Data science and artificial intelligence are in everybody’s ears these days. Most people use these terms synonymously, which creates confusion among prospective candidates. Even though both are entirely unfamiliar concepts, people still find it difficult to differentiate.
Both fields are new and still in their developmental stages. That’s why people are perplexed by these terms. A lack of knowledge about these fields is a serious issue for people who want to make a career in data science or artificial intelligence.
In this blog, we will understand data science and artificial intelligence. We will help you discover which career is best for you. Before we delve into the difference, let’s understand what these terms signify.
Data science vs. artificial intelligence: An overview
Data science deals with extracting insights from a large volume of data. We detect trends and patterns to derive meaningful insights. These insights are used by organizations and businesses to increase profits.
Artificial intelligence refers to building a program that can think like human minds. A scientist attempts to imitate the human mind and actions, such as thinking, acting, learning, and problem-solving. For instance, Apple’s Siri, Google Now, and Amazon Alexa are popular examples of AI.
In simple words, data science is extracting insights from unsupervised data, while artificial intelligence builds programs similar to humans.
Data Science vs. Artificial Intelligence: Skills Required
Whether you have to do analysis or create an AI program, there are certain skills you must have. Some skills are common in both fields, while others vary widely. These are skills you must master:
- Statistical analysis and computing
- Deep Learning
- Programming languages (Python, R, and Java are the most necessary)
- Linear algebra and statistics.
- Signal processing techniques.
- Neural network architectures.
Data Science Vs. Artificial Intelligence: Roles and Responsibility
To understand which career suits your skills, it’s important to know the roles and responsibilities of each one of them. Let’s find out!
Data science is all about data cleaning, data processing, data wrangling, and data visualization. Roles and responsibilities also revolve around data processing:
- Identify the problem and collect the relevant data.
- Clean, transform, and explore data before analysis
- Use data analysis tools to generate the insight
- Identity patterns, trends, and correlations in the larger data set
- communicate insights in a compelling way
Artificial intelligence is more concerned with building a program that imitates human intelligence. Therefore, as an AI engineer, your roles and responsibilities include:
- Create intelligent algorithms for better learning.
- Build infrastructures of leading AI frameworks
- Test and deploy models
- Take care of all the AI needs
- Develop APIs that are scalable, flexible, and reliable to integrate data products and sources into the application
Data Science vs. Artificial Intelligence: Opportunities
One of the key factors in deciding whether a career is the right fit is knowing the future opportunities in the field. Although both career options are promising, there is a slightly higher demand for AI engineers/specialists. Let’s have a look at the data!
According to Statista, the global big data market is predicted to grow to 103 billion US dollars by 2021. Meanwhile, the AI market forecast says it will hit 126 billion US dollars by 2025. Therefore, the demand for AI specialists is slightly higher than for data scientists.
Both careers have huge scope and future opportunities.
Data Science vs. Artificial Intelligence: Salary
Salary is deciding whether the field is worth putting effort into. We will compare the average salary packages of the fields. Depending on your expertise, the average salary in data science ranges from Rs 3 lakhs to Rs 25 lakhs per year.
At the same time, an artificial intelligence engineer earns around 7.8 lakhs per year. This average figure means that if you have experience and expertise in the field, your annual salary will be around Rs. 25 lakhs.
Both fields are in developmental stages. Thus the average salary is only going to increase exponentially.
Which one to choose – data science or artificial intelligence?
Whenever you have to decide which career option is best, consider two factors: your skills/capabilities and the demand for the field.
Before coming to any conclusion, you must analyze your skill set and experience. If you can handle big data, and organize and conclude meaningful insights, then you should opt for data science. Choose artificial intelligence if you are good at programming and coding.
Another deciding factor is to look for opportunities and the future scope of each field. Below is a chart that compares data science vs. artificial intelligence to help you decide which one is the right career option for you:
ML and Deep learning
Recognize patterns and trends in data.
Make autonomous data model
Does not require a high level of technical knowledge
Requires high level of technical and programming knowledge
Popular Python and R
Tensor flow, Keras, Kaffee
Approx. 9 Lakh INR (per year)
Ranges between 6 lakhs to 25 lakhs per year.
AI professionals are in higher demand when we talk about salary and opportunities. But this doesn’t mean data science isn’t a good option. The data scientist also has vast opportunities. You can choose whichever suits you best.
“Data science or artificial intelligence—which one is the best option?”
The answer depends on your skills, abilities, experience, and, most importantly, your preferences. Interpersonal skills are the key factor that will help you determine which career option is best for you.
And if we talk about factors like salary, opportunities, and future scope, artificial intelligence tops all these criteria. We elaborated on every factor that will help you choose a career option.