Udemy - Python for Data Analytics - From A to Z Data Analytics

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[ DevCourseWeb.com ] Udemy - Python for Data Analytics - From A to Z Data Analytics
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Before starting to the course
    • 1. Before Starting.html (0.5 KB)
    10. How to build a project by yourself and share it
    • 1. Where to find data.html (0.6 KB)
    • 2. Where to share the projects.html (0.7 KB)
    2. Statistics fundamentals
    • 1. About this section of the course.html (0.4 KB)
    • 10. Simple Linear Regression.mp4 (9.0 MB)
    • 10. Simple Linear Regression.srt (1.8 KB)
    • 11. Statistics Quiz.html (0.2 KB)
    • 2. General Concepts.mp4 (6.0 MB)
    • 2. General Concepts.srt (2.2 KB)
    • 3. Descriptive statistics introduction & Frequency.mp4 (8.3 MB)
    • 3. Descriptive statistics introduction & Frequency.srt (3.1 KB)
    • 4. Mean - Mode - Median.mp4 (6.9 MB)
    • 4. Mean - Mode - Median.srt (3.0 KB)
    • 5. Probability Introduction.mp4 (6.2 MB)
    • 5. Probability Introduction.srt (2.8 KB)
    • 6. Probability Distributions.mp4 (9.4 MB)
    • 6. Probability Distributions.srt (3.6 KB)
    • 7. Conditional Probability & Tree Diagram.mp4 (17.6 MB)
    • 7. Conditional Probability & Tree Diagram.srt (5.5 KB)
    • 8. Inferential Statistics introduction.mp4 (9.4 MB)
    • 8. Inferential Statistics introduction.srt (4.3 KB)
    • 9. Confidence Interval.mp4 (9.1 MB)
    • 9. Confidence Interval.srt (3.4 KB)
    3. Python enviroment will be used in the course
    • 1. Google Colab & Jupyter Notebook.html (0.2 KB)
    4. Python fundamentals
    • 1. Print & Comments.mp4 (6.7 MB)
    • 1. Print & Comments.srt (2.2 KB)
    • 10. Python Quiz.html (0.2 KB)
    • 2. Variables part 1.mp4 (20.7 MB)
    • 2. Variables part 1.srt (3.0 KB)
    • 3. Variables part 2.mp4 (12.9 MB)
    • 3. Variables part 2.srt (1.5 KB)
    • 4. Data Types part 1.mp4 (26.9 MB)
    • 4. Data Types part 1.srt (3.8 KB)
    • 5. Data Types part 2.mp4 (16.7 MB)
    • 5. Data Types part 2.srt (3.0 KB)
    • 6. Operators.mp4 (24.0 MB)
    • 6. Operators.srt (4.7 KB)
    • 7. If Statements.mp4 (15.4 MB)
    • 7. If Statements.srt (3.0 KB)
    • 8. Loops.mp4 (11.8 MB)
    • 8. Loops.srt (3.3 KB)
    • 9. Functions.mp4 (10.9 MB)
    • 9. Functions.srt (2.7 KB)
    5. Pandas
    • 1. Pandas Introduction.mp4 (21.3 MB)
    • 1. Pandas Introduction.srt (7.7 KB)
    • 2. Pandas Coding 1.mp4 (7.5 MB)
    • 2. Pandas Coding 1.srt (1.7 KB)
    • 3. Pandas Coding 2.mp4 (8.9 MB)
    • 3. Pandas Coding 2.srt (1.7 KB)
    • 4. Pandas for time series analysis.mp4 (23.6 MB)
    • 4. Pandas for time series analysis.srt (4.3 KB)
    • 5. Pandas Quiz.html (0.2 KB)
    6. Matplotlib
    • 1. Matplotlib Introduction.mp4 (2.5 MB)
    • 1. Matplotlib Introduction.srt (1.0 KB)
    • 2. Matplotlib Coding.mp4 (10.1 MB)
    • 2. Matplotlib Coding.srt (1.5 KB)
    • 3. Matplotlib Quiz.html (0.2 KB)
    7. Seaborn
    • 1. Visualization of distributions.mp4 (6.5 MB)
    • 1. Visualization of distributions.srt (1.2 KB)
    • 2. Visualization of statistical relationships.mp4 (1.8 MB)
    • 2. Visualization of statistical relationships.srt (0.5 KB)
    • 3. Plotting Categorical Data.mp4 (4.7 MB)
    • 3. Plotting Categorical Data.srt (1.1 KB)
    • 4. Seaborn Quiz.html (0.2 KB)
    8. Project 1
    • 1. Project 1.mp4 (46.8 MB)
    • 1. Project 1.srt (3.5 KB)
    9. Project 2
    • 1. Project 2.mp4 (26.1 MB)
    • 1. Project 2.srt (3.7 KB)
    • Bonus Resources.txt (0.4 KB)

Description

Python for Data Analytics - From A to Z Data Analytics



https://DevCourseWeb.com

Instructors: Onur Baltacı
10 sections • 34 lectures • 1h 52m
Video: MP4 1280x720 44 KHz | English + Sub
Updated 11/2022 | Size: 388 MB

Learn Python for Data Analytics

What you'll learn
Learn how to analyze data
Learn how to build a Data Analytics Project
Learn how to visualize data
Repeat the basics of statistics and python

Requirements
No programming experience needed. We will repeat statistics and python fundamentals together.
Description
This is a data analysis course which we use Python and its libraries in order to clean, analyze and visualize our data. This course is for anyone who is interested in data analytics. You don't need to have any knowledge about python or statistics since we will be repeating these two at the beginning of the course. We will cover python libraries which is designed for data manipulation, data analysis, data visualization. Topics we are going to be covering



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seeders:16
leechers:11
Udemy - Python for Data Analytics - From A to Z Data Analytics
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