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Your new Mentor for Data Science E-Learning.
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Figure 1-1

If you like Virgilio, FILL THIS FORM and I'll contact you whenever a new free guide comes out.

What Is This Place?

Studying through the Internet means swimming in an infinite jungle of chaotic information, even more so in rapidly changing innovative fields.

Have you ever felt overwhelmed when trying to approach a new subject without a real “path” to follow? Were you hindered from obtaining deep knowledge and the ability to apply it?

Hi, I'm Virgilio.

Like I did with Dante, just some centuries ago, I'll be your mentor and reference point during your journey through the Internet, providing you complete and organic learning paths for several fields, tools, skills and more.

You can read me in 简体中文.

If you like Virgilio, fill this form and I'll contact you whenever a new free guide comes out.

How Did I Do This?

I've tried to be concise to avoid information overhead.

I organized the contents hierarchically and by the level of complexity to give you a coherent idea of how things work.

You will learn to understand and apply theory with hands-on projects and by carefully following my hints and tips, you will master new skills from scratch.

You do not require any prior knowledge of the topics, but be confident with programming and high school-level math to understand and implement most of the concepts.

Every source listed here is free or open source.

My biggest interest is Data Science since I tried to predict the fall of Rome, but you know, at that time we didn't have so much computational power!

What Can You Find Here?

I've packed several types of guides for you:

  • Careers: complete learning paths that guide you through mastering a new skill from scratch.
  • Topics: comprehensive guides about a specific topic, methodology and real-world application organized by sub-field.
  • Specializations: vertical guides on individual skills.
  • Tools: in-depth guides on a single tool or technology.
  • Research: Up-to-date review and explanation of state-of-the-art papers and technical documents.
  • Meta: these are mostly guides on how to study and approach new concepts.

If you find this repository useful, I ask you to leave a star, share it with your friends and colleagues and click on "watch", because this is being updated daily!

What Is My Purpose?

My objective is mostly to help people out there getting started with innovative fields and technologies, and even if you've never tried to write code, or you need a deep math review, I'll give you this kind of basis as well. So, you can be a student, a worker in another field or a manager, and you'll find here everything you need to be prepared for the disrupting and unpredictable transformation of the market and society that will happen for sure during the next years.

My prices: I'm here for you, for free. If you find me helpful in some way, I just ask you to leave a star, click on "watch", and share me everythime you have the occasion to do it. Let's start our journey!

New To Data Science?

Basic Python


Advanced Python -- Coming Soon

Advanced Math -- Coming Soon

Python for Data Science

Math for Data Science -- Coming Soon

Complete Learning Paths

Machine Learning Study Path

Business Intelligence Study Path -- Coming Soon

Cloud Computing Study Path -- Coming Soon


Data Preprocessing

Data Collection -- Coming Soon

Data Visualization

Effective Communication -- Coming Soon

Impactful Presentations

Pragmatic Decision Making -- Coming Soon



Wolfram Alpha




A Lot More Coming Soon!


High Level Topics

1 - Demystification of the key concepts of Artificial Intelligence and Machine Learning

2 - Introduction to ML systems

3 - Introduction to Artificial Neural Networks

Low Level Topics

Chatbots - Build a complex and useful Virtual Assistant with DialogFlow and Flask

Introduction to Computer Vision using OpenCV and Python

Deep Learning in Cloud

Object Instance Segmentation using TensorFlow Framework and Cloud GPU Technology



State-of-Art Papers Explained

About Specializations

You can take them in order or choose the one that fits you the most, but I recommend you to walk through them all at least once.

I've planned two types of Specializations: Hard skills and Soft skills

The former is about technical processes that are the core toolkit for everyone working with data. Working with data is an art form, and the rules of thumb and best practices will help you understand the way to deal with them. You need to develop a "sense" of what to do with the data and this "sense" is primarily driven by the situation and the experience. Because of that, these specializations will be strongly focused on exercises and practice.

The latter is about... everything that's not written in technical books. Use and master them, because they are the real value enabler for you. You can be the best developer or engineer in the world, but if you can't communicate your suggestions and discoveries to your audience, or use data to suggest practical actions in the real world, you're useless for a company.

About Topics

Single topics will be split by field and they can touch real-world applications, methodologies, technological stacks, best practices and more.

About Tools

The Tools section will host several guides about everything you need to know about a particular technology/language/methodology! They will give you a means of thoroughly exploring and mastering the tool at hand.


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