Udemy - Data Analysis A-Z - Become Data Analyst in 30 Days

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Udemy - Data Analysis A-Z - Become Data Analyst in 30 Days (Size: 1.6 GB)
  1. ChatGPT for smooth python coding in Data Analysis.mp4 60.3 MB
  1. Day 1 Data analysis and its characteristics.mp4 10.6 MB
  1. Day 12 Exploring value counts analysis method.mp4 165.6 MB
  1. Day 18 Various aspects of hypothesis testing.mp4 30.4 MB
  1. Day 21 Testing normal distribution of numeric variables.mp4 42.8 MB
  1. Day 26 One way between groups ANOVA.mp4 67.3 MB
  1. Day 3 Loading dataset in your jupyter notebook.mp4 39.1 MB
  1. Day 8 Learn data sorting and arrangement.mp4 30.9 MB
  1. Install Python and Jupyter Notebook.html 204.8 B
  1.1 Mac.pdf 1.5 MB
  1.2 Windows.pdf 929.7 KB
  2. Course Resources.html 102.4 B
  2. Day 13 Exploring descriptive statistics analysis method.mp4 95.7 MB
  2. Day 19 Understand confidence level, significance level and p-value.mp4 27.4 MB
  2. Day 2 Complete data analysis work-flow.mp4 9.9 MB
  2. Day 22 Square root transformation for normal distribution.mp4 37.8 MB
  2. Day 27 Pearson product-moment correlation coefficient.mp4 82.5 MB
  2. Day 4 Dealing with missing values.mp4 81.1 MB
  2. Day 9 Learn conditional data filtering.mp4 71.7 MB
  2. Setting Up ChatGPT for SMART Analysis.html 204.8 B
  2.1 Complete Data Analysis Work-flow.pptx 47.1 KB
  2.1 Instructions of setting up ChatGPT.pdf 409.1 KB
  2.2 Confidence, significance and p value.pdf 53.6 KB
  2.3 Data Analysis.pptx 38.7 KB
  2.4 Steps in Hypothesis Testing.pdf 333.5 KB
  2.5 Various aspects of Hypothesis.pdf 58.9 KB
  3. Day 10 Learn to merge extra variables.mp4 31.1 MB
  3. Day 14 Exploring group by analysis method.mp4 113.6 MB
  3. Day 20 Understand complete steps in hypothesis testing.mp4 29.8 MB
  3. Day 23 Logarithmic transformation for normal distribution.mp4 37 MB
  3. Day 28 Multiple linear regression analysis with statsmodel.api.mp4 103.8 MB
  3. Day 5 Dealing with inconsistent values.mp4 61.7 MB
  3. Practice datasets and instruction for QUIZES.html 307.2 B
  4. Day 11 Learn to concatenate extra data.mp4 31.4 MB
  4. Day 15 Exploring pivot table analysis method.mp4 144.4 MB
  4. Day 24 Box-cox transformation for normal distribution.mp4 37.9 MB
  4. Day 6 Dealing with miss-identified data types.mp4 40.3 MB
  4. Final QUIZ Hypothesis Testing A-Z.html 204.8 B
  4. QUIZ 4 Understanding Statistical Data Analysis A-Z.html 204.8 B
  5. Day 16 Exploring crosstabulation analysis method.mp4 68.5 MB
  5. Day 25 Yeo-Johnson transformation for normal distribution.mp4 41.6 MB
  5. Day 7 Dealing with duplicated data.mp4 28.2 MB
  5. Final Solution Hypothesis Testing A-Z.html 102.4 B
  5. QUIZ 2 Data Manipulation A-Z.html 204.8 B
  5.1 Stage 6- Hypothesis Testing A-Z (Solution).ipynb 1.2 MB
  6. Day 17 Exploring correlation analysis method.mp4 27.1 MB
  6. QUIZ 1 Data Cleaning A-Z.html 204.8 B
  6. QUIZ 5 Data Transformation A-Z.html 204.8 B
  6. Solution 2 Data Manipulation A-Z.html 102.4 B
  6.1 Stage 2- Data Manipulation A-Z (Solution).ipynb 85.4 KB
  7. QUIZ 3 Exploratory Data Analysis A-Z.html 204.8 B
  7. Solution 1 Data Cleaning A-Z.html 102.4 B
  7. Solution 5 Data Transformation A-Z.html 102.4 B
  7.1 Stage 1- Data Cleaning A-Z (Solution).ipynb 34.8 KB
  7.1 Stage 5- Data Transformation A-Z (Solution).ipynb 1.2 MB
  8. Solution 3 Exploratory Data Analysis A-Z.html 102.4 B
  8.1 Stage 3- Exploratory Data Analysis A-Z (Solution).ipynb 748.3 KB
  Bonus Resources.txt 409.6 B
  Extra Data.xlsx 10.5 KB
  Extra Variable.xlsx 33 KB
  Get Bonus Downloads Here.url 204.8 B
  _Extra Data.xlsx 307.2 B
  _Extra Variable.xlsx 307.2 B
  _sales data.xlsx 307.2 B
  sales data.xlsx 85 KB
  ▲ 65 total files

Description


Data Analysis A-Z: Become Data Analyst in 30 Days

https://DevCourseWeb.com

Published 10/2023
Created by Md Shahriar
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 38 Lectures ( 4h 20m ) | Size: 1.61 GB

Unlock Data Analysis with Hands-on Python Proficiency. Master Full Work-flow and Become Pro Data Analyst in 30 Days.

What you'll learn
Understand and apply the complete data analysis workflow, from data cleaning to hypothesis testing, mirroring real-life scenarios.
Develop the personal capabilities of critical thinking and problem-solving essential for effective data analysis, decision-making, and recommendation.
Implement various data analysis techniques: value counts, percentage, group by, pivot tables, correlation, and regression, practically and professionally.
Solve more than 12 real-world data analytical questions to gain hands-on experience in applying data analysis skills to diverse situations.
Learn to derive significant insights from data and use them to make informed decisions and recommendations by emphasizing the practical application.
Gain proficiency in using Python for data analysis, covering key libraries and tools commonly employed in the industry.
Learn the principles of statistical inference, understand how to draw meaningful conclusions, and make data-driven decisions based on statistical evidence.
Cultivate the ability to think critically about data, and extract meaningful insights, and deliver actionable recommendations for informed decision-making.

Requirements
No coding Experience is Needed.
Mindset to be Successful.
Dedication to be Data Analyst.
Intention to Learn Python.

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