Python
Topics for this course
Python
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10:21
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Variables in Python
12:41 -
Data types in Python
00:00 -
Python String
10:21 -
String Methods
13:16 -
List in Python
16:11 -
Tuples in Python
09:23 -
Dictionaries in Python
06:40 -
Sets in Python
06:43 -
Python Conditional Expression
06:09 -
Exploring Operators and Conditional Expressions in Python
14:24 -
For loops in Python
17:15 -
Function in Python
12:54 -
While loops in Python
11:04 -
Recursion in Python
10:41 -
Lambda function
00:00 -
File IO in Python
13:21 -
Introduction to NumPy arrays
10:03 -
Accessing the element of array
08:22 -
Leveraging Data Types, Shapes, and Array Stacking in NumPy
12:33 -
Exploring Diverse Approaches to Creating NumPy Arrays
08:12 -
Mathematical operations on arrays
08:47 -
Introduction to Pandas Library
04:57 -
Exploring Series and DataFrame in Python
08:07 -
Essential Data Analysis Methods in Python
14:23 -
Missing Data Handling in Python
12:53 -
Manipulating DataFrame in Python
17:30 -
Introduction to Matplotlib Library
05:59 -
Data Visualization with Matplotlib Plotting Essentials and Customization
16:42 -
Exploring Subplots, Scatter Plots, and Customization
12:14 -
Crafting Bar Plots, Histograms, Pie Charts with Customization Using Matplotlib
13:58 -
Introduction to Seaborn Library
09:38 -
Exploring Seaborn Univariate and Bivariate Analysis for Data Visualization
08:41 -
Advanced Data Visualization with Seaborn Pairplot and Barplot Customization
12:49 -
Advanced Visualizations with Countplot and Heatmap Using Seaborn
08:38 -
Python Quiz
Description
This Python programming course provides a complete foundation from core concepts to data analysis and visualization. Learners begin with Python basics such as variables, data types, strings, collections, loops, functions, and file handling. The course then introduces powerful libraries including NumPy for numerical computing, Pandas for data manipulation and analysis, and Matplotlib and Seaborn for data visualization. Through hands-on examples, learners gain practical skills in data handling, analysis, and visual storytelling. By the end of the course, students will be able to write efficient Python programs and analyze real-world data confidently.
