Source: Deep Learning on Medium

## 1) Python Basics

In order to become a data scientist, you need to understand the basics of Python first. Because Python is the favored language for data science.

By going through this course of edX **“Introduction to Python for Data Science” **you will have some basic understanding of python.

## 2) Statistics & Probability

Stats is a key part of Data Science. If I am not wrong Data Science is all about statistics. This course of KhanAcademy will help you to understand the basic concepts of statistics and probability. Click here.

## 3) Data Analysis

Data preprocessing and visualization of data is one of the main components of data science. This course will teach you how computing and mathematics come together. The data analysis involves the collection of data preprocessing and interactive visualization of data. If you want to master this key component, click here.

## 4) Machine Learning for Data Science and Analytics

Now its time to learn some Machine learning stuff. After taking this course**“Machine Learning For Data Science & Analytics” **you will be able to understand algorithms and how to create ML models.

## 5) Deep Learning

This is a complete book of Deep Learning in which you will have got clear and very precise knowledge about deep learning.

**6) Intro to Relational Databases (SQL, DB-API & More..)**If you have learned python completely, this course will help you a lot to understand this course, because it is all about SQL queries and how you will use the relational database from your code using python example. You will learn the basics of SQL along with Python API for connecting python code to the database.

## 7) Intro to Hadoop and MapReduce

For the handling of Big Data, Apache Hadoop develops open-source software for the manipulation of Big Data. This course will make you understand the basics of Hadoop and the principles behind it.

## 8) Data Storytelling

To be a data scientist is not enough, you have to learn the way of representing data and its insights to the management, executives and other stakeholders. So, it is necessary to learn the data storytelling skill so that you wouldn’t get confused at the time of data representation. Click here.

# *Important*

Learning is not enough if you don’t practice what you have learned. So I urged you to do at least 2 to 3 Kaggle projects to polish your data science skills.

This roadmap is enough for you to start your career as a data scientist. You don’t need to go anywhere or enrolled $1000 of courses to become a data scientist. You can do it on your own. You just need to start once with passion!