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Python For Data Science

Python is an important skill that the current industry demands in every data scientist. Learning Python for
data science is a necessity and can add a lot of value to your resume!
Get started now and enroll in the course at Learn Digital Academy.

What is Python programming? What is the main use of Python for data science?

Python is a high-level programming language created by a Dutch Programmer Guido Van Rossam in 1991. It is an interpreted language, meaning it has an interpreter to execute programming directly without depending on machine languages.

It is used in software development, application development, data science, system automation, machine learning, and more. Python for data science is widely used for big data processing and mathematical computations.

Python code syntax uses simple English language which makes it easy for anyone to learn and understand it. Learning Python can exponentially increase your chances of getting hired and income in a matter of months. Learn Python for data science in a matter of weeks at Learn Digital Academy.

Python has a broad range of uses which includes but not limited to – 

  • Back end (or server-side) web and mobile app development
  • Scripting language for the desktop app and software development
  • Processing big data and performing mathematical computations
  • Writing system scripts (writing instructions that tell a computer to “do” something)

YouTube, Instagram, Dropbox, and Quora are some of the platforms among many that use the Python programming language. Because of its simplicity, it can help you develop functions with much less text and simpler commands than most programming languages.

Why should you learn Python for Data Science?

Readability is an important feature of this popular programming language. That means anyone can learn it easily. Even if you do not have a background in coding, you can pick it up with proper training. Coders and developers swear by this language and they enjoy using it as well. So hop on to Learn Digital Academy and learn Python with our data science master course.

If you’re wondering why you need to learn Python, here are the reasons –

It comes with Graphics and Visualisation

Python comes with many visualization options like matplotlib. It provides a solid foundation around which other libraries like Seaborn, pandas plotting, and ggplot have been built. The visualization packages will help you make sense of the data, create charts, graphical plots, and web-ready interactive plots.

Data science is a stable industry that’s not going to crash anytime soon. Given the highly competitive nature of the job market today, learning Python Data can be highly beneficial for your career and help you upskill to meet the current industry’s standards. It may not be easy but it’s certainly a step towards better career prospects. We provide python for a data science course that’s beginner and pocket-friendly. Learn from the best in Bangalore.

There’s a high demand for Python programmers

As of now, there are more than 68,000 vacancies in Python Programming jobs in India. This is because of a gap in the skill-sets and less knowledge about the scope of Python. People are not aware of the benefits of learning Python and they think it’s a hard language to learn. But that’s not true and learning Python data comes with a lot of benefits. Since it is applied for various purposes, you can work in different fields and get a good salary. This brings us the next point –

Multiple choices for data science libraries

Another good reason to learn Python is that it offers a wide range of choices for data science and data analysis libraries. Some of them are NumPy, Pandas, SciPy, StatsModels, Scikit-learn. When you learn Python, you will find that it offers different solutions to problems that were previously unsolvable.

Great salary packages 

Because there is a high demand for Python developers, employers pay a good sum of salaries to them. An average salary for an entry-level data scientist or data analyst skilled in Python Programming earns about 5 lakhs per annum with less than one year of experience.

Scalability

Python enables data scientists to solve problems from multiple approaches. It also gives them flexibility, thus facilitating scalability. It’s also much faster than other programming languages like Matlab, R, and Stata

It’s easy and faster to learn 

Beginners and professionals who have very little time can learn it easily and quickly. It’s one of the reasons why learners prefer Python for Data Science. Python has a shorter learning curve compared to R due to its easy to understand syntax.

Our Python for Data Science course includes -

python basic programs

Course duration - 1 month

  • Introduction to Python – Learn the basics of Python, why it’s used, where it’s used, and for what it’s used. Learn how to use Python for big data processing and how to apply it for problem-solving. Also, learn how to use Python for Machine learning and implement machine learning algorithms,
  • Python data model – Learn how to use python to store, access, and manipulate data in lists, which is the first step to working with huge amounts of data. 
  • Control Flow in Python
  • Files & Exception Handling
  • Object-Oriented Python
  • NumPy
  • Function, Generators & Iterators – Learn how to use functions, methods, and packages to efficiently leverage the code that Python developers have written. You will learn how to reduce the amount of code required to solve problems faster and efficiently. 
  • Data manipulation – Learn how to import data, clean it, calculate statistics, and visualize the data using Pandas and strengthen your Python knowledge. You will also learn how to use Pandas for data analysis

Learn how to use Seaborn for statistical plots, how to use SciKit-learn for machine learning tasks, and how to use spark for big data analysis.

We provide affordable, intense Python for data science training in Bangalore. We provide offline and online training classes. Learn without a career break from our experienced industry professionals.

HOW TO GET STARTED

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