Udemy - Python Data Analysis Bootcamp for Beginners - All in One

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[ DevCourseWeb.com ] Udemy - Python Data Analysis Bootcamp for Beginners - All in One
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Setting Up Your Data Analysis Environment
    • 1. Installing Python and Jupyter Notebook.html (0.2 KB)
    • 1.1 Mac.pdf (1.5 MB)
    • 1.2 Windows.pdf (929.7 KB)
    • 2. Setting Up The AI Environment ChatGPT.html (0.1 KB)
    • 2.1 Instructions of setting up ChatGPT.pdf (409.1 KB)
    10. Statistical Analysis and Hypothesis Testing
    • 1. One sample T-test.mp4 (70.2 MB)
    • 2. Independent sample T-test.mp4 (57.3 MB)
    • 3. One way analysis of variance (ANOVA).mp4 (67.3 MB)
    • 4. Chi-square test for independence.mp4 (83.6 MB)
    • 5. Pearson correlation analysis.mp4 (82.5 MB)
    • 6. Linear regression analysis.mp4 (103.8 MB)
    • 7. Hypothesis Testing and Analysis.html (0.2 KB)
    11. Understanding Python Errors
    • 1. Module not found error.mp4 (8.6 MB)
    • 2. Syntax error.mp4 (9.5 MB)
    • 3. Key error.mp4 (7.4 MB)
    • 4. Index error.mp4 (6.9 MB)
    • 5. Attribute error.mp4 (8.6 MB)
    • 6. Value error.mp4 (7.8 MB)
    • 7. Type error.mp4 (8.3 MB)
    12. Handling Errors in Python
    • 1. Debugging errors in seconds.mp4 (22.9 MB)
    • 2. Enhancing python codes.mp4 (26.0 MB)
    2. Python Programming Fundamentals - Level 1
    • 1. Why Python.mp4 (32.5 MB)
    • 2. Your First Python Code Getting Started.mp4 (14.5 MB)
    • 3. Variables and naming conventions.mp4 (28.1 MB)
    • 4. Data types integers, float, strings, boolean.mp4 (28.9 MB)
    • 5. Type conversion and casting.mp4 (46.6 MB)
    • 6. Arithmetic operators (+, -, , , %, ).mp4 (32.6 MB)
    • 7. Comparison operators (, =, =, ==, !=).mp4 (35.3 MB)
    • 8. Logical operators (and, or, not).mp4 (32.1 MB)
    • 9. Python Programming Basics – Level 1.html (0.2 KB)
    3. Python Programming Fundamentals - Level 2
    • 1. Lists creation, indexing, slicing, modifying.mp4 (73.6 MB)
    • 2. Sets unique elements, operations.mp4 (38.8 MB)
    • 3. Dictionaries key-value pairs, methods.mp4 (44.6 MB)
    • 4. Conditional statements (if, elif, else).mp4 (28.1 MB)
    • 5. Logical expressions in conditions.mp4 (40.1 MB)
    • 6. Looping structures (for loops, while loops).mp4 (34.8 MB)
    • 7. Defining, Creating and Calling functions.mp4 (21.3 MB)
    • 8. Python Programming Basics – Level 2.html (0.2 KB)
    4. What is Data Analysis
    • 1. Understanding data analysis.mp4 (10.6 MB)
    • 2. Step-by-step data analysis procedure.mp4 (9.8 MB)
    • 3. Practice dataset and quizz instructions.html (0.3 KB)
      • Practice datasets
      • Extra Data.xlsx (10.5 KB)
      • Extra Variable.xlsx (33.0 KB)
      • sales data.xlsx (85.0 KB)
      __MACOSX Practice datasets
      • _Extra Data.xlsx (0.3 KB)
      • _Extra Variable.xlsx (0.3 KB)
      • _sales data.xlsx (0.3 KB)
      5. Clean Dataset for Integrity and Validity
      • 1. Importing dataset into Jupyter Notebook.mp4 (39.1 MB)
      • 2. Imputing missing values with SimpleImputer.mp4 (81.1 MB)
      • 3. Finding and dealing with inconsistent data.mp4 (61.8 MB)
      • 4. Identify and assign correct dataset.mp4 (40.3 MB)
      • 5. Dealing with duplicate values.mp4 (28.2 MB)
      • 6. Data Cleaning in Python.html (0.2 KB)
      6. Manipulate Data to Increase the Functionality
      • 1. Sorting and arranging dataset.mp4 (30.9 MB)
      • 2. Conditional Filtering of dataset.mp4 (71.6 MB)
      • 3. Merging extra data with the dataset.mp4 (31.2 MB)
      • 4. Concatenating variables within dataset.mp4 (31.4 MB)
      • 5. Data Manipulation.html (0.2 KB)
      7. Explore dataset and generate significant insights
      • 1. What is exploratory data analysis.mp4 (27.9 MB)
      • 2. Frequency and percentage analysis.mp4 (165.7 MB)
      • 3. Descriptive analysis for numeric data.mp4 (95.7 MB)
      • 4. Grouping analysis - numeric measure by nominal data.mp4 (113.6 MB)
      • 5. Pivot table - a tabulation of insights.mp4 (144.4 MB)
      • 6. Crosstabulation - categorical vs categorical data.mp4 (68.6 MB)
      • 7. Correlation - numeric vs numeric data.mp4 (27.1 MB)
      • 8. Exploratory data analysis.html (0.2 KB)
      8. What is Statistical Data Analysis
      • 1. Various aspects of hypothesis testing.mp4 (30.4 MB)
      • 2. Confidence level, significance level, p-value.mp4 (27.4 MB)
      • 3. Steps in hypothesis testing.mp4 (29.8 MB)
      • 4. Statistical data analysis.html (0.2 KB)
      9. Transforming Data into Normal Distribution
      • 1. Test normality of numeric data.mp4 (42.8 MB)
      • 2. Square root transformation method.mp4 (37.8 MB)
      • 3. Logarithm transformation method.mp4 (37.1 MB)
      • 4. Boxcox transformation method.mp4 (37.9 MB)
      • 5. Yeo-johnson transformation method.mp4 (41.6 MB)
      • 6. Data Transformation.html (0.2 KB)
      • Bonus Resources.txt (0.4 KB)

Description

Python Data Analysis Bootcamp for Beginners: All in One

https://DevCourseWeb.com

Published 1/2024
Created by Md Shahriar
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 59 Lectures ( 7h 4m ) | Size: 2.41 GB

Master Python Essentials, Data Cleaning, Manipulation, Analysis, Transformation, Statistics, Hypothesis Testing and More

What you'll learn:
Learn Python's syntax, data types, variables, and operators to construct simple programs and execute basic functions.
Learn to regulate program flow, use loops and conditional statements like if, elif, and else.
Acquire skills to use Python lists, dictionaries, tuples, and sets.
Learn NumPy and Pandas the key Python packages for data manipulation and computing.
Learn how to quickly fix NameError, TypeError, IndentationError, and other issues.
Harness the power of ChatGPT for real-time code suggestions, completion, and improvement.
Learn and apply the data analysis methodology, from data cleaning to hypothesis testing, in real-world applications.
Increase your critical thinking and problem-solving skills for data analysis, decision-making, and recommendation.
Use value counts, percentage, group by, pivot tables, correlation, and regression professionally and realistically.
Solve over 60+ real-world data analytical questions to practice applying data analysis to various circumstances.
Emphasize practical application to gain valuable insights from data and create educated judgments and suggestions.
Learn Python for data analysis using industry-standard libraries and tools.
Master statistical inference, draw meaningful findings, and make data-driven decisions.
Develop critical thinking, data analysis, and practical recommendations for informed decision-making.

Requirements:
No coding experience is needed
Desire to learn data analysis in python



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Udemy - Python Data Analysis Bootcamp for Beginners - All in One

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Download torrent
2.4 GB
seeders:15
leechers:21
Udemy - Python Data Analysis Bootcamp for Beginners - All in One

Torrent hash: 5C38B4470761FFF127E3733BE56427B1B908EC2D