Welcome to All Data Science.

It is a long and hard way to become a data scientist. If you do some research and try to put together everything you need to learn data science you will end up with a list similar to the following:

  • Mathematics (Linear Algebra, Calculus, Probability, Inference…).
  • Computing (Algorithms, Programming, Databases, Web…).
  • Machine Learning (Supervised Learning, Unsupervised Learning, Reinforcement Learning…).
  • Big Data. (MapReduce, Unstructured data…).
  • Visualization. (Networks, Charts, Maps…).

And we could keep expanding each of these topics in more subtopics.

Even if you have knowledge of some of these fields, it’s normal to feel a bit overwhelmed:

  • Where do I start?
  • Do I have to start learning statistics or programming?
  • Is it better Python or R?
  • Or even, What is really data science?

Here you will find a guide to help you answering to these questions. It will still be long and hard, but you won’t feel lost anymore.

Please note that this page will be updated with new posts and resources. Subscribe to our email newsletter to receive the latest updates directly to your inbox.

Start index:

1. Introduction – Resources
2. Mathematics – Statistics
3. Computing – Tools
4. Machine Learning – Data Mining
5. Big Data – Cloud
6. Visualization – Business

1. Introduction – Resources


Congratulations on taking the first step to become a data scientist. In this section you will find the introductory posts and resources you need to check to start off on the right foot.

The simplest definition of Data Science is the following one:

Data Science is the extraction of knowledge from data.

Another one by Simply Statistics:

Data science is the process of formulating a quantitative question that can be answered with data, collecting and cleaning the data, analyzing the data, and communicating the answer to the question to a relevant audience.

It is important to note the difference between knowledge and data. We can find a more detailed description in the post What is Data Science?

Once you are sure you know what is the meaning of data science, we recommend you to read the following selection of introductory articles:

Read all the posts in the Introduction – Resources category.

2. Mathematics – Statistics


Mathematics is one of the basis of Data Science. Most of the machine learning techniques require a good knowledge of linear algebra and calculus, but even more important is the field of statistics, as it is the basis of Data Analysis and Data Science.

In this section you will find the posts related to these fields.

Selected posts

  • Basic statistics for Data Science.
  • Basic linear algebra for Data Science.
  • Basic calculus for Data Science.

Read all the posts in the Mathematics – Statistics category.

3. Computing – Tools


The use of computing is what separates the traditional statistician and business analyst from the data scientist. Every data scientist needs to know at least one programming language to develop its analysis.

Here you will find the posts that will help you developing your toolbox.

Selected posts

  • The Data Scientist’s toolbox.

Read all the posts in the Computing – Tools category.

4. Machine Learning – Data Mining


Machine Learning and Data Mining is what separates basic descriptive analysis from more complex and useful data studies. Prediction and classification are just an example of what can be achieved with machine learning and data mining techniques.

Selected posts

  • What is Machine Learning?
  • What is Data Mining?

Read all the posts in the Machine Learning – Data Mining category.

5. Big Data – Cloud


When it comes to data, sometimes more is better. But you have to be aware, actual big data problems need to be approach with different techniques.

Selected posts

  • What is Big Data?

Read all the posts in the Big Data – Cloud category.

6. Visualization – Business


A Data Scientist should be able to effectively communicate the findings of an analysis to non-technical people, and knowing how to visually present the data and the results is a must to achieve this.

In this section you will find the posts related to visualization and communication in the business environment.

Selected posts

  • What is Visualization?

Read all the posts in the Visualization – Business category.

In our resources page you can find a selection of the best resources classified by type of resource.

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