Curriculum
Data Analysis in Python and AI (Urdu medium) Recorded
Module 1: Introduction to Python and Anaconda
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Module 1.1: Introduction to Python and Anaconda
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Module 1.2: Introduction to Jupyter Notebook, Working Directory, and Python PackagesPreview
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Module 1.3:How to Import an Excel File in Jupyter Notebook (Python)
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Module 1.4:Import Excel in Python and Make a Seaborn Scatter Plot
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Module 1.5: Import Multiple Sheets from One Excel File and Create Bar, Box, Line & Violin Plots
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Module 1.6: Using ChatGPT to Generate Python Scripts (Best Practice Workflow)
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Module 1.7: PCA, Heatmap, Dendrogram & Chord Diagram in Python: Data Import → Explore → Visualize
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Assignment Task 1
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Assignment task 2
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Assignment Task 3
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Module 1.8: create Study area map in python
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Module 1.9: Study area map with pie plots or % values
Module 2: Descriptive statistics in python
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Module 3: T Test, why do we perofrm t test types of t test
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Module 4: ANOVA in Python: From Basics to All Major Types
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Module 5: Regression in Python: Learn All Major Types with Simple Examples
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Video lesson
Module 1.2: Introduction to Jupyter Notebook, Working Directory, and Python Packages
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✅ In this lesson, you will:
Understand Jupyter Notebook:
What it is
How code and markdown cells work
How to run and save notebooks
Work with the file system:
Check your current working directory using
os.getcwd()Change the directory using
os.chdir()
Install and import Python packages:
Use
!pip installto install packagesUse
importto load them
Practice with essential Python packages:
Package Purpose osFile & directory handling sysSystem-specific info numpyNumerical operations pandasData loading & manipulation matplotlibBasic plotting seabornStatistical data visualization