Roadmap to become a Data Scientist

Data Science is considered as the trending profession across the globe. It has been declared as the highest paying job. The average salary of data science across the world is USD 130,000 to USD 195,000 per year which is approximate 1 crore in Indian Rupee. Back in 1974, Peter Naur brought data science to the world of computers and it has been into existence in India since 2001.

As with more of its advantages people want to get into this field. They want to have a high profile job and want to secure their future but they don’t know where to start with. So, I am going to tell you all the tracks that will lead you to become a professional Data Scientist.

Keys to become a Data Scientist

  • Programming
  • Data Wrangling
  • Machine Learning
  • Deep Learning’
  • Natural Language Processing (NLP)
  • Framework
  • Tools
  • Data Visualization


Programming is the basic need of computer science. Data Science is all about studying large amount of data that is stored in raw facts and figures. With these you can analyze the data, fix the data, and protect the data. Now, to handle such a huge amount of data you need some programming skills and Data Science or Big Data Analytics requires main four programming languages that are Python, R language, Jupyter Notebook and Julia.

Data Wrangling

As you have a huge amount of data that means it will be having many errors, faults and incomplete data too. So, in order to remove all the errors and make all the difficult datasets into more convenient form we follow the process of Data Wrangling. It is done with the help of some open source software namely Structured Query Language (SQL), Apache Spark, Pandas and Tableau.

Machine Learning and Deep Learning

Data Science has a union sets of machine learning and deep learning. Without both these data science will not be possible. In order to categorize the data in an organized form we need the help of some machine learning algorithms, that are Supervised, Unsupervised and Reinforcement Learning of the data.

The subset of machine learning is Deep learning which enables the computers to perform human-like tasks. For Data Science from the category of deep learning we have Neural Networks, GANS, CNN and LSTM.

Natural Language Processing (NLP)

NLP is a branch of artificial intelligence and machine learning which actually acts as a medium of communication between the computer and the human language. For particularly Data Science you have to use Transformers, BERT and Sentiment Analysis.


For the framework side of your data science journey you will have to work on PyTorch, TensorFlow Keras, and Scikit-learn. These will help you in proper data mining.


Working with data science will require you some tools that are Airflow, MLFlow, MLOPs, Spark and Kubeflow.

Data Visualization

The time your data is fully mined, cleaned and is now ready to set for presentation/visualization we use some of the libraries that help us get the clear insight of the data. The data visualization tools are D3.JS, Plotly, MatPlotLib and Tableau.


So, these are the roadmap to become a successful data scientist. All the tools, programming languages, framework, tools, etc plays a very important role. After you have done all of these tested your data too then make a project and add it to the resume. This will help you to having a real time experience with data and you will learn a lot from this and side by side it’s building your profile too.

Read More: What kind of machine learning techniques does Snapchat use?

Leave a Comment

Your email address will not be published. Required fields are marked *