Python Data Mastery- From Basics to Advanced Analysis

Python Data Mastery: From Basics to Advanced Analysis, available at $54.99, with 17 lectures, and has 1 subscribers.

You will learn about Foundations of Programming , Setting Up the Environment , Python Basics , Functions and Modules , Data Structures in Python , Introduction to NumPy and Pandas Data Visualization Basics , Advanced Data Visualization with Seaborn , Data Cleaning and Preprocessing , Data Analysis with Pandas , Capstone Project Capstone Project: Applying Python programming and data analysis skills to a real-world project. Presenting findings and insights derived from the analyzed data. Practical Application: The capstone project provides an opportunity for students to apply their skills to a real-world data analysis problem This course is ideal for individuals who are This Course for any one want to learn data analysis field there is no need to any background for this course ,, in this course you will learn in details many things It is particularly useful for This Course for any one want to learn data analysis field there is no need to any background for this course ,, in this course you will learn in details many things.

Enroll now: Python Data Mastery: From Basics to Advanced Analysis

Summary

Title: Python Data Mastery: From Basics to Advanced Analysis

Price: $54.99

Number of Lectures: 17

Number of Published Lectures: 17

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $59.99

Quality Status: approved

Status: Live

What You Will Learn

Foundations of Programming , Setting Up the Environment , Python Basics , Functions and Modules , Data Structures in Python , Introduction to NumPy and Pandas

Data Visualization Basics , Advanced Data Visualization with Seaborn , Data Cleaning and Preprocessing , Data Analysis with Pandas , Capstone Project

Capstone Project: Applying Python programming and data analysis skills to a real-world project. Presenting findings and insights derived from the analyzed data.

Practical Application: The capstone project provides an opportunity for students to apply their skills to a real-world data analysis problem

Who Should Attend

This Course for any one want to learn data analysis field there is no need to any background for this course ,, in this course you will learn in details many things

Target Audiences

This Course for any one want to learn data analysis field there is no need to any background for this course ,, in this course you will learn in details many things

In the “Python for Data Analysis” course, students will acquire a comprehensive set of skills and knowledge that empowers them to effectively use Python for analyzing and manipulating data. The course covers a wide range of topics to ensure a well-rounded understanding, from foundational programming concepts to advanced data analysis techniques. Here’s an overview of what students will learn:

Module 1: Introduction to Python Programming

1. Foundations of Programming:

2. Understanding basic programming concepts.

3. Exploring the Python programming language.

4. Setting Up the Environment:

5. Installing and configuring Python and an integrated development environment (IDE).

6. Python Basics:

7. Mastering Python syntax, variables, and data types.

8. Implementing control flow through if statements and loops.

9. Functions and Modules:

10. Writing functions for code modularity.

11. Exploring Python modules and libraries.

Module 2: Data Handling in Python

5. Data Structures in Python:

6. Working with lists, dictionaries, and tuples.

7. Understanding their use in data handling.

8. Introduction to NumPy and Pandas:

9. Using NumPy arrays for numerical operations.

10. Exploring Pandas for data manipulation with DataFrames.

Module 3: Data Visualization with Matplotlib and Seaborn

8. Data Visualization Basics:

9. Understanding the importance of visualizing data.

10. Creating basic plots using Matplotlib.

11. Advanced Data Visualization with Seaborn:

12. Enhancing visualizations with Seaborn.

13. Creating informative and aesthetic charts and graphs.

Module 4: Introduction to Data Analysis with Pandas and NumPy

10. Data Cleaning and Preprocessing:

11. Handling missing data and outliers.

12. Transforming and cleaning data for analysis.

13. Data Analysis with Pandas:

14. Performing basic data analysis tasks using Pandas DataFrames.

15. Aggregating, grouping, and filtering data.

Module 5: Capstone Project: Data Analysis with Python

13. Capstone Project:

14. Applying Python programming and data analysis skills to a real-world project.

15. Presenting findings and insights derived from the analyzed data.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Python Basics (Variables , List , Set , IF Else Condition , For .. While Loops)

Lecture 1: Define Variables

Lecture 2: Define Lists , Sets

Lecture 3: Python_Lesson3(Control Flow IF .. ELSE Statement)

Lecture 4: Python_Lesson4(Control Flow Part2)

Lecture 5: Python_Lesson5(Loops)

Chapter 3: Python_Function

Lecture 1: Python_Function

Chapter 4: Python Libraries (Numpy Library)

Lecture 1: Python_Lesson7(Numpy Part1)

Lecture 2: Python_Lesson8(Numpy Part2)

Lecture 3: Python_Lesson9(Numpy Part3)

Chapter 5: Python Libraries (Pandas Library)

Lecture 1: Python_Lesson10(Pandas Part1)

Lecture 2: Python_Lesson11(Pandas Part2)

Lecture 3: Python_Lesson12(Pandas Part3)

Chapter 6: Python Real Projects

Lecture 1: Python_Lesson13(Real Projects)

Lecture 2: Python_Lesson14(Real Projects)

Lecture 3: Python_Lesson15(Real Projects)

Lecture 4: Python_Lesson16(Real Projects)

Instructors

Nourhan Sarhan
Data Analysis Instructor

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