The Rising Importance of Data Science in Today’s World
The quantity of data available to us nowadays is astounding. hence data science plays a more important role than it has ever had.
According to Michael Berthold, CEO and co-founder of data science startup KNIME, “Data science is the art of making sense of data in an increasingly data-saturated world.” With a high pay floor and lots of room for advancement, it may also be a fulfilling career path.
Python is a programming language you might wish to learn if data science is your dream job. Python’s robust libraries, user-friendliness, community support, and versatility make it a vital tool for data scientists. Are you curious to know more? What you should know about using Python for data science is provided here.
What is data science?
The goal of the multidisciplinary area of data science is to extract useful and applicable knowledge from large and complicated data sets. It incorporates elements of AI, computer science, statistics, and more. According to Justice Erolin, CTO of software development business BairesDev, “data scientists use scientific methods, algorithms, processes, and systems to extract insights and knowledge from data.” Informed decision-making and strategic planning for firms are among the main objectives of data science.
A profession in data science can be quite profitable. compensation.com states that the normal compensation range for a data scientist in the United States is between $130,842 and $159,732. The average salary for a data scientist is $145,257. Of course, real pay for data scientist jobs might differ significantly based on a variety of criteria, including your degree of schooling, any other qualifications or experience you may have, how long you’ve been in the field, etc.
This sector of work has a bright future ahead of it. While not keeping a separate tally of data scientists, the U.S. Bureau of Labor Statistics (BLS) classifies them as “Computer and Information Research Scientists.” This category was expected to increase at a rate substantially faster than the average for all vocations, by 23% between 2022 and 2032. The need for data scientists is anticipated to be at the higher end of this growth spectrum due to the growing significance of big data.
Because data science is the basis of machine learning and artificial intelligence, Erolin claims that it is currently a very valuable job path. “You can have a significant impact on the company or on other people’s lives, depending on the role.”
What is Python?
Python is a popular high-level interpreted programming language that is easy to learn and has a lot of adaptability. Since its initial release in 1991, Python has grown to be one of the most widely used programming languages worldwide.
According to Berthold, “Python started out as an easy-to-use and learn programming language for quick prototyping.” “Many features related to data manipulation have been added in recent years, making it one of the two main languages—along with R, which remains the best option for statistical work—in the field.”
Berthold continued, “The majority of the new tools in the AI/ML space have been developed in Python, so working directly with those libraries requires knowledge of the language.” It is important to remember that many facets of data science also call for the use of other languages, such as Javascript for visualization and SQL for data engineering, the author adds.
Using Python for Data Science
If you are willing to practice, learning a programming language is now simpler than ever, claims Erolin. He mentioned that there are many paid and free internet resources available, such as Udemy and YouTube. He continued, “You can also find communities on Reddit and Stack Overflow that can assist you in solving specific problems you encounter.” But according to Erolin, learning happens best when done on the job.
Aspiring data scientists should grasp the essentials, including basic Python syntax, control structures, functions, etc., Erolin added, regardless of where they obtain their knowledge and how they practice. “Next, you would proceed to acquaint yourself with widely used data science libraries like Pandas and Seaborn, which offer instruments for manipulating, analyzing, and displaying data.” He went on to say that from there you could combine data science ideas like machine learning and statistics.
The conclusion
A job in data science can be very fulfilling and demanding if you’re seeking for a STEM profession. According to Berthold, the career path is in high demand and calls for a good dose of imagination because the work varies from project to project and technologies and techniques are always changing.
Data science requires a wide range of abilities and resources, but knowing Python, which is frequently essential to the work, will help you succeed. There are many tools available to help you become an expert in Python and apply it to data science, whether you want to learn it on your own using free online classes or by signing up for a Python bootcamp.
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