Data-Science-Roadmap

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# Data Science RoadMap

## Table of Contents

1. [Data Science Vs AI vs Machine Leanrning](#datascience-vs-ai-machine-learning)

2. [Prerequisite before Jumping in Data Science](#datascience-jumping)
  
3. [Free Courses for Data Science](#free-courses-for-datascience)

4. [Best Paid Courses for Data Science](#paid-courses)

# Data Science Vs AI vs Machine Leanrning

- Add Content Here

# Prerequisite before Jumping in Data Science

-“ Deeper the roots, taller the trees grow ”
Various Prerequisites for Data Science are:

1. Machine Learning

2. Mathematical Modeling

3. Statistics

4. Computer Programming

5. Databases
What to cover in Programming and Statistics?

When it comes to programming language, there is a lot of debate on Python vs R. Both languages have their own pro’s and cons. Personally, I would recommend Python as it is a general multi-purpose language and has a lot of visualisation libraries like Bokeh, Seaborn and Pygal.

Importing Data in Python,
Pandas Foundation,
Python Data Science Toolbox,
Databases in Python,
Data Visualization with Python,
Interactive Data Visualization with Bokeh,
Merging DataFrames with pandas,
For Statistics,

Statistical Distributions & probability theory ( Calculating MGF, CGF, Mean, Median, Mode, Variance Maximum likelihood Expectation, Central limit theorems, ANOVA ),
Fitting of a distribution,
Sampling & Testing of a hypothesis,
Bayesian Modeling,
Regression and Time Series,

# Free Courses for Data Science

1.[Data Scientist with Python](https://www.datacamp.com/tracks/data-scientist-with-python)(beginner)
2.[Data Scientist with R](https://www.datacamp.com/tracks/data-scientist-with-r)(beginner)
3.[IBM Data Science Professional Certificate](https://www.coursera.org/specializations/ibm-data-science-professional-certificate)(professional)(applicable for finacial aid )(free of cost)
4.[INTRODUCTION TO DATA SCIENCE](https://in.udacity.com/course/intro-to-data-science--ud359)(Beginners)

# Best Paid Courses for Data Science

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