One of the most known and practically applied fields in most industries to learn and analyse their products and businesses is Data Science. On the other hand, applied data science has a wide scope of data science. However, there is a bit of difference between Data Science and Applied Data Science.
Data science is a subpart of applied data science to some while for others, both terms are interchangeable. Data science is the extraction of data to create a visualization, forecast, or manipulate the data accordingly.
Data science consists of the entire data lifecycle whereas applied data science narrows the focus to the practical application of data science techniques and methodologies to solve domain-specific problems. Applied data science emphasises the execution of data-driven solutions to address specific challenges.
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One can get a job in Data Science and Applied Data Science by doing a Data Science Certification course. These Data Science courses are worth it for those who want to evolve their career in this field. Read on to understand applied data science vs data science, What is applied data science? and the major difference between Data Science and Applied Data Science, along with online Data Science courses, their scope, and more.
Before understanding the difference between Data Science and Applied Data Science, let us explore the focused areas of Data Science for better understanding. These focused areas will help aspirants choose the best online Data Science courses and Applied Data Science courses wisely. Also, it will clarify the difference between Applied Data Science and Data Science to an extent.
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Focused Areas of Data Science | Focused Areas of Applied Data Science |
Data Mining- Data mining is a methodology of data science used to extract the raw data and relationships found to make decisions as per the needs. | Researching New Algorithms- Just like in software development, there are many algorithms to sort the data. However, the selection of the algorithm depends upon the time complexity and arrangement of data and so, the same happens in data science too. |
Data Visualisation- It is another aspect of data science that helps in creating visualizations based on the analysis and needs of the business. | Researching New Applications- There are still many applications undiscovered where data science can be applied. |
Time-Series Prediction- This is a way of forecasting the data using historical data and finding out the mathematical relationship between the data. | Making Conventional Algorithms Faster by Optimizing Mathematical Functions- Mathematics and statistics are important while learning data science. For faster implementation, a better mathematical function is required rather than using previous conventional mathematical functions. |
Data Cleaning and Transformation- In database management, storing a lot of data can be cumbersome to read and analyse. Data cleaning is one of the focused areas of data science which removes the noise from the database and helps in analysing the data easily and can be transformed accordingly. | Creating New Predictions- Even after using so many algorithms, predictions are not fully accurate. They lack seasonality and trends. Applied data science research on creating new predictions too. |
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Most young minds in India are not updated with the rapidly transitioning changes in the field of computer science, owing to which learning is a little bit slow. Like in the COVID-19 pandemic, many non-technical individuals lost their jobs because businesses went down during that period.
However, software engineers were able to sustain themselves by working from their homes. In the coming time, there is going to be a boom in the jobs in the Data Science and Applied Science field. As the number of learners increases, the applications of the fields increase.
There are many Data Science certificate and Applied Data Science certificate courses online. Some of the best platforms to opt for the best Data Science courses online are Coursera, Udacity, edX, and Udemy. One can opt for online data science courses from these platforms based on their needs and international validity.
As for international validation of the Data Science certification courses, Coursera is the best among all. There are so many deals present on Udemy and other platforms for online Data Science courses.
To pursue online Data Science courses, it is preferred to have a mathematical background. As data science is completely based on mathematics and statistical functions, learning through data science certification courses will be helpful. Without the knowledge of mathematics and statistics, you will fall behind.
Other than this, Python and the R programming language are best known as data science tools. With the knowledge of these tools, the Data Science certificate and Applied Data Science certificate courses will be easier for you to accomplish. These tools will also help you in many aspects other than Data Science. Python is used in web development, software development, game development, and data science.
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Do you want to know what is all about applied data scientist vs data scientist? There are several job opportunities in the applied data science and data science fields as they both are interchangeable technical words in organisations. Careers in data science include Data Scientists, Senior Data scientists, Lead Data scientists, Data scientists in Computer Vision, Data scientists in Image Processing, and many others.
Conversely, some of the popular jobs in applied data science include Applied Data Scientist, Senior Applied Data Scientist, Lead Applied Data Scientist, Applied Machine Learning Engineer, Research Data Scientist, Applied Scientist, and others.
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There are numerous jobs in the field of data science. The average salary of a data scientist in India is Rs. 919,777 p.a. Compared to data scientists, software engineers have an average salary of Rs. 666,249 p.a. in India.
This clearly shows that the profile of a data scientist is bound for growth and upcoming data scientists can expect exceptional pay in exchange for their services.
Machine Learning - It is one of the most hyped technologies in the world. Every technologist must have heard about machine learning. It is the technology that uses data science and mathematical functions to evolve better learning and optimising the models.
Many supervised and unsupervised algorithms in machine learning enhance the training and learning model. Using statistical models, machines learn the behaviour. Using classification and regression algorithms, data can be predicted.
Artificial Intelligence - AI is a technology that makes machines behave like human brains. Using learning and training models, statistical functions are adjusted and after training behave like a human brain but with less accuracy than the human brain.
Market Analysis - This is another field where data science is widely used. If an organisation has to find out the analysis of its sales and revenue from previous years, data science creates the visualization for the same. Using data science, organisations can check where they lacked customer satisfaction in previous years.
Big Data - As the data increases with time, difficulty in managing and extracting information from the data also increases. Big data analytics certification is a field that analyses data and deals with large and complex datasets.
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As you have learned the difference between Data Science and Applied Data Science, it is clear that Data Science and Applied Data Science are related fields to some extent. However, they differ in their focus and objectives. Data science uses the latest technology and this technology will not fade until there is no data left to collect.
Data scientists have a huge impact on the success of any business. If you want to be a data scientist, then start learning, get a professional data science certificate, and begin with extracting insightful data from the datasets. Whether it is finance, manufacturing, or IT services, data science will certainly help in the success of your business.
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Data Science is one of the rapidly evolving industries with great career opportunities. As interpretation and analysis of data have become indispensable for almost every company, this field will surge exponentially and pave enormous career scope for data science professionals.
Different fields of data science include data visualization, data mining, forecasting, and analysis of data. Other than this, database management and data cleaning are other fields of data science that are widely used now.
Online platforms like Coursera and Udacity provide professional certificates in data science.
There are no such prerequisites but for best learning, a bachelor’s degree with a mathematical background will be preferred.
Completing an applied data science online course certificate is worth considering future aspects and learning.
Data science courses can be learned from home as many online platforms are providing online data science courses with credibility, which is valuable across the industry.
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