[DesireCourse.Net] Udemy - Practical statistics for data and business analysis

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[DesireCourse.Net] Udemy - Practical statistics for data and business analysis

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种子哈希：da5876f612d4b19d955277548416f2a121f2f051
文件大小： 1.7G
已经下载：1331次
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收录时间：2021-03-20
最近下载：2025-07-16

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文件列表

  • 9. Data types/7. Quizzes and examples about data types.mp4 188.1 MB
  • 7. Comparison between inferential ans descriptive statistics/2. Simplified viewpoint about descriptive and inferential statistics.mp4 92.9 MB
  • 7. Comparison between inferential ans descriptive statistics/5. Population and sample in inferential statistics.mp4 63.9 MB
  • 5. What is after data analysis/4. What is after data analysis .mp4 60.7 MB
  • 3. Startup point of programming in data analysis/4. Where is my start up point to learn programming .mp4 59.4 MB
  • 3. Startup point of programming in data analysis/7. Review about our questions related to programming.vtt 51.9 MB
  • 3. Startup point of programming in data analysis/7. Review about our questions related to programming.mp4 51.9 MB
  • 7. Comparison between inferential ans descriptive statistics/3. Data before and after descriptive statistics.mp4 51.2 MB
  • 10. Center of numerical data/9. Examples of mode.mp4 46.9 MB
  • 10. Center of numerical data/7. Examples of mean.mp4 43.7 MB
  • 1. Getting Started/2. Introduction and overview about data analysis.mp4 43.4 MB
  • 9. Data types/6. Difference between numerical and categorical data.mp4 41.7 MB
  • 8. FAQ about descriptive statistics/2. What will we learn in descriptive statistics .mp4 39.6 MB
  • 4. Example about programming and big data/1. Important introduction about SQL example.mp4 39.4 MB
  • 9. Data types/5. Data types ( continuous vs discrete ).mp4 35.7 MB
  • 10. Center of numerical data/8. Examples of median.mp4 34.2 MB
  • 4. Example about programming and big data/9. Variety in big data.mp4 31.8 MB
  • 5. What is after data analysis/3. Difference between data analytics and data science.mp4 31.3 MB
  • 1. Getting Started/7. Collection about important questions related to data science.mp4 31.1 MB
  • 4. Example about programming and big data/4. Python with sample activity.mp4 30.1 MB
  • 8. FAQ about descriptive statistics/4. Waitress should be friendly or friendlier .mp4 29.1 MB
  • 4. Example about programming and big data/10. What is velocity in big data .mp4 29.0 MB
  • 5. What is after data analysis/5. What is professional people in data analysis care .mp4 27.5 MB
  • 4. Example about programming and big data/7. Professional answer about what is big data .mp4 26.9 MB
  • 9. Data types/8. The summary about data types.mp4 26.6 MB
  • 9. Data types/4. Categorical data types.mp4 26.2 MB
  • 5. What is after data analysis/2. Introduction with important questions .mp4 25.8 MB
  • 7. Comparison between inferential ans descriptive statistics/6. Simplified viewpoint about inferential statistics data.mp4 25.8 MB
  • 2. Careers and robot jobs/2. Important questions about Robot jobs and my career.mp4 25.7 MB
  • 2. Careers and robot jobs/5. Robot jobs will create new jobs for you because it is a friend.mp4 23.9 MB
  • 6. introduction before descriptive statistics/2. Our strategy to learn practical statistics.mp4 22.9 MB
  • 4. Example about programming and big data/11. Big data is something made overloads.mp4 22.7 MB
  • 2. Careers and robot jobs/4. Example about robot jobs.mp4 22.3 MB
  • 3. Startup point of programming in data analysis/2. Collection of important questions related to programming.mp4 21.3 MB
  • 10. Center of numerical data/3. Characteristics of numerical data.mp4 21.0 MB
  • 2. Careers and robot jobs/3. High demand for hiring data analysis engineer.mp4 20.6 MB
  • 7. Comparison between inferential ans descriptive statistics/4. Conclusions between inferential and descriptive statistics.mp4 20.4 MB
  • 10. Center of numerical data/2. introduction about data center.mp4 20.4 MB
  • 9. Data types/3. the benefit of data types.mp4 19.7 MB
  • 4. Example about programming and big data/2. Run your first SQL command without any previous experience.mp4 19.0 MB
  • 1. Getting Started/9. People are panic from robot jobs.mp4 18.4 MB
  • 5. What is after data analysis/6. Your data is your treasure.mp4 17.7 MB
  • 10. Center of numerical data/5. Example about characteristics of categorical data.mp4 16.8 MB
  • 10. Center of numerical data/10. I'm confused between mean , median and mode.mp4 16.6 MB
  • 8. FAQ about descriptive statistics/3. Statistics between Lie and trustworthy.mp4 14.6 MB
  • 1. Getting Started/5. Machine learning should be after practical statistics.mp4 14.5 MB
  • 9. Data types/2. Introduction about data types.mp4 13.5 MB
  • 6. introduction before descriptive statistics/3. Four main things in practical statistics.mp4 13.1 MB
  • 4. Example about programming and big data/8. What is OVERLOADS in a big data .mp4 12.9 MB
  • 1. Getting Started/6. General overview about what will you learn in data science courses.mp4 12.9 MB
  • 1. Getting Started/8. Be patient for interview questions.mp4 12.5 MB
  • 1. Getting Started/4. What is the main concept of data analysis .mp4 12.2 MB
  • 10. Center of numerical data/4. Categorical data characteristics considered to be limited.mp4 12.2 MB
  • 1. Getting Started/3. Is programming for data science easy or hard .mp4 11.4 MB
  • 3. Startup point of programming in data analysis/3. Should i learn programming like professional .mp4 11.0 MB
  • 10. Center of numerical data/6. What are measures of center .mp4 10.7 MB
  • 2. Careers and robot jobs/6. It is not easy to hire data science engineer.mp4 9.5 MB
  • 4. Example about programming and big data/6. What is big data .mp4 9.5 MB
  • 3. Startup point of programming in data analysis/5. R language not for software developers.mp4 8.7 MB
  • 4. Example about programming and big data/5. Review about Python and SQL in data analysis.mp4 8.2 MB
  • 2. Careers and robot jobs/7. Why do you think that learning programming is Barrier in data analysis .mp4 8.2 MB
  • 3. Startup point of programming in data analysis/6. Programming in data analysis uses simple and easy language.mp4 7.9 MB
  • 4. Example about programming and big data/3. Note the difference between SQL and English language.mp4 6.7 MB
  • 3. Startup point of programming in data analysis/8. What is our example in programming .mp4 5.2 MB
  • 9. Data types/7. Quizzes and examples about data types.vtt 10.1 kB
  • 3. Startup point of programming in data analysis/4. Where is my start up point to learn programming .vtt 7.5 kB
  • 7. Comparison between inferential ans descriptive statistics/2. Simplified viewpoint about descriptive and inferential statistics.vtt 6.0 kB
  • 4. Example about programming and big data/4. Python with sample activity.vtt 5.0 kB
  • 4. Example about programming and big data/9. Variety in big data.vtt 4.3 kB
  • 4. Example about programming and big data/10. What is velocity in big data .vtt 3.5 kB
  • 5. What is after data analysis/4. What is after data analysis .vtt 3.4 kB
  • 7. Comparison between inferential ans descriptive statistics/5. Population and sample in inferential statistics.vtt 3.4 kB
  • 7. Comparison between inferential ans descriptive statistics/3. Data before and after descriptive statistics.vtt 3.2 kB
  • 4. Example about programming and big data/1. Important introduction about SQL example.vtt 3.1 kB
  • 10. Center of numerical data/9. Examples of mode.vtt 3.1 kB
  • 9. Data types/5. Data types ( continuous vs discrete ).vtt 3.0 kB
  • 10. Center of numerical data/8. Examples of median.vtt 2.9 kB
  • 5. What is after data analysis/3. Difference between data analytics and data science.vtt 2.8 kB
  • 9. Data types/6. Difference between numerical and categorical data.vtt 2.7 kB
  • 1. Getting Started/7. Collection about important questions related to data science.vtt 2.6 kB
  • 8. FAQ about descriptive statistics/2. What will we learn in descriptive statistics .vtt 2.5 kB
  • 10. Center of numerical data/1. Slides and material used in this content.html 2.4 kB
  • 3. Startup point of programming in data analysis/1. Slides and material used in this content.html 2.4 kB
  • 6. introduction before descriptive statistics/2. Our strategy to learn practical statistics.vtt 2.3 kB
  • 10. Center of numerical data/7. Examples of mean.vtt 2.3 kB
  • 10. Center of numerical data/3. Characteristics of numerical data.vtt 2.2 kB
  • 1. Getting Started/2. Introduction and overview about data analysis.vtt 2.2 kB
  • 4. Example about programming and big data/2. Run your first SQL command without any previous experience.vtt 2.2 kB
  • 9. Data types/4. Categorical data types.vtt 2.2 kB
  • 9. Data types/1. Slides and material used in this content.html 2.1 kB
  • 8. FAQ about descriptive statistics/4. Waitress should be friendly or friendlier .vtt 2.1 kB
  • 2. Careers and robot jobs/3. High demand for hiring data analysis engineer.vtt 2.1 kB
  • 7. Comparison between inferential ans descriptive statistics/6. Simplified viewpoint about inferential statistics data.vtt 2.0 kB
  • 5. What is after data analysis/5. What is professional people in data analysis care .vtt 1.9 kB
  • 4. Example about programming and big data/7. Professional answer about what is big data .vtt 1.7 kB
  • 3. Startup point of programming in data analysis/5. R language not for software developers.vtt 1.6 kB
  • 4. Example about programming and big data/11. Big data is something made overloads.vtt 1.6 kB
  • 2. Careers and robot jobs/5. Robot jobs will create new jobs for you because it is a friend.vtt 1.6 kB
  • 2. Careers and robot jobs/4. Example about robot jobs.vtt 1.6 kB
  • 9. Data types/8. The summary about data types.vtt 1.5 kB
  • 4. Example about programming and big data/6. What is big data .vtt 1.5 kB
  • 7. Comparison between inferential ans descriptive statistics/4. Conclusions between inferential and descriptive statistics.vtt 1.5 kB
  • 9. Data types/3. the benefit of data types.vtt 1.5 kB
  • 2. Careers and robot jobs/6. It is not easy to hire data science engineer.vtt 1.4 kB
  • 1. Getting Started/9. People are panic from robot jobs.vtt 1.4 kB
  • 2. Careers and robot jobs/1. Slides and material used in this content.html 1.3 kB
  • 1. Getting Started/5. Machine learning should be after practical statistics.vtt 1.3 kB
  • 5. What is after data analysis/6. Your data is your treasure.vtt 1.3 kB
  • 5. What is after data analysis/2. Introduction with important questions .vtt 1.3 kB
  • 1. Getting Started/8. Be patient for interview questions.vtt 1.3 kB
  • 2. Careers and robot jobs/2. Important questions about Robot jobs and my career.vtt 1.3 kB
  • 10. Center of numerical data/5. Example about characteristics of categorical data.vtt 1.2 kB
  • 6. introduction before descriptive statistics/3. Four main things in practical statistics.vtt 1.1 kB
  • 1. Getting Started/1. Slides and material used in this content.html 1.1 kB
  • 3. Startup point of programming in data analysis/3. Should i learn programming like professional .vtt 1.1 kB
  • 4. Example about programming and big data/3. Note the difference between SQL and English language.vtt 1.1 kB
  • 3. Startup point of programming in data analysis/2. Collection of important questions related to programming.vtt 1.1 kB
  • 8. FAQ about descriptive statistics/3. Statistics between Lie and trustworthy.vtt 1.0 kB
  • 1. Getting Started/4. What is the main concept of data analysis .vtt 1.0 kB
  • 1. Getting Started/3. Is programming for data science easy or hard .vtt 965 Bytes
  • 10. Center of numerical data/4. Categorical data characteristics considered to be limited.vtt 935 Bytes
  • 10. Center of numerical data/2. introduction about data center.vtt 933 Bytes
  • 5. What is after data analysis/1. Slides and material used in this content.html 929 Bytes
  • 4. Example about programming and big data/8. What is OVERLOADS in a big data .vtt 926 Bytes
  • 1. Getting Started/6. General overview about what will you learn in data science courses.vtt 891 Bytes
  • 8. FAQ about descriptive statistics/1. Slides and material used in this content.html 884 Bytes
  • 7. Comparison between inferential ans descriptive statistics/1. Slides and material used in this content.html 873 Bytes
  • 4. Example about programming and big data/5. Review about Python and SQL in data analysis.vtt 845 Bytes
  • 10. Center of numerical data/6. What are measures of center .vtt 842 Bytes
  • 2. Careers and robot jobs/7. Why do you think that learning programming is Barrier in data analysis .vtt 734 Bytes
  • 6. introduction before descriptive statistics/1. Slides and material used in this content.html 708 Bytes
  • 3. Startup point of programming in data analysis/6. Programming in data analysis uses simple and easy language.vtt 684 Bytes
  • 9. Data types/2. Introduction about data types.vtt 665 Bytes
  • 3. Startup point of programming in data analysis/8. What is our example in programming .vtt 510 Bytes
  • [DesireCourse.Net].url 51 Bytes
  • [CourseClub.Me].url 48 Bytes

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