If you want to start your journey as a data scientist, Python is the programming language you begin with.
Data Science and Python are quite inseparable. Where Data Science involves the management of data getting created at a high variety and volume, Python is the tool which aids in managing that data.
Python is easy to learn, quicker to grasp, and very closely associated with the English language. It the most common programming language and can be learned in just 45 days, from our
Python training courseAccording to a study conducted by business broadway, 93% of data scientists prefer Python as their choice in programming languages. The rest go for SQL and R.
Now, lets explore some further reasons as to why Python is suitable for machine learning and data science,
Data scientists must solve complicated problems, and the problem-solving process consists of four primary steps: data collection, cleaning, exploration, modelling, and visualization.
Python offers users with all of the tools they need to complete this process efficiently, including dedicated libraries for each stage
1. Flexibility-
If any new updates come in the way, Python will be the first to adjust. So, this language is the one which solves problems quickly and efficiently.
2. Libraries and frameworks-
A lot of manual labor is saved with the existence of Pythons libraries and frameworks.
Most of the libraries cater to Data Analysis and Machine learning. These include:
“ Panda
“ NumPy
“ SciPy
3. Community based-
Python is open sourced and has a huge community support, so in case of any problems or difficulties, a panel of specialists will always be present to guide the learners. This support from specialists is going to guide the learners efforts in the right direction.
4. Web Development-
Python started its journey from serving the web development process. If we compare PHP and Python for the given purpose, then codes will be created in a few hours from PHP but will only take a few minutes when created using Python.
Pythons frameworks for web development include:
“ Django
“ Pyramid
“ Web2py
“ Turbo Gears
“ Flask
“ Bottle
5. Automation-
Python comes with some automation frameworks, having advantages like:
“ Even if you have no prior experience with Python, working with Unittest will be a breeze. It is a derivative, and its operation is comparable to those of other xUnit frameworks.
“ Individual experiments can be carried out in a more basic manner. The names should simply be written on the terminal. The output is very concise, making the structure suitable for running test cases.
“ It takes milliseconds to generate test reports.
These automation frameworks include:
“ UnitTest
“ Lettuce
“ Behave
6. Low entry barrier in ML and AI industry-
In the ML and AI industry, there is a lot of data that needs to process in a convenient and efficient manner. Python is the language that aids the process through its simplicity.
7. More readable and good visualization-
In the AI, ML industry, the data needs to be presented in a comprehensible visual format and Python is there to serve the purpose.
8. Simplicity-
This point has been reiterated enough and forms the basic reason for choosing Python for data science and Python for machine learning. Its easy-to-understand and simple nature provide it an advantage to be the most commonly used programming language.
In order to make it more convenient for you, here we have arranged certain
online courses on Python, which have a good reputation of being taught by industry experts having 7+ years of experience.
