Data Scientist Mathematics Syllabus Complete Road Map Part 1

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 Data Scientist  Mathematics

 Syllabus Complete Road 

 Map  Part 1


Data science means different things for different people, but as its gits,  data science is using data to answer questions.
this definition is a moderately broad definition, and that's because one must say data science is a moderately broad field !!









Data science is the science of analyzing raw data using statics and machine learning techniques with the propose  of drawing conclusions about that information



A Roadmap to Learn 

Start with the Overview of Data Science.                                              


Read some Data Science related blogs and 

also research some Data Science-related 

things. For example, read blogs on 

Introduction to Data Science, Why to choose 

data science as a career, Industries That 

Benefits the Most From Data Science, Top lO 

Data Science Skills to Learn in 2021, etc., etc., 

and make a complete mind makeup to start 

your journey on Data Science. 



1. Mathematics 

Math skill is very important as they help us in understanding various machine learning algorithms that play an important role in Data Science


Part 1 :

◎   Linear Algebra 
◎    Analytic Geometry
◎    Matrix
◎   Vector Calculus
◎   Optimization


Part 2 :

◎   Regression 
◎   Dimensionality Reduction
◎    Classification 



2   Probability 

◉   Introduction to Probability
◉    1 D Random Variable
◉    The function of One Random Variable
◉     joint probability  Distribution
◉    Discrete Distribution
              ◎ Binomial ( Python | R )
              ◎  Bernouli 
              ◎   Geometric etc
◉   Continuous Distribution
             ◎  Uniform
             ◎  Exponential
             ◎  Gamma
◉   Normal Distribution ( Python | R )
◉   Correlation
◉   Multiple Regression ( Python | R )
◉   Nonparametric Statistics 
             ◎  Sign Test
             ◎  The Wilcoxon Signed Rank Test (R)
             ◎   The Wilcoxon Rank Sum Test
             ◎    The Kruskal-Wallis Test (R)
◉   Statistical Quality Control
◉    Basics Of Graphs 


3 Statistics 

◉   Introduction to Statistics 
◉   Data Description 
◉   Random Samples 
◉  Sampling Distribution 
◉   Parameter Estimation 
◉   HypothesesTesting (Python I R)
◉   ANOVA(Python I R) 
◉   Reliability Engineering
◉   Stochastic Process 
◉   Computer Simulation 
◉   Design of Experiments
◉   Simple Linear Regression


                                                                                                                                          -Unknown00759-
                                                                             















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