課程資料
- 可獲發
- *證書的發放與分配,依課程提供者的政策及安排而定。
課程簡介
Learn the statistics & probability for data science and business analysis
Are you aiming for a career in Data Science or Data Analytics?
Good news, you don't need a Maths degree - this course is equipping you with the practical knowledge needed to master the necessary statistics.
It is very important if you want to become a Data Scientist or a Data Analyst to have a good knowledge in statistics & probability theory.
Sure, there is more to Data Science than only statistics. But still it plays an essential role to know these fundamentals ins statistics.
I know it is very hard to gain a strong foothold in these concepts just by yourself. Therefore I have created this course.
Why should you take this course?
This course is the one course you take in statistic that is equipping you with the actual knowledge you need in statistics if you work with data
This course is taught by an actual mathematician that is in the same time also working as a data scientist.
This course is balancing both: theory & practical real-life example.
After completing this course you ll have everything you need to master the fundamentals in statistics & probability need in data science or data analysis.
What is in this course?
This course is giving you the chance to systematically master the core concepts in statistics & probability, descriptive statistics, hypothesis testing, regression analysis, analysis of variance and some advance regression / machine learning methods such as logistics regressions, polynomial regressions , decision trees and more.
In real-life examples you will learn the stats knowledge needed in a data scientist's or data analyst's career very quickly.
If you feel like this sounds good to you, then take this chance to improve your skills und advance career by enrolling in this course.
課程章節
- 9 個章節
- 91 堂課
- 第 1 章 Let's get started
- 第 2 章 Descriptive statistics
- 第 3 章 Distributions
- 第 4 章 Probability theory
- 第 5 章 Hypothesis testing
- 第 6 章 Regressions
- 第 7 章 Advanced regression & machine learning algorithms
- 第 8 章 ANOVA (Analysis of Variance)
- 第 9 章 Wrap up
課程內容
- Master the fundamentals of statistics for data science & data analytics
- Master descriptive statistics & probability theory
- Machine learning methods like Decision Trees and Decision Forests
- Probability distributions such as Normal distribution, Poisson Distribution and more
- Hypothesis testing, p-value, type I & type II error
- Logistic Regressions, Multiple Linear Regression, Regression Trees
- Correlation, R-Square, RMSE, MAE, coefficient of determination and more
此課程所涵蓋的技能
評價
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VVijay Kumar Shankar
its all basics to learn how the Statistical analysis works with mathematics. i enjoyed with the examples
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KKARNIK
Complex topic explained in very simplified manner
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RRohit Nishad
Poor explanation on hypthesis testing
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DDisplay Name Unknown
I hope we go more into standard deviation. It seems like a really important concept to gloss over with just a formula.