AI vs Data Science: Mapping Your Career Path

Table of Contents [show]

Introduction

Data science and AI, two career paths sometimes cross one another. Data science uses AI and its many components, including machine learning and deep learning. But AI-ML depends on data science practices to ensure high-quality, ML algorithms. Data science is an integrative field that often incorporates the knowledge of AI and ML. Also many AI careers, like AI engineering, need data scientist skills. Structured and unstructured data are the building blocks of AI. Data science is mostly used in machine learning, deep learning, and other branches of AI. A data science expert should be able to understand the complexities of AI. So AI professionals should ideally have a solid understanding of data science. Many digital technologies and applications utilize the skill set known as data science. 
Many disciplines of the digital workforce can be established upon a foundation of data science education. Read on to know what is data science and what is AI, and what are the differences between the two. 

What is Data science?

Data Science is a broad process that includes pre-treatment, analysis, and visualization. Then it comprises prediction and generating understanding. It is the study of data to pull valuable understanding for business. It combines various disciplines to evaluate huge data. Disciplines like statistics, Artificial Intelligence, and computer engineering. This meaningful data helps Data analysts to respond to various business questions. 

What is AI?

Generally, the Artificial Intelligence method works by consuming huge amounts of labeled training data. Then analyzing the data for correlations and patterns. AI uses these patterns to make predictions about business decisions. The replication of human intelligence by computer systems is defined as artificial intelligence. Speech recognition, natural language processing, and machine vision are some good examples of AI applications.

Map Your Learning Path

The career path you choose to take must be supported by your learning path. To see the skill sets you will need for each of those careers is one strategy to map your learning path. Assess your skills and interests next. Look for professions that best suit your qualifications, appropriate abilities, and interests. Then go for educational initiatives that can provide you with those abilities. Think about the level and type of education that companies need for these positions.

AI vs Data Science Jobs and required skills

The best way to start is by choosing the career that is best for you. Then attempting to meet the required skill set of that career path.Many times you are uncertain of the career path to choose AI vs Data Science. It is better to analyze the required respective skill sets for each path. Then you can decide the career option that best suits you.

The following are the in-demand job posts in the field of AI vs. Data Science. You can focus on skills and interests by understanding the job requirements and the organization’s qualifications for your career path.

• Big Data Engineer/Architect

It develops and plans the whole big data environment on Hadoop and Spark. Holding experience in data visualization, data mining, and data migration is an essential requirement. Also to have demonstrated experience with C++, Java, Scala, and Python required to grow. It's crucial to work backward to develop the abilities required for your career, whether it's in AI or data science. 

• Machine learning engineer

It requires a deep understanding of programming languages, analytical skills, and mathematical tools. It also needs a good understanding of data sets and development tools. Many firms are also in search of candidates who are having master's or doctorate degrees in mathematics or computer science.

Our Learners Also Read: Explain Top 10 Digital Marketing Tools

• Business intelligence developer

Strong understanding of BI tools. & Data science is an essential requirement for this career path. Along with the above, excellent communication, and problem-solving abilities, and the capacity to analyze complicated data sets to identify market trends helps Business intelligence developers flourish.

• Research Scientist

A research scientist must know multiple streams of AI, including applied mathematics, machine learning, computational statistics, and deep learning. This is one of the most desirable positions in the artificial intelligence field. It requires strong knowledge of parallel computing, graphical models, and ML. Also, NLP, distributed computing, and reinforcement learning skills are needed.

• Statistics scientist

A good understanding of big data platforms like Hadoop, Statistical analysis is important for this path. Along with the above platforms analytical skills and business, knowledge is also required.

Artificial Intelligence vs Data Science Salary

According to various websites, the salary of Data Scientists starts at 10 LPA and may rise to about 30 lakhs per annum. On the other hand, AI Engineers earn approximately 15 lakhs per annum. This amount may increase to about 50 lakhs per annum. However, depending on experience, performance, job location, and company salaries may vary. Hence data science vs artificial intelligence salary cannot be summed up based on one factor.

Conclusion

Since they are two distinct fields of study, one cannot compare two domains to determine which is superior. However, it is evident, the popularity of data science today cannot be disclaimed. Almost all organizations depend on data to make their business decisions. Data has become an integrated part of businesses. On the other hand, AI or ML is still in an evolving stream that is yet to be adopted by some industries. Considering this, AI technologies will have more demanding significance shortly. Hence, there will be equal demand for experts in data science and artificial intelligence jobs. AI and data science are interconnected. So specialization in either field requires a working knowledge of the other. To begin using ML-AI, studying data analysis is more necessary than understanding data science. No business or firm would be able to run without data science. So, if you're ready to go down this path, your efforts will be amply remunerated with a rewarding profession, salary, and also job stability.

About The Author: