What is the Difference Between Data Science and Applied Data Science
As most businesses are completely data-driven, the rise in opportunities for the data scientists and applied data scientists is expanding across various industries. Although Data Science and Applied Data Science field look similar, there are major differences between Data Science and Applied Data Science. Candidates must look at the differences between the two before choosing one of them.
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- What is the difference between Data Science and Applied Data Science?
- Difference Between Data Science and Applied Data Science
- Focused Areas of Data Science and Applied Data Science
- Data Science and Applied Data Science: Fees Comparison and Course Duration
- Data Science and Applied Data Science: Eligibility Criteria
- Scope of Pursuing Data Science and Applied Data Science
- Data Science Certification Courses by Top Providers
- Conclusion
Data Science and Applied Data Science share overlapping concepts yet differ in focus, applications, and career paths. This article explores the core distinctions between Data Science and Applied Data Science, their fees, scope, job roles, and salary trends. Whether you are an aspiring data scientist or curious about how applied data science fits into the broader landscape, this article will clarify your understanding.
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What is the difference between Data Science and Applied Data Science?
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 versus 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.
Data Science: Data Science is the study of a combination of math and statistics, specialised programming, advanced analytics, artificial intelligence (AI) and machine learning with specific subject matter. The major objective of Data Science is to use methods from computer science, machine learning, and statistics to derive useful insights. The major key skills required for Data Science are Python/R programming, Machine Learning and AI, Statistical analysis, Data visualisation tools (Example: Tableau, Power BI), and Big Data tools (Example: Hadoop, Spark). Also Read: Online Data Science Courses & Certifications
Applied Data Science: On the other hand, Applied Data Science is a specialised subset of Data Science that emphasises implementing data-driven solutions in real-world scenarios. Applied Data Science is about practical applications, ensuring data solutions are actionable and aligned with organisational goals. The major key skills required are Business acumen, Project management, Data integration techniques, Applied machine learning, and Domain expertise (Example: healthcare, retail, finance)
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Difference Between Data Science and Applied Data Science
Data Science is research-orientated, whereas Applied Data Science is implementation-focused. Check the category-wise difference between data science and applied data science in the table below.
Difference between Data Science and Applied Data Science: Category-wise
Criteria | Data Science | Applied Data Science |
Focus | Theory, research, and developing new algorithms | Practical implementation of data-driven solutions |
Key Activities | Data modelling, predictive analytics, and research | Applying data insights to solve real-world problems |
Tools Used | Python, R, TensorFlow, Hadoop | SQL, Tableau, business intelligence tools |
Nature of Work | Broad and exploratory | Narrow and application-specific |
Target Audience | Researchers, data analysts, statisticians | Business analysts, IT professionals |
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Focused Areas of Data Science and Applied Data Science
Before making the choice between the Data Science and Applied Data Science, check the focused areas of data science and applied data science in the table below.
Data Science and Applied Data Science: Focus Areas
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 visualisations 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 Optimising 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, 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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Data Science and Applied Data Science: Fees Comparison and Course Duration
Check the costs and duration of certification courses for Data Science and Applied Data Science vary based on the program type, institute, and delivery mode (online or offline)in the table below.
Data Science and Applied Data Science: Fees Comparison
Course | Fees (Rs. ) | Duration |
Data Science | Rs. 50,000 – Rs. 3,00,000 | 6 months to 2 years |
Applied Data Science | Rs. 30,000 – Rs. 2,50,000 | 3 months to 1 year |
Note: Fees depend on the institute and mode of study.
Data Science and Applied Data Science: Eligibility Criteria
- Data Science Courses: Bachelor's degree in computer science, mathematics, or a related field. Some advanced courses may require programming knowledge.
- Applied Data Science Courses: Basic understanding of data analytics and familiarity with tools like Excel or SQL.
Scope of Pursuing Data Science and Applied Data Science
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.
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. Check the scope, job responsibilities and salary comparison for both the job profiles in the table below.
Scope for Data Science and Applied Data Science
Course | Scope | Job Responsibilities |
Data Science | Research and development in AI and machine learning. Working with large-scale data platforms in tech companies like Google, Amazon, and Meta. Academic roles for advanced research in data science. | Designing and optimising predictive models. Implementing AI-driven solutions. Exploring large datasets for insights. |
Applied Data Science | Solving business-specific problems in industries like banking, retail, and healthcare. Real-time data integration for decision-making. Roles in IT consultancy and analytics firms. | Applying pre-existing data models to specific use cases. Collaborating with stakeholders to meet business objectives. Developing dashboards and actionable reports. |
Data Science and Applied Data Science: Salary Comparision
Role | Data Science Average Salary (Rs. ) | Applied Data Science Average Salary (Rs. ) |
Data Scientist | Rs. 10,00,000 – Rs. 25,00,000 | Rs. 8,00,000 – Rs. 18,00,000 |
Machine Learning Engineer | Rs. 12,00,000 – Rs. 30,00,000 | NA |
Applied Data Scientist | NA | Rs. 8,00,000 – Rs. 18,00,000 |
Data Analyst | Rs. 5,00,000 – Rs. 10,00,000 | Rs. 4,50,000 – Rs. 8,50,000 |
BI Developer | Rs. 6,00,000 – Rs. 12,00,000 | Rs. 5,00,000 – Rs. 10,00,000 |
Source: Glassdoor, Payscale
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Data Science Certification Courses by Top Providers
There are a lot of education platforms who are providing the certifications in Data Science or Applied Data Science. Freshers who want to start their career in this field or working professionals who want to have career growth or switch their career to Data Science can choose these certification courses. Some of the major platforms offering Data Science certification course are mentioned in the table below.
Top Providers offering Data Science Certification Course
Conclusion
As the difference between Data Science and Applied Data Science are mentioned in detail here, 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.
Frequently Asked Questions (FAQs)
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.
Data Science includes data visualisation, 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.
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