Artificial Intelligence (AI) is a fast-growing field with limitless potential to transform various industries and improve our everyday lives. If you are someone who is attracted by technologies and problem-solving, starting a career as an AI engineer can be an exciting and rewarding choice.
As you are new to this field, you might not be fully familiar with the term AI or how to pursue a career in AI engineering after 12th grade.
That’s why we are here to help you by providing all the information you are seeking to achieve your career goals in the field of Artificial Intelligence.
In this article, we will explore a complete guide on what AI is and how to become an AI engineer after 12th in 2024-25.
What is Artificial Intelligence?
According to John MC Carthy, the father of AI “The science and engineering of making intelligent machines, especially intelligent computer programs”.
Let me explain this in simple terms
The term AI is composed of two words {Artificial (A) + Intelligence (I)}
The term Artificial refers to “man-made” and the Intelligence stands for “thinking Power”, and when we combine AI it means “a man-made thinking power”.
Is the meaning of AI clear now? If not, let’s understand further!
It is a branch of computer science in which we can create intelligent machines or systems that behave like a human, think like humans, and make decisions.
Artificial Intelligence refers to the ability of computer systems to copy human behaviour. Machines with AI capabilities can learn from past data and actions, make corrections, and perform human-like tasks.
We hope that by now, you have a clear understanding of what AI is and how it functions, let’s dive in to more details!
Types of AI
There are two main types of AI: Narrow AI and General AI.
Narrow AI, also known as Weak AI, is designed to perform specific tasks and is highly proficient in those areas.
Examples: Speech recognition systems can perform only one task related to speech and image recognition systems can only perform on the prompt related to images.
MidJourney is an image generation AI and Google Assistant for voice recognition.
On the other hand, General AI, also referred to as Strong AI, is an advanced form of AI that possesses the ability to understand, learn, and apply intelligence across a wide range of tasks and domains, much like a human.
Example: Sophia a social humanoid robot. Sophia’s architecture is made up of scripting software, a chat system, and OpenCog, an example of an AI system developed for general thinking and referred to as Artificial General Intelligence (AGI).
Interested in Computer Science?
Learn – Best courses in Computer Science After 12th
How to Become an AI Engineer After 12th?
AI has become one of the most trending career options after 12th as 97 million new roles is expected to be created by 2025 due to AI and automation, according to the World Economic Forum.
Read the given steps carefully on how to become an AI Engineer after 12th:
Core Command in Math, Physics & Computer Science
Start by completing your Higher education with a focus on subjects such as Mathematics, Physics and Computer Science. These subjects provide a solid foundation for your future studies in AI engineering.
Pursue a Bachelor’s Degree
You can enrol in a bachelor’s degree program such as B.Tech in AI, or BSc AI along with relevant fields such as computer science, information technology, or data science. This will provide you with in-depth knowledge of programming, algorithms, data structures, and other essential concepts.
Students interested in gaining admission in the top artificial intelligence colleges in India can take various AI Engineering Entrance Exams conducted by renowned exam conducting authorities and universities.
Acquire Programming and Data Skills
Develop proficiency in programming languages such as Python, R, Java, or C++. Additionally, learned data manipulation and analysis techniques, as working with large datasets is a fundamental aspect of AI engineering.
Specialize in Artificial Intelligence
During your bachelor’s program, focus on courses that delve into artificial intelligence, machine learning, and data science. This specialization will equip you with the necessary skills and knowledge to work as an AI engineer.
Candidates can go for short term certification programs in AI & machine learning while pursuing their full time degree, some of the popular short term certification courses are given below:
- AI For Everyone by Andrew Ng
- Introduction to Artificial Intelligence (AI) by IBM
- Machine Learning Fundamentals by UC San Diego
- Introduction to Machine Learning with Python
- Artificial Intelligence MicroMasters by Columbia University
- AI Product Manager Nanodegree
- Advanced AI: Machine Learning and Neural Networks
Gain Hands-on Experience
While theoretical knowledge is important, practical experience is equally crucial. Engage in projects, internships, or part-time jobs that allow you to apply AI concepts and work with real-world datasets.
This experience will enhance your problem-solving abilities and give you valuable insights into the industry.
Pursue Advanced Studies
Consider pursuing a master’s degree in artificial intelligence, machine learning, or a related field. This advanced degree will deepen your understanding of AI concepts, expose you to the vast field of research, and open up higher-level job opportunities.
Stay Updated with Emerging Technologies
AI is a rapidly evolving field, so it’s essential to stay abreast of the latest advancements. Follow industry publications, attend conferences, join AI communities, and engage in online courses to stay updated with emerging technologies, tools, and best practices.
Build a Strong Portfolio
Create a portfolio that showcases your AI projects, research work, and practical applications. This will demonstrate your skills and abilities to potential employers and increase your chances of landing a job as an AI engineer.
Example: You can make a portfolio on Wix.com, Canva.com, Google Blogger, Adobe.com, Reddit, and WordPress in a freemium model.
Network and Collaborate
Network with professionals in the AI industry through online platforms, meetups, or conferences. Collaborate on projects and participate in hackathons or competitions to expand your professional network and gain exposure to different AI applications.
Example: You can publish and collaborate with your projects on these websites GitHub, LinkedIn, Kaggle, Keystone, Devpost, and AI Stack Exchange.
Seek Job Opportunities
Once you feel confident in your skills and knowledge, start applying for AI engineer positions in companies or research institutions.
Always remember that learning is a lifelong process, so continue to upgrade your skills, explore new AI techniques, and stay curious about the latest developments in the field.
What does an AI Engineer Do?
AI engineers work to design and develop intelligent systems that can learn and make decisions. They use their expertise in programming, data science, and machine learning to build AI models and algorithms.
As an AI engineer, your work involves collecting and preprocessing data, selecting appropriate models, training them using large datasets, and optimizing their performance.
AI engineers also evaluate the models’ accuracy and validate their effectiveness in solving real-world problems. They continuously refine and improve the models based on feedback and new data.
AI Engineers have been Working in the Following Fields
- AI engineers are innovating chatbots that can answer customer queries and solve issues without requiring human participation. These chatbots are skilled in datasets of customer interactions, and they can also learn to understand the variation of human language.
- They are developing algorithms to help doctors identify diseases more accurately. These algorithms can receive information on large datasets of X-ray and patient records, and they can learn to identify patterns that would be difficult for humans to see.
- AI engineers are using machine learning to detect false transactions in financial services. They are trained on datasets of fraud and legal transactions so they can learn to identify patterns that are linked with fraud.
Qualifications For AI Engineering
To pursue a career in AI engineering after 12th, certain qualifications and skills are generally required. Here are the key considerations:
Educational Background
A strong educational foundation is essential. Most AI engineering roles require at least a bachelor’s degree in a relevant field such as computer science, information technology, mathematics or engineering.
Some employers may prefer candidates with advanced degrees like a master’s or Ph.D. in AI, machine learning or a related discipline.
Mathematics and Statistics
AI engineering involves working with complex algorithms and models, which require a solid understanding of Mathematics and Statistics.
Key mathematical concepts include linear algebra, calculus, probability theory, and optimization techniques. Proficiency in these areas enables you to develop and analyze AI models effectively.
Data Science and Machine Learning
Knowledge of data science principles and machine learning algorithms is fundamental for AI engineering. Familiarity with concepts like supervised and unsupervised learning, regression, classification, clustering, and feature engineering is necessary.
Practical experience in applying machine learning algorithms to real-world problems is highly valued.
Skills for an AI Engineering
Programming Skills
Proficiency in programming is crucial for AI engineers. You should have a good command of programming languages commonly used in AI, such as Python, R, Java, or C++. Familiarity with frameworks and libraries like TensorFlow, PyTorch, sci-kit-learn, or Keras is also advantageous.
Problem-solving and Analytical Skills
AI engineers need strong problem-solving and analytical abilities. They must identify patterns, devise efficient algorithms, and troubleshoot issues arising during AI model development and deployment.
Critical thinking and creativity are important for designing innovative solutions.
Domain Knowledge
Depending on the industry or application domain you work in, having domain-specific knowledge can be advantageous.
Understanding the challenges, and specific requirements of domains like healthcare, finance, e-commerce, or autonomous systems can enhance your ability to develop tailored AI solutions.
Top AI Colleges in India
In India, many government and private engineering colleges offer UG and PG courses in AI. Below is the list of top colleges in India offering Artificial Intelligence courses:
- Indian Institute of Technology (IIT), Roorkee
- IIT Banaras Hindu University (BHU)
- IIT Guwahati – Indian Institute of Technology (IIT), Guwahati
- Indian Institute of Technology (IIT), Hyderabad
- BITS, Pilani
- National Institute of Technology (NIT), Karnataka
- SRM Institute of Science & Technology, Chennai
- University of Petroleum and Energy Studies (UPES), Dehradun
What is the Salary of an AI Engineer?
The salary of an AI Engineer depends upon the skills and work experience of the individual. In India, the average salary for an artificial intelligence engineer is 1,500,000 rupees per annum.
The starting salary for entry-level positions is ₹900,000, per annum while the average yearly salary for experienced personnel is ₹3,000,000 rupees.
| Company | Experience | Salary (INR) |
|---|---|---|
| Intel | 1-4 Years Experience | 15.0L- 30 LPA |
| TCS | 1-7 Years Experience | 3.8L-15 LPA |
| Tata ELXI | 1-4 Years Experience | 4.5L- 12.5 LPA |
Real-life Example of AI
Artificial intelligence has become the integral part of modern technologies and it is being used across various industries to enhance the user’s experience.
Some of the common examples of AI, used in our day to day lives, are as following:
- Chatbots for customer support
- Recommendations from Amazon, YouTube, and Netflix
- Self-driving vehicles
- Robotic vacuum cleaners
- Manufacturing robots
- Smart home devices
- Siri, Alexa, and Watson
- Virtual travel booking agents
- Social media monitors
- Automated healthcare management apps and systems
- Search engines
- Natural Language Processing (NLP) tools (e.g., GPT-3)
- Online financial investing
Top Recruiters in AI
Below is the list of top companies working in the field of AI and proving job opportunities to the graduates:
- Google (DeepMind, Google AI)
- Microsoft (Azure AI)
- Amazon (AWS, Alexa AI)
- Facebook (Meta AI Research – FAIR)
- IBM (IBM Watson)
- Apple (Siri and Machine Learning Teams)
- Nvidia
- Intel (AI and Data Center Group)
- OpenAI
- Tesla
- Baidu
- Oracle
- SAP
- Accenture
- Infosys