Python for Data Science - Python Programming and Data Analysis (2024)

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[ CourseWikia.com ] Python for Data Science - Python Programming and Data Analysis (2024)
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction.mp4 (20.0 MB)
    • 2. Course resources.html (0.1 KB)
      • Python training
      • Housing.csv (29.3 KB)
      • Housing.xlsx (37.5 KB)
      • Housing_with_null.csv (29.1 KB)
      • MatplotLib.ipynb (1,003.8 KB)
      • Numpy.ipynb (53.1 KB)
      • Pandas.ipynb (233.8 KB)
      • Python_Tutorial.ipynb (139.8 KB)
      • Seaborn.ipynb (2.0 MB)
      • example.txt (0.0 KB)
        • ipynb_checkpoints
        • Autoviz-checkpoint.ipynb (0.1 KB)
        • MatplotLib-checkpoint.ipynb (0.1 KB)
        • Numpy-checkpoint.ipynb (0.1 KB)
        • Pandas-checkpoint.ipynb (0.1 KB)
        • Python_Tutorial-checkpoint.ipynb (120.0 KB)
        • Seaborn-checkpoint.ipynb (0.1 KB)
        • example-checkpoint.txt (0.0 KB)
        • gemini-checkpoint.ipynb (0.1 KB)
        10. Matplotlib Library
        • 1. Introduction to Matplotlib Library.mp4 (39.5 MB)
        • 2. Data Visualization with Matplotlib Plotting Essentials and Customization.mp4 (116.5 MB)
        • 3. Visualizing Average Session Length per Day with a Line Chart.html (0.1 KB)
        • 4. Exploring Subplots, Scatter Plots, and Customization.mp4 (78.2 MB)
        • 5. Creating a Scatter Plot of Random Data Points.html (0.1 KB)
        • 6. Crafting Bar Plots, Histograms, Pie Charts with Customization Using Matplotlib.mp4 (85.9 MB)
        • 7. Practice Assignment Visualizing Olympic Medals Data with Matplotlib.html (0.1 KB)
        11. Seaborn Library
        • 1. Introduction to Seaborn Library.mp4 (71.5 MB)
        • 2. Exploring Seaborn Univariate and Bivariate Analysis for Data Visualization.mp4 (50.4 MB)
        • 3. Advanced Data Visualization with Seaborn Pairplot and Barplot Customization.mp4 (88.6 MB)
        • 4. Advanced Visualizations with Countplot and Heatmap Using Seaborn.mp4 (64.0 MB)
        • 5. Practice Assignment Data Visualization with Seaborn and the Iris Dataset.html (0.1 KB)
        12. Conclusion
        • 1. About your certificate.html (0.9 KB)
        • 2. Bonus lecture.html (6.3 KB)
        2. Getting Started with Python
        • 1. Introduction to Python.mp4 (37.1 MB)
        • 10. Practice Assignment.html (0.1 KB)
        • 2. First code to Python Programming.html (0.1 KB)
        • 3. Variables in Python Declaration and Use.mp4 (67.5 MB)
        • 4. Basic Arithmetic Operations in Python.html (0.1 KB)
        • 5. Data types in Python.mp4 (38.9 MB)
        • 6. Python String.mp4 (48.2 MB)
        • 7. Quiz.html (0.1 KB)
        • 8. String methods.mp4 (82.5 MB)
        • 9. Calculating Body Mass Index (BMI) in Python.html (0.1 KB)
        3. Data Structures in Python
        • 1. List in Python.mp4 (75.0 MB)
        • 2. Working with Lists in Python.html (0.1 KB)
        • 3. Tuples in Python.mp4 (41.6 MB)
        • 4. Dictionaries in Python.mp4 (36.8 MB)
        • 5. Working with Dictionaries in Python.html (0.1 KB)
        • 6. Sets in Python.mp4 (29.9 MB)
        • 7. Practice Assignment.html (0.1 KB)
        4. Conditional Statements in Python
        • 1. Python Conditional Expressions.mp4 (31.7 MB)
        • 2. Conditional Statements in Python.html (0.1 KB)
        • 3. Exploring Operators and Conditional Expressions in Python.mp4 (79.7 MB)
        • 4. Practice Assignment.html (0.1 KB)
        5. Loops in Python
        • 1. For loops in Python.mp4 (76.9 MB)
        • 2. Generating Square Numbers in Python.html (0.1 KB)
        • 3. While loops in Python.mp4 (51.6 MB)
        • 4. Practice Assignment.html (0.1 KB)
        6. Python Functions
        • 1. Function in Python.mp4 (70.7 MB)
        • 2. Checking Even Numbers Using Functions in Python.html (0.1 KB)
        • 3. Recursion in Python.mp4 (52.6 MB)
        • 4. Lambda function.mp4 (49.5 MB)
        • 5. Lambda Functions for Exponentiation.html (0.1 KB)
        • 6. Practice Assignment.html (0.1 KB)
        7. File handling in Python
        • 1. File IO in Python.mp4 (69.4 MB)
        • 2. Writing to a File in Python.html (0.1 KB)
        • 3. Quiz.html (0.1 KB)
        8. NumPy Library
        • 1. Introduction to NumPy arrays.mp4 (60.9 MB)
        • 2. Accessing the elements of NumPy arrays.mp4 (33.5 MB)
        • 3. Creating and Accessing Elements in NumPy Arrays.html (0.1 KB)
        • 4. Leveraging Data Types, Shapes, and Array Stacking in NumPy.mp4 (53.0 MB)
        • 5. Exploring Diverse Approaches to Creating NumPy Arrays.mp4 (42.6 MB)
        • 6. Creating NumPy Arrays with Evenly Spaced Numbers.html (0.1 KB)
        • 7. Mathematical operations on arrays.mp4 (46.1 MB)
        • 8. Array Operations and Median Calculation in Python.html (0.1 KB)
        • 9. Practice Assignment.html (0.1 KB)
        9. Pandas Library
        • 1. Introduction to Pandas Library.mp4 (40.8 MB)
        • 2. Creating DataFrame from Dictionary in Pandas.html (0.1 KB)
        • 3. Exploring Series and DataFrame in Python.mp4 (47.3 MB)
        • 4. Essential Data Analysis Methods in Python.mp4 (111.6 MB)
        • 5. Importing Data from CSV File using Pandas.html (0.1 KB)
        • 6. Missing Data Handling in Python.mp4 (109.2 MB)
        • 7. Manipulating DataFrame in Python.mp4 (110.7 MB)
        • 8. Practice Assignment Analyzing and Visualizing the Titanic Dataset with Pandas.html (0.1 KB)
        • Bonus Resources.txt (0.4 KB)

Description

Python for Data Science: Python Programming & Data Analysis (2024)

https://CourseWikia.com

Published 5/2024
Created by Start-Tech Trainings,Start-Tech Academy
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 39 Lectures ( 6h 5m ) | Size: 2.15 GB

Transform data into insights using Python and its powerful Libraries such as Numpy, Pandas, MatplotLib, Seaborn etc.

What you'll learn:
Gain a thorough understanding of Python syntax, script writing, and fundamental programming concepts such as variables, data types, and string operations
Become adept at using lists, dictionaries, tuples, and sets for organizing and managing data effectively within Python
Master the use of conditional statements and loops in Python to automate and optimize data processing tasks
Learn to design reusable Python functions to perform repetitive tasks efficiently, including knowledge of recursion and lambda functions
Acquire skills in reading from and writing to files in Python, crucial for data processing tasks in real-world applications
Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance
Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format for analysis
Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python

Requirements:
No prior experience in Python or data analysis is required; just basic computer skills and access to a computer with an internet connection are necessary to start this course.



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Python for Data Science - Python Programming and Data Analysis (2024)

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2.2 GB
seeders:31
leechers:16
Python for Data Science - Python Programming and Data Analysis (2024)

Torrent hash: 151EFBEA7BCC6E2A6879AC73C8CF06EA492F577B