to introduce anyone interested in the topic to Python's data engineering-related features.

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