Newly developing technologies like Artificial Intelligence, Deep Learning, Machine Learning and , Internet of Things are all part and parcel of Data Science. The future scope of Data Science seems to be crucial for every business today because of the following reasons:
- Mass amount of data to be handled
A large amount of data is collected in each second from online transactions, in-person purchases, social media, and website interactions and so on. Large companies have to collect this data for their business prospects in various ways. This is where the Data Science technologies come in to effect where the structured and unstructured data is studied to draw meaningful conclusion for their business growth.Blockchain technology
2. Blockchain technology
A decentralized, distributed ledger technology that records the provenance of a digital asset is called cblock chain technology in simple terms. This assures the security of data from tampering upto a certain extent.
3. Changing face of Data Science
It is expected that a Digital Mesh is going to become a reality at near future where all the apps, devices, and people will come together to work as a unit.
How Python can be used with Data Science
The open-source, free, easy to learn Python is undeniably the most widely used programming language in Data Science. There are others like R, Java, C++, SQL which are also utilized for data-driven calculations in larger companies, but none of these seem to be near to python in performance. The availability of massive Machine Learning libraries with its simple use is the plus point of Python.
I try to find the answer question asked by general people regarding choosing R or python is more suitable for Data Science field. Some companies are using R for their calculations where the rest are choosing Python as their prominent language for their purposes.
In order to answer this question we should go through a thorough analysis with both of these.
- Python is considerably good in machine learning where R is consistent enough for Statistical modelling.
- Python is favourite tool for developers always since it is flexible and open source language. Its large variety of libraries are used for data manipulations in companies.
- Sincere python is a general purpose language , gained more popularity among people and is recommending to others as well. It is also well known amongst beginners because its syntax is so easy to follow unlike other languages.
- If someone is relocating from their current job to a new one, python is more advantageous for them because a wide area of applications are created using python.
- Python is extensively used in the scientific and research communities because it is easy and simple, which makes it adaptable for people who do not have a coding background.
The most commonly used libraries for data Science are NumPy, Pandas, Series, Dataframe, Matplotlib, Scipy, Scikit-learn.
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Scope of Python in Data Science
In a study conducted in 2018, 83% of the data professionals have suggested Pythonlanguage for data analysis. Data Scientists who are ideally the jack of all trades with the knowledge of Mathematics, Statistics and programming skills, and industry knowledge are the highest-paid professionals.
They are the ones who are highly educated with masters or degree in Ph.D. The other career opportunities in Data Science are:
- Data Analyst
- Machine Learning Scientist
- Data Engineer
- Machine Learning Engineer
- Data Architect
These professionals are in demand in almost every field including government organizations.
Hence, we can say that Data Science using is Python is unbeatable!
Why Do Data Scientists prefer Python for Data Science ?
- Python links between different units of a business and gives a intermediate between data sharing and processing language.
- Graphics used in various data visualization libraries and coll application programming interfaces.
- Python requires data scientists to learn regular expressions, scientific libraries, and master data visualization concepts.
- Python is a two decade old robust, dynamic programming language where you can write code and execute codes without using a separate compiler. This makes Python very flexible and convenient..
- professionals who are not much familiar with web programming concepts can easily learn Python language and pursue data science ,so it is very much popular among data scientists.
Future Scope of Python in Data Science
Python is in large demand always because it is inseparable from the area of Data Science.
When talking about Python with data science.
Most of the Data analyst, Machine Learning and and some other companies in india are using Python because of the following points:
- Python is easy to learn: Python’s main advantage is that anyone can learn it quickly and easily. The language was designed to be simple and effective.
- NumPy and pandas (Python libraries) allow you to read/manipulate data efficiently and easily.
- Matplotlib allows you to create useful and powerful data visualizations.
- Scikit allows you to train and apply machine learning algorithms to your data and make predictions accurately.
- PyMySQL allows you to easily connect to MySQL database, execute queries and extract data from databases
The reason for that I believe is that Python is the only programming language in the world of Machine Learning right now that has so much huge community support as well as that is so easy to learn. Anyone who knows coding can be familiar with the python syntax within few hours.
Scope of Python in data science will increase in near future because of
- Large volume of data to be handled
- New Block chain technology
- Advancements in data science
Python and R are both doing jobs well in data science but Python outweighs R in terms of
- Good in machine learning
- Open source language
- General purpose language
- Widely used in a variety of applicatons
Job roles can be handled by a person who is proficient in Data Science are
Different libraries used in Data Science are
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