In an era where you have more information (not the accurate ones always), most professionals and students are stumped when they search for Data Science jobs and the set of programming languages they need to know to excel in the industry. With innumerable programming options to choose from, ranging from the basic Java to the highly complex Python and SQL, it’s really hard for professionals to zero onto a data science course that would deliver on value, and return on investments.
So, what should one do?
8 out of 10 data scientists would recommend starting with a basic Python Data Science course. This is the most sophisticated and widely-accepted programming language.
We bring you five reasons why choosing Python Data Science course is a better option for professionals today.
Popularity as the Number One Programming Language
Recently, according to an IEEE article, Python has overtaken C++ and Java as the most popular and widely accepted datascience programming language in the world. Though built in the same vein as C++ and Java, Python has a slightly charming demeanour. It is extremely popular with the economists, physicist, mathematicians, statisticians and even Nobel Laureates like Paul Romer, a co-winner of the 2018 Nobel Prize in economics.
Main Stream AI/ML Programming Language
Data is the oil all data science projects run on. To drive any AI/ML algorithm accurately, they need meaningful data modelling, visualization and wrangling. Python data science help professionals get there very quickly. And, the industry professionals agree to it.
Python remains the most popular and, in most cases, the stepping stone to building a career as a Data Scientist.
Apart from the perennial demand in the web development projects, the use of Python is only growing to grow as AI/ML projects become more main stream and popular with global businesses.
Python is Open Source
It’s never been this easier to understand how machine learning and AI with data science could produce results. Yes, a part of that success with Python is attributed to its open source community. If you choose a Python Data Science course, you can learn a lot more with the open source community that keep building cool, savvy and interactive machine leaning and AI resources week on week.
Technical Aspects: UX and GUI
GUI programming in Python could edge out all other programming languages very soon. It could make Python data sciencecourses the most basic electives for professionals to make a career as both analysts and data scientists. Together with quick solving techniques and traditional Python-based applications, data scientists can further contribute to the popular libraries, including pygame and piglet.
It’s all in the Details
Python data science course could set the ball rolling for business intelligence and analytics team that easily earn more than the contemporary sales and marketing groups. With Python empowering the reasoning and logic behind techniques, it is easier to justify that spend on resources.
Python has some of the most complex data libraries for mining and analytics. The sheer size of libraries makes it harder to collate details and apply them logically in a problem. With a reliable Python data science course, professionals can leverage automation, AI/Machine learning to manipulate multidimensional arrays and matrices.
Python learners also need to understand an extensive compilation of mathematical functions for performing various calculations and their applications in completing technical computing tasks, including for plotting various charts and graphs, relevant to businesses.
If you are looking at a long-term success with data science courses, it’s best to start with Python. As competition in the job market grows bigger and edgier, it’s only going to push more professionals into picking the most contemporary Python datascience course over the older courses. We can certainly see Python making greater inroads into AI. Voice-based search, machine learning and Natural Language Processing projects that currently drive our smartphones, search on internet, automation and of course, Autonomous vehicles!