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-“ Deeper the roots, taller the trees grow ” Various Prerequisites for Data Science are:
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Machine Learning
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Mathematical Modeling
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Statistics
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Computer Programming
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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,
1.Data Scientist with Python(beginner) 2.Data Scientist with R(beginner) 3.IBM Data Science Professional Certificate(professional)(applicable for finacial aid )(free of cost) 4.INTRODUCTION TO DATA SCIENCE(Beginners)