Road Map for learning Data Science

Data science at its most basic level is defined as using data to obtain insights and information that provide some level of value. Data science is evolving fast and has a wide range of possibilities surrounding it and so to limit it by that basic definition is kind of elementary. An extension of the that definition would be that data science is a complex combination of skills such as programming, data visualization, command line tools, databases, statistics, machine learning and more… in order to analyze data and obtain insights, information, and value from vast amounts of data.

Python Programming
The very first thing you should learn is some basic python programming. Learn the Syntax, Variables and Data types, Lists and for Loops, Conditional Statements, Dictionaries and Frequency Tables, Functions, and Object Oriented Python to get started.

Databases
You’ll want to learn SQL for querying data as well as PostgreSQL for advanced database management. You should also know how to work with APIs and web scraping for creating your own datasets. Also try learning spark and map-reduce.

Statistics
Next you’ll want to learn statistics fundamentals which includes sampling, frequency distributions, the mean, weighted mean, the median, the mode, measures of variability, Z-scores, probability, probability distributions, significance testing, and chi squared tests.

Machine Learning
You will want to learn at least 10 basic algorithms for machine learning: linear regression, logistic regression, SVM, random forests, Gradient Boosting, PCA, k-means, collaborative filtering, k-NN, and ARIMA.

Command Line Tools
Next you will want to learn how to navigate the file directory, create and delete directories, how to edit and manage files and their permissions, how to work with programs from the command line, and how to create virtual environments. You’ll also want to learn about git and GitHub for version control.

Data Analysis and Visualization
Now we want to learn data analysis and visualization. First you will want to start off by learning pandas and numpy for cleaning and exploring your data. Then you will want to learn matplotlib for exploratory data visualization and storytelling with your data.

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