Data Science, Machine Learning, and Artificial Intelligence are all subsets of Information Technology that have become significant sectors of work thanks to the developments in the IT industry over the past few decades. Even though these streams may sound similar and their functionalities do share some similarities, they are quite different in terms of career preparation and scope of work. If you choose to educate yourself in Artificial Intelligence, you will not be able to pursue a career in data science without again going through rigorous education.

When it comes to the differences between Data Science, Machine Learning & Artificial Intelligence, it is essential to consider that these fields have less and less in common, the more you delve into them. So, it would be best if you made a very proper conscious choice to make sure you choose the career path that you will be able to stick with for the rest of your life. For high school graduates, it is difficult to draw that conclusion immediately so, to help you make your choice, here is a comparative study between these career choices and where they can lead you in your career.

Comparative Study Between Data Science, Machine Learning & Artificial Intelligence

• Data Science

As a career path, data science has two entry points. You can join as a data science engineer who is skilled and knowledgeable about the developmental and deployment skills required to implement data science solutions. Engineers work with enormous amounts of data and use algorithms to sort the data and create information out of them, which can then be used to solve the required problems. The engineers require very vast knowledge and skills in the field of coding, including mastery of various coding languages such as C, Java, and Python

The other way for you to enter the stream of data science is as a data scientist. Data scientists are professionals that have studied pure mathematics, statistics, and other general study courses extensively to gain all the necessary knowledge needed to conceptualize and solve computational problems and help retrieve, collect, and transform large amounts of data. Since they are not engineers, data scientists do not require mastery of coding languages; however, being familiar with particular languages and framework technologies related to the field of work is necessary for the job role.

• Machine Learning

Machine learning is another great career choice that is most suited for students with an engineering background. Students that come from non-engineering backgrounds can also be placed, but the job roles will not be equal or even similar. As an ML engineer, your job will be to handle huge amounts of data, sorting and creating valuable solutions out of the data using algorithms that you would have to design yourself or know how to use. And finally, when the solutions are made, you would have to learn and automate the process of data extraction and resolution by teaching it to the computer. This process solves business problems and automates the solution for future requirements.

For non-engineering students, a career in machine learning can be a bit tricky, given that the entire focus of work for machine learning is programming and mathematics. If you really want to pursue machine learning, the best thing for you would be to learn to code and have a working knowledge of coding and other framework technologies to get better placements.

• Artificial Intelligence

A career in artificial intelligence requires students to have profound knowledge and understanding of programming, mathematics, statistics, and algorithms. This career path is also best suited for engineers as an AI engineer is the most common job role in the AI industry. You have to create automated solutions to problems and use data to solve business problems daily using your programming skills. You will also need to develop new algorithms and deploy the AI solutions you design for businesses. The job responsibilities of an AI engineer are varied, and it very much depends on the project they are working on to define what they are most needed to do adequately.

For non-tech students who are not even educated in mathematics or statistics, you can crack the AI industry as conversation designers who help chatbots create human-like responses to user questions. Chatbots are an essential tool for branding nowadays. Big companies are working hand-in-hand with writers to develop a very human-like feel for their chatbots to ensure customers get the feedback/answers they need without feeling like they are speaking to a robot.

Final Thoughts

Choosing a career in any of these streams of IT can be an excellent choice for your future, given that this industry is growing exponentially, and it will make your future steady. However, since these fields are very scholarly, you need the proper education to get to the top of these IT industries. The appropriate guidance from your formative Bachelor's degree that properly guides you toward a career in AI, ML, and data science can be crucial in deciding your future success. So, for proper career guidance and the best educational platform, you should choose JIET DAT, which is one of the best/top technological colleges in Rajasthan. Their dedicated AI, ML, and data science B.Tech degrees can surely help you get the right start needed for your career in the AI industry.