Introduction
Data science covers a huge field that has tons of points to enter on the basis of the point you wish to start from. People often start to learn elementary data science with languages such as R, and then eventually discover the problems and limitations. Python definitely wins the competition for being the best for data science. Once you are ready to take up the next venture in your journey of data science, you can move on to Python.
Utilizing Python to get into data science is probably the quickest, easiest, and most interesting method of getting into data science. Undoubtedly, it makes up an extremely valuable skill, that offers a high salary as well as enough job satisfaction. Note that there are several companies who still post multiple job listings looking for data scientists making the profession extremely in demand.
Stepping into the data science world with the help of Python has many reasons— the language is used by several FAANG-adjacent organizations for doing data science, offers great versatility as a language, easy to learn for coding beginners as well as expert coders.
Although Python is usually considered a general-purpose language, there are some solid and practical reasons to learn Python with the explanation of Python’s importance in data science.
There exist several different methods of implementing data analytics, but Python became extremely popular and reasonably so. Python is clearly a powerful language offering ease of learning and implementation.
Reasons to Learn Data Science
Data analytics basically revolves around problem-solving abilities. This involves analyzing the data on hand in order to use it for solving problems that you face at the moment or anticipate facing in the near future. Among the major advantages of learning data science is the liberty to work in your choice of field. Each industry boasts of a unique group of the present as well as future problems. Data science comes up as the only way to sort them out. This is the reason all industries are always hiring data scientists and you have the choice to pick the ideal one among them. You are not going to get this liberty to choose in any other field.
However, data Science has not just cropped up as a current trend, it will rule the future. While you begin to plan your career opportunities, it is imperative to research not only the present but also the future prospects. At the moment, all industries are facing a dearth of data scientists. Businesses are keen to hire quality people for these positions but are not able to get candidates qualified enough. Learning data science at this point is going to begin your journey towards a very lucrative choice of career. Let us look at your reasons to learn data science with python course.
- Easy Learning
Python can be considered one of the simplest languages for learning easily. Even if one has absolutely zero coding background, learning the language can not be hard. A major problem that holds interested candidates back regarding the choice of working as a data scientist is not having any coding skills and a false notion of difficulty to learn the same. No one can face such a problem while learning Python.
- Quick Development
As you start dealing with vast quantities of data, an important factor is speed. A slow language may potentially make processes incredibly slow. Python is very easy to work with a language that requires very few coding lines. This cuts down the time required for coding significantly. The slow execution of the language was the reason holding it back from total acceptance. Nonetheless, ever since the Anaconda platform was introduced, this complaint is dealt with accurately.
- Strong Packages
Python offers users a wide range of packages which include NumPy, PyBrain, SciPy, Pandas, and so on, which makes the work of coding complex data analytics problems incredibly easy. There also exist several libraries which are backing the merge of Python with different languages like C or SQL. This decision will aid Python further to make it even stronger.
- Community Backing
One of the reasons for making Python an easy language for learning and understanding is the strong support of the community. In case you are stuck with a problem, you might seek help from this community which will be happy to help you. Along with this, several people in this community are also dedicated to creating new packages continuously for a number of uses. Given the increasingly popular backing of Python to use in data science, several such packages are underway for being used by data scientists.
- Better Visualization of Data
Visualization is crucial for data scientists because this helps the professionals analyze this data better. Because of libraries and APIs like Plotly, Python is appropriately equipped for helping you to create stunning visuals. It is also possible to integrate tools for different big data visualization through Python. All these reasons add to the usefulness of Python for data scientists.
- Hadoop Compatibility
Hadoop is the most used open-source site for big data and is perfectly compatible with Python. A Python package called PyDoop allows you to access the Hadoop API. This enables you to write programs for Hadoop using Python. This package will also let you write codes for complicated problem solving with much lesser effort.
Conclusion
Once you have decided to start your professional life while considering the various paths open to be taken, you can undoubtedly consider the field of data science along with Python training. Today, it stands among the most desired professional options which can potentially set you towards a well-paid and exciting profession.
