Data Science Roadmap with Learning Resources
Here is a complete roadmap to learn data science with all the learning resources you can follow.
Data science is one of the highest paying career options in this data-driven world. Every company now makes decisions based on the data generated by its business. A company, therefore, needs skilled data science professionals to turn raw data into actionable insights. If you’re looking for a step-by-step roadmap for learning data science, this article is for you. In this article, I will introduce you to a data science roadmap that you can follow to learn data science.
Data Science Roadmap
Start with Python
Data Science is a branch of Artificial Intelligence and computer science. It is a combination of data mining and computer science. So to work with data, you should know a programming language. Python is the most preferred programming language by data science professionals. You can understand why data science professionals prefer Python over other languages from here. If you want to learn Python from scratch, below are some of the best resources you can follow:
Learn Probability and Statistics for Data Science
The next step in your data science roadmap is understanding the probability and statistics for data science. Probability and statistics will help you figure out what kind of data you are working with. It will also help you understand machine learning algorithms that you will learn later. If you don’t know how to learn probability and statistics for data science, below are some of the best resources you can follow:
Learn Python for Data Science
After learning the fundamentals of the Python programming language and probability and statistics, the next step in your data science roadmap is learning Python for Data Science. There is a difference between the fundamentals of Python and Python for Data Science.
In the fundamentals, you learn the Python programming language, and in Python for data science, you learn how to use Python libraries and frameworks to work with data. If you do not have any idea about how you can learn Python for data science, below are some of the best resources you can follow:
Now Learn Machine Learning
It is the most important step in your data science roadmap. Here you have to learn machine learning. Machine Learning means using data and algorithms to build intelligent systems. While learning machine learning, you need to focus on the theory of machine learning algorithms and their implementation using Python.
Understanding the theory of machine learning algorithms will help you select a machine learning algorithm based on your problem and the type of data you are dealing with. Below are some of the best resources to learn machine learning:
Explore Essential Data Science Tools
The next step in your data science roadmap is to explore all the essential data science tools. There are some tools and software that you should know to work as a data science professional in any domain. You can explore all the tools that you need to learn for data science from here.
Final Step: Work on Projects
The last step in the data science roadmap is often overlooked by many beginners. The ultimate goal is to learn data science and get a job as a data science professional. To get your first data science job, you need to show how you can solve problems with all the skills you have.
So work on projects! It will help you show your approaches to solving different problems with your data science skills. You can find some amazing data science projects solved and explained from here. You can practice your skills by going through these projects.
Summary
So this is the complete data science roadmap that I will recommend you to follow to learn data science:
- Start with Python
- Learn Probability and Statistics
- Learn Python for Data Science
- Learn Machine Learning
- Explore Data Science Tools
- Work on Projects
At each step of the roadmap above, I’ve mentioned some of the best resources you can follow to learn data science. I hope you liked this article on a comprehensive roadmap to learning data science. Feel free to ask valuable questions in the comments section below.
