Python for Data Science

Level up in Data Science using Python, master Numpy, Pandas, Data Visualisation, Web Scraping, Automation, SQL and more.
4.48 (864 reviews)
Udemy
platform
English
language
Data Science
category
instructor
Python for Data Science
5 964
students
22.5 hours
content
Oct 2024
last update
$69.99
regular price

What you will learn

Python fundamentals for beginners!

Learn to use Python for Data Science

Data Acquistion using Beautiful Soup, Scrapy

Automation using Selenium

Data Analysis using Numpy, Pandas, SQL

Data Visualisation using Seaborn, Matplotlib

Introduction to Machine Learning

Building 5 projects using data science concepts

Course Gallery

Python for Data Science – Screenshot 1
Screenshot 1Python for Data Science
Python for Data Science – Screenshot 2
Screenshot 2Python for Data Science
Python for Data Science – Screenshot 3
Screenshot 3Python for Data Science
Python for Data Science – Screenshot 4
Screenshot 4Python for Data Science

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Comidoc Review

Our Verdict

This 22.5-hour course serves as a one-stop solution for learning Python fundamentals, data analysis, visualization, web scraping, automation, and SQL from the ground up. While certain software versions are outdated causing discrepancies, the majority of modules cover key concepts thoroughly with challenging labs that build on top of each other. However, be prepared to encounter repetitive, typo-ridden quiz questions and a limited number of labs in some areas. With that said, this course is still an excellent starting point for those new to programming or data science.

What We Liked

  • Comprehensive coverage of Python for Data Science
  • Logical sequence of topics with challenging labs
  • In-depth exploration of various data science tools like Numpy, Pandas, SQL
  • Excellent explanation of complex concepts
  • Highly recommended for beginners in programming and data science

Potential Drawbacks

  • Outdated software versions causing inconsistencies
  • Limited labs on certain modules
  • Quiz questions with occasional repetition, typos, and errors
3557793
udemy ID
09/10/2020
course created date
10/06/2021
course indexed date
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