Udemy - Master Python for Data Analysis - Build Job-Ready Skills

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size706.3 MB
  • Uploaded Byfreecoursewb
  • Downloads125
  • Last checkedMay. 03rd '26
  • Date uploadedMay. 02nd '26
  • Seeders 24
  • Leechers9

Infohash : C9A8C624021E834372EDFD61A7BAED04045ED523

Master Python for Data Analysis: Build Job-Ready Skills

https://WebToolTip.com

Published 4/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 20m | Size: 706.34 MB

Lean Python by solving real data problems. Clean, analyze, and visualize data to land a data analyst job.

What you'll learn
Master core Python programming to confidently write clean and efficient code.
Clean and format messy, real-world datasets for accurate business analysis.
Use Pandas to filter, merge, and manipulate data like a professional analyst.
Calculate key business metrics and group data to extract actionable insights.
Build clear data visualizations to uncover trends and communicate results.

Requirements
No prior programming or data analysis experience required. You will learn everything from scratch
A computer with internet access. We use Google Colab, so no complex software installation is needed.

Files:

[ WebToolTip.com ] Udemy - Master Python for Data Analysis - Build Job-Ready Skills
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1 - Course Introduction
    • 1. Course Overview & Learning Objectives (Description).html (0.9 KB)
    • 1. Course Overview & Learning Objectives.mp4 (30.9 MB)
    • 2. Real-World Applications of Python in Data (Description).html (0.9 KB)
    • 2. Real-World Applications of Python in Data.mp4 (24.3 MB)
    2 - Python Basics
    • 3. 3. Google Colab.url (0.1 KB)
    • 3. Understanding Variables and Core Data Types (Description).html (1.0 KB)
    • 3. Understanding Variables and Core Data Types.mp4 (17.7 MB)
    • 4. Working with Arithmetic Operators (Description).html (0.9 KB)
    • 4. Working with Arithmetic Operators.mp4 (12.7 MB)
    • 5. Mastering Logical Operators (Description).html (0.9 KB)
    • 5. Mastering Logical Operators.mp4 (14.0 MB)
    3 - Working with Data Structures
    • 6. Introduction to Python Lists (Description).html (0.9 KB)
    • 6. Introduction to Python Lists.mp4 (15.5 MB)
    • 7. Managing Data with Tuples (Description).html (0.9 KB)
    • 7. Managing Data with Tuples.mp4 (9.1 MB)
    • 8. Utilizing Sets in Python (Description).html (0.9 KB)
    • 8. Utilizing Sets in Python.mp4 (10.0 MB)
    • 9. Structuring Data with Dictionaries (Description).html (1.0 KB)
    • 9. Structuring Data with Dictionaries.mp4 (45.6 MB)
    4 - Control Structures in Python
    • 10. Using If Statements for Conditional Logic (Description).html (1.0 KB)
    • 10. Using If Statements for Conditional Logic.mp4 (14.8 MB)
    • 11. Iterating Data with For Loops (Description).html (1.0 KB)
    • 11. Iterating Data with For Loops.mp4 (13.9 MB)
    • 12. While Loops and Loop Control Statements (Description).html (1.0 KB)
    • 12. While Loops and Loop Control Statements.mp4 (13.9 MB)
    5 - Data Analysis with Python
    • 13. The Data Analyst's Workflow in Python (Description).html (1.0 KB)
    • 13. The Data Analyst's Workflow in Python.mp4 (14.2 MB)
    • 14. Fundamentals of Data Manipulation (Description).html (1.0 KB)
    • 14. Fundamentals of Data Manipulation.mp4 (34.4 MB)
    • 15. 15. ecommerce_sales.csv (101.6 KB)
    • 15. Importing Datasets with Pandas (Description).html (0.9 KB)
    • 15. Importing Datasets with Pandas.mp4 (34.5 MB)
    • 16. Exploring and Profiling Your Data (Description).html (1.0 KB)
    • 16. Exploring and Profiling Your Data.mp4 (55.2 MB)
    • 17. Data Slicing Selecting Rows and Columns (Description).html (1.0 KB)
    • 17. Data Slicing Selecting Rows and Columns.mp4 (44.6 MB)
    • 18. Filtering and Sorting Datasets (Description).html (1.0 KB)
    • 18. Filtering and Sorting Datasets.mp4 (34.8 MB)
    • 19. Data Cleaning and Preprocessing Techniques (Description).html (1.0 KB)
    • 19. Data Cleaning and Preprocessing Techniques.mp4 (56.8 MB)
    • 20. Feature Engineering Creating New Columns (Description).html (1.0 KB)
    • 20. Feature Engineering Creating New Columns.mp4 (62.1 MB)
    • 21. Data Aggregation for Business Insights (Description).html (1.0 KB)
    • 21. Data Aggregation for Business Insights.mp4 (40.9 MB)
    • 22. 22. ecommerce_clean.csv (95.6 KB)
    • 22. 22. ecommerce_customers.csv (7.9 KB)
    • 22. Combining and Merging Datasets (Description).html (1.0 KB)
    • 22. Combining and Merging Datasets.mp4 (53.7 MB)
    • 23. Visualizing Data for Business Impact (Description).html (1.1 KB)
    • 23. Visualizing Data for Business Impact.mp4 (52.5 MB)
    • Bonus Resources.txt (0.1 KB)

Code:

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