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

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Python for Data Science - Python Programming and Data Analysis (2024) (Size: 2.2 GB)
  1. About your certificate.html 921.6 B
  1. File IO in Python.mp4 69.4 MB
  1. For loops in Python.mp4 76.9 MB
  1. Function in Python.mp4 70.7 MB
  1. Introduction to Matplotlib Library.mp4 39.5 MB
  1. Introduction to NumPy arrays.mp4 60.9 MB
  1. Introduction to Pandas Library.mp4 40.8 MB
  1. Introduction to Python.mp4 37.1 MB
  1. Introduction to Seaborn Library.mp4 71.5 MB
  1. Introduction.mp4 20 MB
  1. List in Python.mp4 75 MB
  1. Python Conditional Expressions.mp4 31.7 MB
  10. Practice Assignment.html 102.4 B
  2. Accessing the elements of NumPy arrays.mp4 33.5 MB
  2. Bonus lecture.html 6.3 KB
  2. Checking Even Numbers Using Functions in Python.html 102.4 B
  2. Conditional Statements in Python.html 102.4 B
  2. Course resources.html 102.4 B
  2. Creating DataFrame from Dictionary in Pandas.html 102.4 B
  2. Data Visualization with Matplotlib Plotting Essentials and Customization.mp4 116.5 MB
  2. Exploring Seaborn Univariate and Bivariate Analysis for Data Visualization.mp4 50.4 MB
  2. First code to Python Programming.html 102.4 B
  2. Generating Square Numbers in Python.html 102.4 B
  2. Working with Lists in Python.html 102.4 B
  2. Writing to a File in Python.html 102.4 B
  3. Advanced Data Visualization with Seaborn Pairplot and Barplot Customization.mp4 88.6 MB
  3. Creating and Accessing Elements in NumPy Arrays.html 102.4 B
  3. Exploring Operators and Conditional Expressions in Python.mp4 79.7 MB
  3. Exploring Series and DataFrame in Python.mp4 47.3 MB
  3. Quiz.html 102.4 B
  3. Recursion in Python.mp4 52.6 MB
  3. Tuples in Python.mp4 41.6 MB
  3. Variables in Python Declaration and Use.mp4 67.5 MB
  3. Visualizing Average Session Length per Day with a Line Chart.html 102.4 B
  3. While loops in Python.mp4 51.6 MB
  4. Advanced Visualizations with Countplot and Heatmap Using Seaborn.mp4 64 MB
  4. Basic Arithmetic Operations in Python.html 102.4 B
  4. Dictionaries in Python.mp4 36.8 MB
  4. Essential Data Analysis Methods in Python.mp4 111.6 MB
  4. Exploring Subplots, Scatter Plots, and Customization.mp4 78.2 MB
  4. Lambda function.mp4 49.5 MB
  4. Leveraging Data Types, Shapes, and Array Stacking in NumPy.mp4 53 MB
  4. Practice Assignment.html 102.4 B
  5. Creating a Scatter Plot of Random Data Points.html 102.4 B
  5. Data types in Python.mp4 38.9 MB
  5. Exploring Diverse Approaches to Creating NumPy Arrays.mp4 42.6 MB
  5. Importing Data from CSV File using Pandas.html 102.4 B
  5. Lambda Functions for Exponentiation.html 102.4 B
  5. Practice Assignment Data Visualization with Seaborn and the Iris Dataset.html 102.4 B
  5. Working with Dictionaries in Python.html 102.4 B
  6. Crafting Bar Plots, Histograms, Pie Charts with Customization Using Matplotlib.mp4 85.9 MB
  6. Creating NumPy Arrays with Evenly Spaced Numbers.html 102.4 B
  6. Missing Data Handling in Python.mp4 109.2 MB
  6. Practice Assignment.html 102.4 B
  6. Python String.mp4 48.2 MB
  6. Sets in Python.mp4 29.9 MB
  7. Manipulating DataFrame in Python.mp4 110.7 MB
  7. Mathematical operations on arrays.mp4 46.1 MB
  7. Practice Assignment Visualizing Olympic Medals Data with Matplotlib.html 102.4 B
  7. Practice Assignment.html 102.4 B
  7. Quiz.html 102.4 B
  8. Array Operations and Median Calculation in Python.html 102.4 B
  8. Practice Assignment Analyzing and Visualizing the Titanic Dataset with Pandas.html 102.4 B
  8. String methods.mp4 82.5 MB
  9. Calculating Body Mass Index (BMI) in Python.html 102.4 B
  9. Practice Assignment.html 102.4 B
  Autoviz-checkpoint.ipynb 102.4 B
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  Housing.csv 29.3 KB
  Housing.xlsx 37.5 KB
  Housing_with_null.csv 29.1 KB
  MatplotLib-checkpoint.ipynb 102.4 B
  Numpy-checkpoint.ipynb 102.4 B
  Numpy.ipynb 53.1 KB
  Pandas-checkpoint.ipynb 102.4 B
  Pandas.ipynb 233.8 KB
  Python_Tutorial-checkpoint.ipynb 120 KB
  Python_Tutorial.ipynb 139.8 KB
  Seaborn-checkpoint.ipynb 102.4 B
  Seaborn.ipynb 2 MB
  example-checkpoint.txt 0 B
  example.txt 0 B
  gemini-checkpoint.ipynb 102.4 B
  ▲ 85 total files

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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