What is the best method of learning data science ? Though you can learn data science on your own, you will need to gain practical experience working on live projects.
If you want to learn the practical aspects of data science, then you should preferably join a good institute which will provide you practical training on data science. If you want to learn data science in Mumbai, you can find more details about our course from the link below.
First lets try to understand what are the characteristics of a data scientist and what are the skills needed to become a data scientist.
We can define data scientists as professionals who, using large volumes of information of different types, solve business problems and obtain answers from data.
Although there are no typical data science projects, since each project is different, companies generally start out with a structure similar to this:
- It requires solving a business problem or answering a question.
- The data scientist should obtain data from the source to solve that question. Here structured data comes into play (eg: databases like SQL), unstructured (eg: images, audios) and semi-structured (eg: texts with a certain structure). In companies that are starting, generally only structured data is used and it is accessed by a typical query language such as SQL.
- A series of techniques, algorithms, etc. are applied on these data. trying to solve the case. Tools like Python, R, SAS, etc. are used here.
- The final result obtained can be an analysis, a combination of a statistical model, business results, etc.
- First, there is something called “Hacking Skills”, which involve computer skills, manipulating data, command line, programming, and so on.
- Second, there is knowledge of mathematics and statistics. It is not necessary to have a doctorate in mathematics or statistics to be a good data scientist, however, it is necessary to have a certain command of basic concepts of statistics and know how to interpret the algorithms that one uses.
- Finally there is business knowledge. Just as important as knowing which algorithm to use or how to program it is knowing what business questions you want to solve, what adds value and what doesn’t, or to what extent the problem you want to deal with may be viable.
These three types of skills are what a good data scientist should have. The first thing a data scientist should know is how to program, as well as having some command of SQL.
The steps that I recommend to get into data science are the following:
- Learn to program in R or Python. Python is preferred as it is more general purpose and learning programming concepts is relatively easy. Some knowledge of how to use the command terminal is also very useful .
- Learn the basics of SQL and statistics. It is not necessary to have extensive knowledge to start as a data scientist, but concepts such as measures of dispersion, centrality, or hypothesis tests are very useful.
- Learn about machine learning algorithms and start programming them, using open public data, competitions, etc.
For people who do not know how to program and want to get into data science, it is good to start with a programming language, preferably a general-purpose one like Python. R and Python are the two most used languages in data science. R is widely used by mathematicians and statesmen, while Python is more used by profiles that come from engineering.
Between the two languages Python is more versatile than R and the concepts learned are more applicable to other types of programming languages. It is true that perhaps at first it may be somewhat more difficult than R, but in the long run it is worth it.
After learning both these languages, you still need to implement these on live projects. Internships can help. Otherwise you will need to join training institutes which provide you with valuable experience and projects.