Python Project for Data Engineering

Python Project for Data Engineering

This course is part of multiple programs.

Instructors: Ramesh Sannareddy

What you'll learn

Demonstrate your skills in Python for working with and manipulating data
Implement webscraping and use APIs to extract data with Python
Play the role of a Data Engineer working on a real project to extract, transform, and load data
Use Jupyter notebooks and IDEs to complete your project

Details to know

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Assessments

4 assignments

Taught in English

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There are 3 modules in this course

Showcase your Python skills in this Data Engineering Project! This short course is designed to apply your basic Python skills through the implementation of various techniques for gathering and manipulating data.

You will take on the role of a Data Engineer by extracting data from multiple sources, and converting the data into specific formats and making it ready for loading into a database for analysis. You will also demonstrate your knowledge of web scraping and utilizing APIs to extract data. By the end of this hands-on project, you will have shown your proficiency with important skills to Extract Transform and Load (ETL) data using an IDE, and of course, Python Programming. Upon completion of this course, you will also have a great new addition to your portfolio! PRE-REQUISITE: **Python for Data Science, AI and Development** course from IBM is a pre-requisite for this project course. Please ensure that before taking this course you have either completed the Python for Data Science, AI and Development course from IBM or have equivalent proficiency in working with Python and data. NOTE: This course is not intended to teach you Python and does not have too much new instructional content. It is intended for you to mostly apply prior Python knowledge.

Module 1 introduces you to Extract, Transform, and Load operations basics. You will learn to extract required information from web pages using web scraping techniques and APIs. You will also access databases using Python and save the processed information as a table in a database.

What's included

5 videos3 readings2 assignments4 app items1 plugin

5 videosTotal 25 minutes

Course Introduction3 minutesPreview module
Demo: Working with an IDE 5 minutes
Extract, Transform, Load (ETL)6 minutes
(Optional) Web Scraping 4 minutes
[Optional] REST APIs & HTTP Requests4 minutes

3 readingsTotal 13 minutes

Helpful Tips for Course Completion2 minutes
Pre-requisites and Course Syllabus10 minutes
Module Summary: Extract, Transform, Load (ETL)1 minute

2 assignmentsTotal 25 minutes

Graded Quiz: Extract, Transform, Load (ETL)15 minutes
Practice Quiz: Extract, Transform, Load (ETL)10 minutes

4 app itemsTotal 120 minutes

Hands-on Lab: Getting Started with IDE 15 minutes
Hands-on Lab: Extract, Transform, Load (ETL)30 minutes
Hands-on Lab: Web scraping and Extracting Data using APIs45 minutes
Hands-on Lab: Accessing Databases using Python script30 minutes

1 pluginTotal 5 minutes

Reading: Querying SQLite3 database5 minutes

In this lesson, you will complete two projects, one for practice and one for assessment to apply what you’ve learned. These projects have you implement your skills learned in the previous course and the last module regarding the Extract, Transform, and Load process using web scraping and accessing databases using REST APIs and Python.

What's included

2 readings1 assignment1 peer review2 app items2 plugins

2 readingsTotal 15 minutes

Congratulations and Next Steps10 minutes
Thanks from the Course Team5 minutes

1 assignmentTotal 15 minutes

Graded Quiz: Final Project 15 minutes

1 peer reviewTotal 60 minutes

Submit your work and grade your peers60 minutes

2 app itemsTotal 120 minutes

Practice Project: Extract, Transform and Load GDP data60 minutes
Final Project: Acquiring and processing information on world's largest banks60 minutes

2 pluginsTotal 10 minutes

Practice Project Overview5 minutes
Final Project Overview5 minutes

In this bonus module, you will become familiar with the best practices for coding as documented in the Python Enhancement Proposal (PEP8) style guide. You will learn about static code analysis, ensuring that your code adheres to the coding rules. Next, you will learn how to create and run unit tests. Finally, you will learn how to create, verify, and run Python packages.