Career in Artificial Intelligence and Machine Learning
Artificial intelligence (AI) and machine learning (ML) are two of the most trending fields these days. Generally, AI and ML are used interchangeably; however, there is considerable difference between the two. In this blog, we will look at these differences. There is no doubt that AI and ML offer one of the most promising careers and are the highest-paying sectors now. This is one of the reasons why AI is included as a degree in many institutions. Other than universities and colleges, there are many private institutes that offer short-term courses in the fields of AI and ML. Engineering students can appear for GATE 2025 in Data Science and Artificial Intelligence for M.E. or M.Tech in AI and ML. A degree from a reputed institute like IIT or IISc can add a lot of weight to your resume. Apart from higher studies, various PSUs also recruit through GATE exam
MADE EASY offers online and offline classes to students preparing for GATE, ESE, and PSU. Students can prepare for GATE 2025 in Data Science and Artificial Intelligence form live online classes offered by MADE EASY.
A career in artificial intelligence and machine learning these days can lead to a higher position in the future, as this sector isn’t saturated yet, so career growth here is easier in comparison to other sectors and jobs.
Machine Learning
Machine learning is a subset of artificial intelligence that gives machines the ability to make decisions, make predictions, and learn automatically from past data and experiences with minimal human intervention. It doesn’t require explicit programming.
For example, chatbots, predictive texts, suggestions on search engines, OTT apps, etc. are all possible with the help of machine learning. What ML does here is just observe the patterns and give suggestions on later encounters.
ML derives the necessary information from large amounts of data and different algorithms to identify patterns and learn in a repeated manner. The various algorithms use guessing methods to learn directly from data rather than using any predetermined set of equations or formulas. As ML algorithms use previous patterns and data, their performance gets better with an increase in the number of samples.
History of Machine Learning
The term machine learning was introduced by IBM Engineer Arthur Samuel in 1959; however, the first machine learning model was introduced in 1950 by Arthur Samuel when he predicted the winning chance in checker for each side.
Arthur Samuel defined machine learning as a branch of study that helps computers learn without doing explicit programming.
The period of 1960–80 was the period in which fundamental algorithms were developed. Decision-based algorithms were also developed at that time. During 1980–1990, knowledge-based approaches were becoming popular, where knowledge was encoded rather than learned from data.
In the 2000s, big data came into play, where a large amount of data was present, and it enabled more complicated and accurate machine learning models. Nowadays, machine learning is present mostly everywhere in the form of virtual assistants, autonomous vehicles, etc.
Career in Machine Learning
As stated above, ML is one of the trending technologies nowadays. The continuous learning curve of ML offers great opportunities in various sectors. A strong skill set in ML can lead to various popular and high-paying jobs such as machine learning engineer, data scientist, NLP scientist, business intelligence developer, etc.
A career in machine learning can help an individual be a part of the digital revolution and can lead to higher positions in the upcoming future. All the FAANG companies [Facebook (Meta), Amazon, Apple, Netflix, and Google (Alphabet)] hire ML engineers on a regular basis. Apart from the IT sector, various automobile companies also hire ML engineers for the maintenance of machine learning algorithms, the design of autonomous driving systems, etc.
A good ML expert requires a lot of skills; some of them are mentioned below:
- Applied Mathematics and Statistics
- Computer science fundamentals such as data structure, algorithms, space and time complexity, etc.
- Programming languages like R, Python, Java, etc.
- Libraries like Numpy, Panda, Matplotlib, Tensorflow, etc.
- ML Algorithms
- Data modeling and evaluation
- Neural Network
- Natural language processing
These are some of the skills required by ML experts; however, the skillset can be increased depending on the role and industry.
The salary range depends on the type of industry and the skill set an individual possesses. According to various research and surveys, the initial salary of an ML engineer in India ranges from 3 LPA to 10 LPA, which increases depending on the skillset and the level of experience.
Artificial Intelligence
Before going further, let us first discuss what AI is. As evident from the name, AI is a combination of human intelligence and the artificial world. A more clear definition of AI would be that it is the technology that helps to inculcate human-like intelligence into machines like computers, which helps to minimize or remove human interference in various tasks and problems.
Although this word is often used to describe a variety of modern technologies, many people disagree on whether they belong to artificial intelligence. Instead, some claim that much of the technology utilized in the real world today is actually very advanced machine learning, which is only the first step toward true artificial intelligence, or “General Artificial Intelligence” (GAI).
History of Artificial Intelligence
The history of artificial intelligence goes back to the 1930s, 1940s, and early 1950s, when the idea of thinking machines became prevalent. The research work of scientists like Alan Turing, Claude Shannon, and Nobert Wiener strengthens the idea of an “electronic brain.” The term artificial intelligence was first introduced at the Dartmouth Conference in 1956. However, during 1970–80, the development of AI stopped due to multiple reasons, like a lack of funds and computing powers, etc. In the 1980s, an AI program named “Expert “Systems” was adopted by organizations. At the same time, the Japanese government heavily funded AI with fifth-generation computer projects. Again, by 1987, lots of companies had failed in AI, and it was considered that the technology was not viable. However, this time, some research continued despite the criticism. In 1993–94, AI revived again with the help of advancements in computational techniques and the availability of large data sets. In 1997, an AI-based chess game called “Deep Blue” drew the world’s attention when it beat world champion Garry Kasparov.
In 2005, a robot developed by Standford won the DARPA Grand Challenge by driving autonomously for 131 miles along an unrehearsed desert trail. These successes motivated the scientists to research more, and thus the AI sector started gaining pace.
Careeer in Artificial Intelligence
Career in AI offers various roles such as AI/ML developer, data scientist, AI research assistant, AI software engineer, AI Chat-bot developer, AI consultant etc. The salary for each role depends upon the skills and the industry an individual is employed. Companies like Google, Open AI, IBM, Microsoft, Amazon, NVIDIA, Facebook, Intel etc. hires AI specialist on regular basis with lucrative salaries and lots of perks. Generally, the initial salary for an AI specialist starts from 3 LPA, with no upper limit which means individuals can earn money in the proportion to their skills and experience level.
To become a good AI expert one needs to have a certain skillset some of which are mentioned below:
- Programming languages such as Python, Java, C++, R etc.
- Data Modelling and engineering
- Big Data Analysis
- Machine Learning Model
- Cloud Based AI services
- AI security
These are some skills which are required to be an AI expert. However one can learn other skills depending upon the nature of job. Apart from technical skills, some non-technical skills like problem solving ability, communication skills, team management etc. are also required by both AI and ML experts.
AI and ML are in trend but that does not means the path is very easy or cakewalk. It requires lot of dedication and hard-work However with right guidance and strategy one can make a wonderful career in these technology.
MADE EASY Publications Books:
Those students who are preparing for GATE 2025 in Data science and Artificial Intelligence can refer the books from MADE EASY Publications. These books are well structured and are designed by renowned experts, having vast industrial experience.
- A Handbook for Computer Science IT Engineering
- Computer Science and Applications
- GATE/PSUs : Computer Science
Must Read:
FAQs:
1. How to start a career in artificial intelligence?
Answer: The best way to start a career in AI is to obtain an UG degree in AI and ML.
2. Is artificial intelligence a good career in India?
Answer: AI is a trending technology all over the world, it offers handsome salary and a good career.
3. Is automation and robotics a good career?
Answer: Those who aspire to be robotics engineers can have a wonderful career in robotics and automation. These are in demand and a rapidly growing field with applications in various other sectors.
4. Is AI is a high paying job?
Answer: AI is a good sector to work in. The salary grows as per experience and skill set.
5. What salary one can expect after learning AI?
Answer: The salary depends upon the industry, skill set and experience level. Generally the starting salary is from 3 LPA.
6. How ML is different from AI
Answer: ML is subset of AI. One need to learn Ml before learning AI.
7. Which are the top recruiters in AI?
Answer: Companies like Google, Facebook, Amazon, etc. are top recruiter in AI.
8. How one can do M.Tech in AI from IIT and IISc?
Answer: Those who want to pursue on AI from IIT and IISc can appear in GATE 2025, Data Science and Artifical Intelligence.
9. Is ML is a good career option?
Answer: ML is one of the trending technologies in the world. It offers one of the best career option nowadays.
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