When you talk about data science the most important thing is Statistical MATHS .

This course teaches statistical maths using simple excel. My firm belief is MATHS is 80% part of data science while programming is 20%. If you start data science directly with python , R and so on , you would be dealing with lot of technology things but not the statistical things.

I recommend start with statistics first using simple excel and the later apply the same using python and R. Below are the topics covered in this course.

Lesson 1 :- What is Data science ?
Chapter 1 :- What is Data science and why do we need it ?

Chapter 2:- Average , Mode , Min and Max using simple Excel.

Chapter 3:- Data science is Multi-disciplinary.

Chapter 4:- Two golden rules for maths for data science.

Lesson 2 :- What is Data science ?

Chapter 4:- Spread and seeing the same visually.

Chapter 5:- Mean,Median,Mode,Max and Min

Chapter 6:- Outlier,Quartile & Inter-Quartile

Chapter 7:- Range and Spread

Lesson 3 - Standard Deviation, Normal Distribution & Emprical Rule.
Chapter 8:- Issues with Range spread calculation

Chapter 9:- Standard deviation

Chapter 10:- Normal distribution and bell curve understanding

Chapter 11:- Examples of Normal distribution

Chapter 12:- Plotting bell curve using excel

Chapter 13:- 1 , 2 and 3 standard deviation

Chapter 14:- 68,95 and 98 emprical rule.

Chapter 15:- Understanding distribution of 68,95 and 98 in-depth.

Lesson 4 :- The ZScore calculation
Chapter 16:- Probability of getting 50% above and 50% less.

Chapter 17:- Probability of getting 20 value.

Chapter 18:- Probability of getting 40 to 60.

Lesson 5 - Binomial distribution

Chapter 22:- Basics of binomial distribution.

Chapter 23:- Calculating existing probability from history.

Chapter 24:- Exact vs Range probability.

Chapter 25:- Applying binomial distribution in excel.

Chapter 26:- Applying Range probability.

Chapter 27:- Rules of Binomial distribution.

Do visit to enroll all courses - https://www.questpond.com/python-r-programming-maths-for-data-science/cid21

Frequently Asked Questions

Are there any course requirements or prerequisites?
1-->No programming knowledge needed. 2-->Basic excel knowledge is added plus point.
Who are your target students?
Who want to learn statistic maths from data science perspective.
What will students learn in your course?
Fundamentals , What and Why of Data science. --> Descriptive statistics Average , Mode , Min and Max using simple Excel. -->Understanding importance of spread and finding spread using range.--> Quartile , Inter-Quartile , outliers, standard deviation , Normal distribution and bell curve .--> Understanding 1,2 and 3 standard deviation and applying 68,95 and 98 empirical rule.-->Finding probability of different scenarios of normal distribution.--> Calculating Z score to find the exact probability. --> Binomial distribution , exact and range probability , applying binomial distribution and rules of binomial distribution.