Why Choose Python as a Career??

Python is an easy-to-use programming language that encourages you to get surefire accomplishment with the projects you make. Python is one of the top three programming languages in the world and is poised to become the most popular, according to ZDNet. In fact, according to the PYPL Index, Python is the most popular programming language worldwide, so if you want to work in a different country, you have a good chance of landing a job in, say, Switzerland or Australia. Where would you like to work? Adding Python to your skill set could be your ticket to anywhere.

Python Top modules

• Data Science
• Machine Learning
• Artificial Intelligence
• Python with Django
• Rest API in Python
• Python Basics
• Python Advance
• Business Analyst with Python
• Data Analyst with Python
• Data Engineer

Thus, after completing the Python Course, you’ll have Ample Job Opportunities and a Great package if you learn Python. If you want to learn Complete Python Course, High Technologies Solutions is one of the best Python Training Institute in Delhi.

Earning Potential

Python is a highly demandable computer language, and ample job opportunities according to INDEED. If you have one year of experience as a data scientist, your starting salary is ₹6,98,413. An entry-level data scientist can earn around ₹500,000 per annum.

Support from Renowned Corporate Sponsors

Programming languages grow faster when a corporate sponsor backs them. For example, PHP is backed by Facebook, Java by Oracle and Sun, and Visual Basic & C# by Microsoft. Python Programming language is heavily backed by Facebook, Amazon Web Services, and especially Google.

Google adopted the python language in 2006 and has used it for many applications and platforms since then. Lots of Institutional effort and money have been devoted to the training and success of the python language by Google. They have even created a dedicated portal only for python. The list of support tools and documentation keeps on growing for python language in the developers' world.

Use of Libraries in Python Program

As we write large-size programs in Python, we want to maintain the code’s modularity. For the easy maintenance of the code, we split the code into different parts and we can use that code later ever we need it. In Python, modules play that part. Instead of using the same code in different programs and making the code complex, we define mostly used functions in modules and we can just simply import them into a program wherever there is a requirement. We don't need to write that code but still, we can use its functionality by importing its module. Multiple interrelated modules are stored in a library. And whenever we need to use a module, we import it from its library. In Python, it’s a very simple job to do due to its easy syntax. We just need to use import.

TYPE OF PYTHON: -

There are two major Python versions- Python 2 and Python 3.

• On 16 October 2000, Python 2.0 was released with many new features.
• On 3rd December 2008, Python 3.0 was released with more testing and includes new features.

HISTORY OF PYTHON: -

It was initially designed by Guido van Rossum in 1991 in the Netherlands and developed by Python Software Foundation. Python was named after the BBC TV show Monty Python’s Flying Circus. It was mainly developed for emphasis on code readability, and its syntax allows programmers to express concepts in fewer lines of code.

PYTHON LIBRARIES

1. TensorFlow: It is an open-source library used for high-level computations. It is also used in machine learning and deep learning algorithms. It contains a large number of tensor operations.
2. Matplotlib: This library is responsible for plotting numerical data. And that’s why it is used in data analysis. It is also an open-source library and plots high-defined figures like pie charts, histograms, scatterplots, graphs, etc.
3. Pandas: Pandas are an important library for data scientists. It is an open-source machine learning library that provides flexible high-level data structures and a variety of analysis tools. It eases data analysis, data manipulation, and cleaning of data.
4. NumPy: The name "NumPy" stands for "Numerical Python". It is a commonly used library. It is a popular machine learning library that supports large matrices and multi-dimensional data. It consists of in-built mathematical functions for easy computations.
5. SciPy: The name "SciPy" stands for "Scientific Python". It is an open-source library used for high-level scientific computations. This library is built over an extension of NumPy. It works with NumPy to handle complex computations. While NumPy allows the sorting and indexing of array data, the numerical data code is stored in SciPy. It is also widely used by application developers and engineers.
6. Scikit-learn: It is a famous Python library to work with complex data. Scikit-learn is an open-source library that supports machine learning. It supports variously supervised and unsupervised algorithms like linear regression, classification, clustering, etc. This library works in association with NumPy and SciPy.
7. PyTorch: PyTorch is the largest machine learning library that optimizes tensor computations. It has rich APIs to perform tensor computations with strong GPU acceleration. It also helps to solve application issues related to neural networks.

There are many more libraries in Python. We can use a suitable library for our purposes. Hence, Python libraries play a very crucial role and are very helpful to developers.

High Technologies Solutions is one of the best python training institutes in Delhi, with 20+ years of experience in Python Course Institute. 100% Job Assistance, Online and Offline Classes Available.