Complete Guide to Python for Data Engineering: From Beginner to Advanced

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Deepak Goyal

5:26:21

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01 - Introduction

01 - Welcome to the course.mp4

00:34

02 - What you should know.mp4

01:22

03 - CoderPad tour.mp4

02:02

02 - 1. Python Basics

01 - Introduction to Python and data engineering.mp4

03:06

02 - Setting up your Python environment.mp4

03:09

03 - Explore the Google Colab worksheet.mp4

04:26

04 - Variables and data types.mp4

05:19

05 - Operators and expressions.mp4

07:07

06 - Control structures.mp4

06:58

07 - Functions.mp4

06:45

08 - Modules and packages.mp4

05:09

09 - String manipulation.mp4

08:12

10 - Error handling.mp4

05:25

11 - Solution Conditions.mp4

01:18

03 - 2. Python Collections

01 - Collection overview.mp4

02:21

02 - Python collections Tuples.mp4

06:05

03 - Python collections Lists.mp4

05:28

04 - Python collections Sets.mp4

04:40

05 - Python collections Dictionaries.mp4

07:42

06 - Solution Collections.mp4

01:04

04 - 3. Python File Handling

01 - File IO overview.mp4

02:21

02 - Working with CSV files.mp4

06:00

03 - Working with JSON files.mp4

05:06

04 - Solution File handling.mp4

02:44

05 - 4. pandas DataFrame API

01 - Introduction to pandas.mp4

03:22

02 - Read files as DataFrames.mp4

05:45

03 - Data cleaning and preprocessing.mp4

07:15

04 - Data manipulation and aggregation.mp4

06:46

05 - Data visualization.mp4

06:13

06 - Write a DataFrame to a file.mp4

04:26

07 - Solution pandas.mp4

01:36

06 - 5. NumPy

01 - Introduction to NumPy.mp4

03:11

02 - Array creation and attributes.mp4

06:38

03 - Array operations.mp4

07:06

04 - Indexing and slicing.mp4

08:21

05 - Linear algebra and statistics.mp4

05:48

06 - Write a NumPy array to a file.mp4

04:37

07 - Solution NumPy.mp4

01:38

07 - 6. OOP with Python

01 - Understanding classes and objects.mp4

01:48

02 - Implementation Classes and objects in Python.mp4

03:45

03 - Understand OOP features Abstraction, inheritance, and more.mp4

03:02

04 - Solution OOP.mp4

02:31

08 - 7. Advanced Data Engineering

01 - Tips to write efficient Python code.mp4

03:25

02 - What is ETL in the data engineering world.mp4

03:27

03 - Understand PySpark for data engineering.mp4

04:01

04 - What is Hadoop.mp4

02:50

05 - Importance of visualization tools in data engineering.mp4

03:39

06 - On-premises vs. cloud data engineering.mp4

03:32

09 - 8. Web Scraping with Python

01 - HTML basics.mp4

07:00

02 - HTML parents, children, and descendants.mp4

06:16

03 - Understand web scraping.mp4

08:12

04 - BeautifulSoup basics.mp4

06:57

05 - Installing BeautifulSoup.mp4

04:11

06 - Get HTML from a web page.mp4

05:29

07 - Scrape the web page.mp4

07:30

08 - Export data as a TXT file.mp4

04:37

10 - 9. Advanced Built-in Functions

01 - Generators in Python.mp4

04:00

02 - Python generator classes and iterators.mp4

11:23

03 - Iterables in Python.mp4

06:15

04 - filter() and map() functions.mp4

05:48

05 - any() and all() functions in Python.mp4

03:54

11 - 10. Logging in Python

01 - What is logging.mp4

04:39

02 - Custom logging.mp4

04:49

03 - Logging best practices.mp4

04:35

12 - 11. Capstone Project

01 - Capstone Project Retail sales analysis.mp4

03:23

02 - Solution Capstone project.mp4

17:27

13 - Conclusion

01 - Next steps.mp4

00:51

Description

Get up and running with the basics of Python before progressing to more advanced topics specific to data engineering. In this hands-on, interactive course, join instructor Deepak Goyal to practice performing a wide range of data engineering tasks in Python to boost your technical know-how, prepare for an interview, or land a new role. This course includes Code Challenges powered by CoderPad. Code Challenges are interactive coding exercises with real-time feedback, so you can get hands-on coding practice to advance your coding skills. Deepak helps you boost your skills as a Python programmer with six specific coding challenges. Explore language basics, Python collections, file handling, Pandas, NumPy, OOP, and advanced data engineering tools that use Python. The course ends with a capstone project focused on retail sales analysis.

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Deepak Goyal

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