Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Subscribe
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
PYTHON: From Basics to Data Analysis (2026)
Hot & New
New
Rating: 5.0 out of 5(31 ratings)
77 students

PYTHON: From Basics to Data Analysis (2026)

PYTHON PROGRAMMING: Master Python Fundamentals, Object-Oriented Concepts, and Essential Data Analysis Libraries
Hot & New
New
Created byPYTHON PROGRAMMING Python Bootcamp: From Fundamentals to Data Analysis
Last updated 4/2026
English

What you'll learn

  • PAY $9.99: Enter the code PYTHON3 and pay the lowest price for the training.
  • Master core Python syntax, data structures, and programming constructs.
  • Understand and implement Object-Oriented Programming (OOP) principles effectively.
  • Utilize key libraries like Pandas and NumPy for efficient data manipulation and numerical computation.
  • Create informative data visualizations using libraries such as Matplotlib.
  • Gain practical experience applying scientific computing concepts with SciPy.
  • Develop problem-solving abilities through structured exercises and project work.
  • Complete a portfolio-ready data analysis project applying learned Python skills.

Course content

4 sections • 47 lectures • 4h 11m total length

  • Download All Files Here0:03
  • Introduction to Python5:51
  • Downloading Python and VScode4:20
  • Algorithms and Programs5:36

    Discover what algorithms are as step-by-step recipes and how programs implement them in code. Summarize key concepts like efficiency, correctness, readability, and scalability with real-world examples.

  • Variables - I4:14
  • Variables - II5:26
  • Variables - III5:36
  • Variables - IV4:22
  • Operators - I3:05
  • Operators - II4:01

    Explain assignment operators like plus equal and chain assignment, and compare values with equal to, not equal to, greater than, and less than across numbers, strings, and objects.

  • Operators - III3:41
  • Strings5:30

    Explore Python strings, learn f-strings for embedding variables, practice string comparisons and templates, and learn about multiline strings, SQL queries inside strings, and function documentation.

  • Conditionals - I6:32

    Explore conditionals in Python by using if and else, compare values with operators, and combine with and, or, not, while understanding truthiness and proper indentation.

  • Conditionals - II5:19

    Explore if-elif-else chains with comparing operators to assign grades from a to f, include nested conditionals, and apply ternary expressions and any and all.

  • Loops - I5:17
  • Loops - II6:15
  • Loops - III6:37
  • Functions - I5:00
  • Functions - II4:51

    Master function parameters and arguments, including positional and keyword arguments, default values, and variable-length inputs with *args and **quarks, and build dictionaries like buildProfile to capture user info.

  • Functions - III2:46

Requirements

  • Basic computer literacy and a genuine interest in learning programming and data analysis concepts.

Description

This comprehensive course provides a structured path to mastering Python programming, starting from the absolute basics and progressing to practical Data Analysis applications.

Over several modules, you will build a solid foundation in programming principles before advancing to more complex topics. The initial lessons cover core Python syntax, including Variables, Operators, Control Flow (Conditionals and Loops), and Functions. You’ll reinforce your knowledge through multi-part lessons with hands-on activities, interactive challenges, and clear examples designed to support consistent learning.

Next, the course moves into Object-Oriented Programming (OOP), introducing essential concepts like Inheritance, Encapsulation, and Polymorphism. These are explored through practical examples and applied in a dedicated OOP Project.

After OOP, you’ll explore Python’s powerful ecosystem for Data Analysis. Dedicated sections cover widely used libraries:

  • Pandas for data manipulation

  • NumPy for numerical computing

  • Matplotlib for visualizations

  • SciPy for scientific calculations

You'll gain hands-on experience with real-world datasets, developing both your technical and analytical thinking.

To conclude the course, you’ll apply everything you've learned in a Capstone Project focused on Exploratory Data Analysis (EDA). Working with the Titanic dataset, you’ll demonstrate your ability to clean, analyze, and visualize data — creating a project you can proudly showcase in your portfolio.


What You'll Gain from This Course:

  • A complete understanding of Python programming, from beginner to intermediate level

  • Practical experience with Object-Oriented Programming (OOP)

  • Hands-on training with essential libraries for data analysis

  • Confidence to manipulate, analyze, and visualize datasets

  • A portfolio-ready final project showcasing your skills in action

  • A strong foundation to pursue data science, automation, or software development

Who this course is for:

  • This course is ideal for beginners with no prior programming experience.
  • It also suits those transitioning into data analysis roles.
  • Students seeking strong Python fundamentals will benefit greatly.
  • Professionals can enhance their toolkit with practical Python skills.

Report abuse