Artificial intelligence and data science are the two most prominent technologies that are presently dominating the world. Data science makes use of AI to perform various operations. However, it does not represent AI completely. Data science is a broad field that acts as an umbrella under which the widespread field of artificial intelligence falls. If you’re interested to know which is easy to learn, data science or ai, then data science is comparatively more straightforward as AI is yet to be thoroughly explored.
Data science is used for transforming data into actionable insights and performing thorough data analysis and data visualization. Artificial intelligence, on the other hand, helps to create new products and brings autonomy to diverse industries so that tasks can be performed automatically without human intervention. Many organizations and companies based on AI provide multiple job positions to professionals such as machine learning engineers, NLP scientists, deep learning scientists, etcetera. On the other hand, data scientists perform various business operations based on data and implement algorithms in programming languages like Python and R.
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What is data science?
Data science is a modern technology that has been reforming diverse industries across the globe. It is responsible for bringing about many industrial revolutions in the recent era. The massive explosion in the amount of data today has contributed to the growth and development of data science. Industries and business organizations rely on data science to make sense of data and to produce better products and data-driven decisions. As a result, the demand for data scientists in the recent day is also skyrocketing.
What is AI?
Artificial intelligence is a subcategory of data science that uses different algorithms for performing various autonomous actions. Artificial intelligence uses software engineering principles and tools to develop solutions to existing business problems. Top tech giants like Amazon, Facebook, and Google are leveraging AI tools and technologies to develop autonomous systems. Artificial intelligence is modeled after natural intelligence, which humans and animals possess.
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Differences between artificial intelligence and data science
- Data science refers to a comprehensive procedure that includes preprocessing, data analysis, visualization, and providing accurate data predictions. Conversely, artificial intelligence refers to implementing predictive models that help forecast upcoming events.
- Data science tools are available in the market compared to AI tools. This makes learning data science easy. As data science includes multiple steps to perform thorough data analysis and generate insights, many tools and technologies are available to assist Data science professionals in their operations.
- The field of data science encompasses different statistical techniques, while artificial intelligence makes use of only computer algorithms. Professionals who do not have knowledge about computers and statistics will find it challenging to make a career in artificial intelligence. On the other hand, data science can be explored by professionals from different educational backgrounds.
- Unlike artificial intelligence, data science activities do not require scientific processes to a higher degree. Although the artificial intelligence domain is quite broad and vast, it is largely unexplored, and this makes learning and artificial intelligence difficult for aspirants.
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Data science versus artificial intelligence which is easy to learn
If you’re confused about whether you want to learn artificial intelligence or data science, the best place to start is to plan the type of career you want in the long run and then decide the type of skill set and corresponding needs required to fulfill the career path. For example, if you want to become a machine learning engineer or artificial intelligence engineer, then you can enroll in a data science certification course with artificial intelligence, where you can develop a strong understanding of mathematics or programming languages, data sets, and analytical and AI tools. On the other hand, if you want to become a data scientist or data analyst, then you can undergo a data science course program where you will hone your skills in programming languages, communication skills for business knowledge, analytical skills, Hadoop, and other data science tools.
If you are interested in business and analytics learning, then going for the data science educational path will be the right choice for you. Also, many data science training institutions and colleges are available in the market today that provide accredited courses to students and enable them to acquire a firm grasp of programming languages, data visualization, data modeling, coding, and algorithms. Both artificial intelligence and data science are leading career choices that have potential opportunities for career growth in the future. Job opportunities in data science are significantly higher than in artificial intelligence, so this field has already entered the mainstream. You can also access plenty of free online resources, tutorials, and blogs to hone your knowledge about the data science domain.
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Data science career vs. artificial intelligence career
For data scientists, AI is a fantastic tool or a procedure that helps them to perform their functions and repetitive tasks. A Data Science professional with knowledge of all data science techniques and artificial intelligence tools such as rigorous classification, deep learning algorithms, etcetera can provide accurate predictions to their organization. Unlike artificial intelligence, data science is a comprehensive procedure. It is easy to learn if you can devote six to seven hours of study every day. An artificial intelligence engineer has to work with numerous subsets like deep learning and machine learning that are complex and difficult to learn. Professionals undergoing rigorous course programs and practicing data science on real-life projects can acquire details and skills quickly.
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Artificial intelligence engineer versus data scientist salary
Salaries for artificial intelligence engineers and data scientists are skyrocketing in the market depending on their experience, companies, and skills required to fill the position. Due to the increasing demand for artificial intelligence engineers and data scientists, these professionals’ salaries are constantly burgeoning. Therefore it is the right time for you to explore the AI and data science industry. You can enroll in certification course programs to hone your knowledge base and skill sets. According to Payscale reports, the average annual salary of a data scientist is INR 8,12,855 LPA, whereas the average annual salary of an artificial intelligence engineer is around INR 15,00,641. The primary job responsibility of a data scientist is to detect hidden patterns and trends in data. They have to work with unstructured and structured data and perform data cleaning, data sources, and data processing to derive business insights. On the other hand, an artificial intelligence engineer’s primary job responsibility is to ensure production autonomy. He or she combines vast data through iterative processing and intelligent algorithms and replicates human intelligence through machines.
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