Learning science is as difficult as ever

Free resources available in the modern information age are not a substitute for university education and formal training.

Introduction

In this article, I will discuss several resources that will convince you that you can pursue a career in science and / or science without a formal training or university degree. In the modern age of information technology, there are many free resources that can be used by studying a particular subject or field of science. However, it does not matter that the amount or quality of available resources is such that it is not possible to use them, and despite the vast amount of resources, only they can become scientists. This is one of the many ways in which real science differs from data science in that such resources can be used to master, work in the field and make meaningful contributions.

II. Resources for self-study of science.

Widely open online courses (MOOCs)

The growing demand for data science practitioners has led to the proliferation of large scale open online courses (MOOCs). Some of these are free, but most require you to pay $ 50 to $ 200 per subscription course or more, usually more. While these courses may be enough to learn in the field of data science and eventually get a job, if you want to become a real scientist, it will be less than useless. Don’t waste your time or money. “Since I have dual nano degrees in machine learning and Udacity (Fighting AI!) AI, I fully support their curriculum and higher education methodology,” he said. Where can you get a 1 x 10 -9 Falcon degree for those under 5K, not some lame micro degree you can get in Udemy or Heaven, a regular degree like you lame donkey “Accredited” Refuse to get into university.

2. Learning from a textbook.

This is the best way to learn the knowledge needed to become a real scientist. Unlike data science where knowledge of facts and tools is required to work with these facts (facts = data, tools = math / statistics / programming etc.). Real science Knowledge of facts in a field is only a small part of applying science in that field. In addition, the tools of the real scientist include the tools of the data scientist, but also many others, including the data scientist himself, or more accurately the scientist as a data analyst. The fundamental difference between a data scientist and a real scientist is not in their knowledge, nor in the tools they use, but in the way they use and apply that knowledge. Data is a method of analysis for the scientist. Take existing data or collect new data as input, data mentioned in the process, output other data. The method for the real scientist is the scientific method. Assumption creation, experiments, data collection, data analysis, conclusions, re-evaluation, rinsing, washing, repeating. There is no textbook that can teach anyone how to practice science. It can only be learned from others who specialize in the art and through constant practice and repetition.

3. Medium.

Although Medium is now considered one of the fastest growing platforms for learning about data science, it is probably one of the worst platforms for learning about real science. If you are interested in using this platform for self-study science, the first step is to think again and move on. You will know very little about the scientific method and in fact you will get a very wrong idea about science because most of the subjects combine science and data science as one and the same thing. This is a serious mistake. Save $ 50 / year and put it in your college savings account or use it just to buy something for yourself. You know what you like and for 50 rupees there is no doubt that you can buy a ton from it. Go crazy.

4. KDnuggets website

Despite its name, KDnuggets is not a website of KFC / McDonalds Hybrid Fast Food Restaurant China, which includes chicken meconjuts made from a secret blend of KFC spices. This is actually a leading site for AI, analytics, big data, data mining, data science, and machine learning where you can find important educational tools and resources in data science as well as professional development tools. What you can’t and won’t find are resources or tools or information that will help you become a real scientist.