The impact of Data Science in today’s world may be one of the best-kept secrets to people who aren’t in the tech field. It’s been called the “one of the best jobs of the 21st century”, “hottest job of the decade”, and “fastest-growing field in tech”.
According to the US Bureau of Labor Statistics, Data science skills are expected to deliver a 27.9% increase in jobs by 2026. This demonstrates the importance of data science expertise in the coming years. On LinkedIn today, there are 2,59,188 data science jobs available around the world. No doubt, data scientists are in high demand.
With the vast volumes of data generated, Data Science Training or Data Science Certification is an important part of every sector. It is now one of the most intensely discussed subjects in the industry. Its popularity has increased over time, and businesses have begun to use data science tools to expand their operations and improve customer satisfaction.
To start a career in data science, you will need to understand what data science is, what skill set is required, how to learn data science smartly, and which data science courses are the best.
What is Data Science?
Data science is the study of comprehending, interpreting, and applying new methods and techniques to curate useful data and develop procedures for making major business decisions.
In layman’s terms, data science is an interdisciplinary discipline that uses scientific methods, procedures, algorithms, and frameworks to collect knowledge and conclusions from structured and unstructured data. It also uses the same procedure to apply that experience and actionable data through a wide variety of application domains.
Finding the best institute for data science will help you understand how to deal with large amounts of data and use cutting-edge methods and strategies to discover hidden trends, extract valuable data, and make business decisions. To build predictive models, data science uses advanced machine learning algorithms as well.
Fundamental Data Science Skill Set
- Programming Language – Python or R
- Writing SQL series
- Statistics knowledge and techniques
- Basic machine learning
- Data visualization
- Business strategy
Why Learn Data Science?
A significant amount of data is created every day as a result of rapid technological advancements, especially in areas like mobile ads, social media, and website personalization. Because of the sheer amount of data, companies have been forced to become data-savvy and adjust to the new environment or face falling behind the market.
Institutions, both public and private, have recognized the importance of incorporating data science into their operations. This has tremendously increased the demand for data scientists all over the world.
According to a new report undertaken by Indeed, work listings for data scientists had increased by 29% year over year by January 2019. There has been a 344 % rise in job listings since 2013. Data science is the latest catalyst that is propelling a variety of industries and businesses forward.
If you look carefully, you will see that you’ve already used data science in some way. However, a close examination of the work market reveals a scarcity of data scientists. In this work market, the skill disparity between demand and supply is enormous.
The doers see that as a win-win situation because they can still brush up on their skills and take the technological leap to take advantage of this new opportunity. Learning data science and identifying the critical tools and techniques will be a game-changer for those looking for high-quality jobs while also showcasing their exposure and credibility. Thus, to make the most use of current technologies, the world today needs more data scientists.
How to Learn Data Science Smartly?
So, how do you get the best course to learn data science online, and where do you begin your data science education? Starting with linear algebra or statistics, the answer to this question usually consists of a long list of classes to take and books to read. To make it simple and smarter for an average student, here is how one can start.
Analyze Yourself
To learn data science, you must first assess yourself and determine what skills you are supposed to possess, such as programming languages, data analysis, statistics, calculus, visualization, linear algebra, machine learning, and much more.
Advanced mathematics, deep learning mastery, and many other skills mentioned above aren’t necessary initially. You require knowledge of a programming language and the ability to manipulate data in that language.
While fluency in mathematics is required to excel at data science, a simple understanding of mathematics is required to get started. The other advanced skills mentioned above could one day assist you in solving complex data science problems.
Once you are well versed with requirements, you need to have a self-assessment about what you know and what you don’t.
Learn Programming Language
For data science, Python and R are both viable choices in programming languages. While R is more popular in academia and Python is more popular in the industry, both languages have a large number of packages that support data science.
To get started, you don’t need to learn both Python and R. Instead, work on studying one language and understanding the basics of the same.
Learn Data Analysis, Manipulation, and Visualization
You can learn how to use the panda’s library if you want to work with data in Python. Pandas have a high-performance data structure called a “DataFrame” that can be used to store tabular data in various types of columns, just like an Excel spreadsheet or SQL table.
It has tools for reading and writing data, coping with missing data, filtering data, cleaning up messy data, combining databases, visualizing data, and many more. In short, learning pandas can greatly improve data-processing performance.
Learn Machine Learning
Machine learning is a difficult field to master. It is a form of data processing that automates the development of analytical models. It’s a subset of artificial intelligence that focuses on the idea that systems should learn from data, recognize patterns, and make decisions with little to no human involvement.
Machine Learning is a significant step forward from computer science, statistics, and other emerging industrial applications. Through designing reliable and effective algorithms and data-driven models for real-time data processing, machine learning can deliver accurate results and analysis.
Scikit-learn is the most widely used library for machine learning. The enticing aspect of data science is creating “machine learning models” to forecast the future or automatically derive information from data. You need to learn how to use the sci-kit-learn library in Python to do machine learning.
Practice Until You Master
Mastering the world of data science needs a lot of practice. You will need to devote a fair amount of time to programming or other data science projects. You must keep that knowledge intact within yourself. There are plenty of free resources available over the internet; make the best out of those resources. Keep learning.
The Bottom Line
Data is consuming the planet faster than you think, and data science will undoubtedly become one of the most critical things for companies and industries in the immediate future.
This has opened up a slew of possibilities for data scientists, as well as a lucrative career path. This is the perfect time to pursue a career in data science. Get the tools and certifications you need to succeed with a top data science program online right away.
Data science is a field with a high learning curve. Data scientists must be fluent in a variety of programming languages and statistical computations, as well as possess excellent interpersonal and communication skills.
Consider it a rough array of procedures when you embark on your data science quest. You will find that if you do any of the things mentioned in the article right, you will gain data science skills on your own. While in the learning process, you can check on how the industry operates, what positions are available, how employees hire and so on. You just need to be consistent in learning and love data to excel in this field.
