Data Science and Machine learning are the buzzwords of the IT sector. Python is the most common programming language which is being used by a large section of the IT employees due to its simplicity, flexibility, and other advantages.
(These have been discussed in our previous blog: )
Before moving further let us understand in simplistic terms the difference between Data Science and Machine Learning.
What is Data Science?
It extracts meaningful information from structured and semi-structured data.
They are used to gain insights.
It contains the entire universe of data.
Algorithm statistics and data processing are taken care of.
Data Science is undoubtedly a broad discipline.
Skills required for Data Science:
" Statistics
" Data visualization
" Data mining and cleaning
" Understanding programming languages, like Python
" Data Science tools
What is Machine Learning?
It makes computer to learn through data, without the need to be programmed.
They are used to make predictions and classify the result.
It utilizes the data science techniques to learn about the data.
It is focused on algorithm statistics.
Machine learning is like a subset of data science.
Skills required for Machine Learning:
" Statistical modeling
" Data evaluation
" Fundamentals of Data Science
" Data architecture design
" Techniques of text representation
What makes Python a good choice for data science and machine learning?
The open-source, free, and simple-to-understand Python is without a doubt the most widely used programming language in the field of data science. Others, including as R, Scala, Java, C++, and SQL, are also used for data-driven calculations, although none appear to be in direct competition. Lets have a look as to what makes it so-
1. Easily comprehensible-
Python is easy to understand, since most of the language takes English structuring into consideration. Hence, the language can be quickly learned and easily grasped within some time.
2. Higher-pay package-
Python is a data science tool and is also helpful in machine learning, and both these technical buzzwords hold an advantage over the future. They will probably fill the positions of future jobs offering a heavy payment to the employees.
3. Libraries & Frameworks-
Python has numerous libraries for different needs, e.g., SciPy for Data Science and Flask for web development. TensorFlow and Pandas for machine learning.
4. Security-
The Python language is secure due to the OWASP Python Security Project.
5. Flexibility-
Python is also known as the forgiving programming language as it provides the advantage to the user of ignoring or adjusting some of its errors.
6. Open Source-
Python is an open-source community developed language. As a lot of people are using it on a regular basis, and it has a pool of specialists who are ready to help the users facing any doubts or difficulties. This language also keeps on evolving, incorporating changes.
7. Automation-
Python is useful in automating mundane tasks &writing scripts.
According to a Kaggle survey from 2018, 83 percent of data professionals use Python to analyse data.
The highest-paid professions are Data Scientists, who are know-it-all with understanding of mathematics/statistics, programming skills, and industry knowledge.
Data scientists using Python can land jobs in:
" Scientific and mathematical computing
" Machine learning
" Web development
" Finance and trading
" System automation and administration
" Computer graphics
" Basic game development
" Security and penetration testing
" General and application-specific scripting
" Mapping and geography (GIS software)
The IoT Academy is one such platform where you can explore the various facets for Data Science, Machine Learning & IoT. With dedicated mentors you can aspire for a dream job in one of the above mentioned domains.
