Question 1

What is Data Science in Artificial Intelligence?

Accepted Answer

Artificial Intelligence (AI) is a domain where algorithms are used to accomplish automatic actions. It is all about machine learning, deep learning etc. and has applications in robotics, automation, etc.

On the other hand, data Science is a subset of Artificial Intelligence. It can be defined as a collection of raw data to analyse using scientific methods, processes, and algorithms. Its applications are advertising, marketing, Healthcare, etc.

Below-mentioned is a comparison between AI and data science that highlights that these are different technologies -

Scope: AI is limited to implementing ML algorithms, whereas Data Science involves various underlying data operations.
Tools: The Tools used in Artificial Intelligence are TensorFlow, PyTorch, and Scikit-learn, and the tools that are used in Data Science are SAS, Python, R, etc
Skills Required: A data scientist must know data analytics tools like R, Excel, Python, Stata, etc. For AI, being an expert in algorithm design is necessary.

Question 2

Why enrol in an Artificial Intelligence course?

Accepted Answer

For building a career in any field, it is vital to have the right qualifications and technical skills. Now, enrolling in a certificate-level course is a great option if you can't devote time to a conventional degree or wish to upgrade your skills.

The AI course generally covers topics such as how to use Python libraries like TensorFlow, Matplotlib, and Scikit-learn, Machine Learning techniques like supervised and unsupervised learning and advanced concepts like artificial neural networks, layers of data, and feature extraction and TensorFlow.

After completing a course in AI, you can grab great career opportunities and work as an Artificial Intelligence Engineer, Data Scientist, Analytics Manager/Lead, Machine Learning Engineer, Statistical Programming Specialist, etc.

Question 3

Who can study an Artificial Intelligence course?

Accepted Answer

The eligibility criteria for enrolling in an Artificial intelligence course differ according to the level of study. In general, you must have completed graduation in a relevant stream of engineering or science. However, if you are from a non-IT background, you can still enrol in a certificate-level course if you have the basic technical knowledge and skills.

The eligibility criteria for enrolling in machine learning and artificial intelligence courses differ according to the level of study. In general, you must have completed graduation in a relevant stream of engineering or science. However, if you are from a non-IT background, you can still enroll in a certificate-level course if you have the basic technical knowledge and skills.

Further, some basic skills required for this course include:

Sound knowledge of Mathematics and Algorithms
Well-Versed With Probability and Statistics
Expertise in Programming Languages
Stay updated and grasp new concepts quickly

Apart from the skills, you must develop familiarity with the tools required for studying AI: CNKT, TensorFlow, theano, and Caffe.

Some of the best artificial intelligence courses available are

Question 4

Why should I get a Data Science certification?

Accepted Answer

Even though it is not mandatory to have a data science certification to become a data scientist, it helps you become credible for your professional journey. It signifies a certain understanding of technology and the candidate's suitability for the data scientist role.

It is a boon for candidates not from a tech background, as these courses cover skills such as exploratory analysis skills, visualization skills, and data mining/machine learning algorithms. Thus, the major benefit of data science certification to the aspirant who has it over someone who is not certified is that they have better chances of being hired for a job, which gives chances of upskilling and a chance to build a project portfolio.

Question 5

What type of job opportunities are there in the Artificial Intelligence field?

Accepted Answer

Artificial intelligence is increasingly widespread and one of the emerging technologies. Thus, professionals specializing in AI are needed now more than ever. The good news is that the AI professional field is full of different career opportunities. You can take on different roles and responsibilities depending upon the position, your experience and your interests. The need for skilled AI professionals spans nearly every industry, such as technology, financial services, healthcare, media, marketing, etc.

The list below includes jobs in AI and some positions that work closely with those in AI roles:

Job title	Average Annual Salary in INR	Average Annual Salary in USD
Machine Learning Engineer	₹9,14,458	$136,404
AI engineer	₹9,64,199	$120,334
Business intelligence developer	₹7,00,000	$100,700
Big data Engineer	₹7,83,496	$109,650

Question 6

Is Artificial Intelligence a good career option?

Accepted Answer

Yes, AI is a good career option because the job outlook for AI professionals is extremely promising. It is rife with so many career opportunities that there are many jobs but too few qualified candidates. On the upside, it offers virtually guaranteed (and well-paying) employment for those with the expertise. According to the U.S. Bureau of Labor Statistics, there will be a 31.4% rise in jobs for data scientists and mathematical science professionals, crucial to AI, by 2030. The AI career is future-proof because it is a component of many cutting-edge, forward-thinking advancements, so aspirants should pursue it.

Question 7

Which is a better course to pursue, artificial intelligence or data science?

Accepted Answer

It is quite a subjective question and makes it difficult to pick the better option from AI or data science. In reality, it depends on individual career expectations, capabilities and interests. A data science course is beneficial if you want to build stronger expertise in implementing statistical and predictive analytics techniques for a career in data analytics. In contrast, the artificial intelligence course would benefit those interested in coding, data modeling, programming languages, algorithms, and visualization who want to become an engineer and create intelligence in software products should opt for AI.

Question 8

Who earns more, AI engineers or data scientist?

Accepted Answer

The average annual salary for AI engineers in India is ₹9,64,199 which ranges between ₹4,61,462 and ₹20,75,817. In the United States, AI engineers earn an average annual salary of $120,329. According to data from Glassdoor, it ranges from $79,446 to $1,82,251. In comparison, the average annual salary for a data scientist in India is ₹11,00,000, which ranges from ₹4,50,000 to ₹24,00,000.

In the United States, the median entry-level salary for a data scientist is $95,000. For a mid-level data scientist, it is $130,000; for experienced data science professionals, it is $165,000. Thus, data scientists earn more than AI engineers.

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