AI vs ML: What is the difference between AI and ML? Which one will give more salary after 12th?

AI vs ML Difference: Be it children or adults, these days everyone has started using AI. Artificial Intelligence is used a lot in studies to make office projects or extract data. After 12th, most of the students now prepare to take admission in the Computer Science course. In this, both AI and ML are taught. There are many big differences between AI, i.e., Artificial Intelligence, and ML, i.e., Machine Learning.

Before establishing a career in either AI or ML, one should know many details, including the difference between these two, the jobs available after the course, and the salary. This will help you choose the best career option. AI is a broad branch of making machines intelligent, while ML is a part of it, which focuses on learning from data. Basic concepts of ML are taught in the AI course, and there are also more options for well-paid jobs in it.

Difference between Artificial Intelligence and Machine Learning
Artificial Intelligence (AI) and Machine Learning (ML) are related, but there are many differences between them:

Definition of AI and ML
AI: It is a broad branch of computer science. It focuses on providing human-like intelligence to machines. This includes developing the ability of machines to think, make decisions, and solve problems. Examples: chatbots (such as ChatGPT, Grok), voice assistants (Siri, Alexa), or autonomous vehicles.

ML: It is a subset of AI that gives machines the ability to learn from data and improve their performance. It does not require explicit programming. Machine learning (ML) allows algorithms to make predictions or decisions by analyzing data patterns. Examples: Netflix's movie recommendations, spam email filters.

What is the scope of AI and ML?
AI: Broad scope. Apart from ML, it includes other techniques such as neural networks, natural language processing (NLP), robotics, and expert systems.

ML: A part of AI. It focuses on data-based models such as supervised, unsupervised, and reinforcement learning.

What is the purpose of AI and ML?

AI: Making machines autonomous and intelligent so that they can work like humans.

ML: Enabling machines to learn from data and get better at specific tasks (such as prediction, classification).

Examples:

AI: Tesla's self-driving car, which makes decisions on the road.

ML: YouTube's recommendation system, which gives suggestions based on the videos you watch.

Which should you make a career in after 12th, AI or ML?

It is possible to make a career in both AI and ML after 12th because ML is a part of AI. You can also gain proficiency in ML along with specialization in AI.

1. Educational Qualifications and Courses
There are many types of courses in AI and ML:

Degree Courses:
B.Tech/B.E. in Computer Science, AI, Data Science, or ML: This is the most popular option. Many IITs, NITs, and private institutes like VIT, SRM now offer specialised B.Tech programmes in AI and ML.

B.Sc. in Data Science/AI: Some universities offer bachelor's degrees in Data Science or AI.

Other related fields: After a degree in Electronics, Mathematics, or Statistics, you can do a Master's (M.Tech/M.Sc.) in AI/ML.

Entrance Exams:
JEE Main/Advanced (admission to IITs/NITs for B.Tech).

BITSAT, VITEEE, or other private institutes' entrance exams.

Some universities offer admission based on 12th marks.

Skill Development
Programming Languages: Python, R, Java.
Tools: TensorFlow, PyTorch, Scikit-learn.

Math: Linear Algebra, Calculus, Probability, Statistics.

Online Courses: AI/ML courses on Coursera, edX, Udemy (e.g., Andrew Ng's ML course).

Job Options in AI and ML

There are many types of jobs available in AI and ML:

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