Exam Date: 05 Feb, 2021 - 07 Feb, 2021
Declaration of Result: 22 Mar, 2021
Artificial Intelligence is a unique career path that can lead you to success. Today there is growing concern over the fact that artificial intelligence is going to snatch away existing jobs. We cannot change the course of progress. But we can adapt ourselves with the changing nature of the job-world. True that AI is going to replace many jobs, AI itself will need development, maintenance and sales. Artificial Intelligence courses are therefore going to be a life-saver in the future.
When it comes to Artificial Intelligence, people generally think about Sci-fi. However, in real life, artificial intelligence is completely different. There is so much work to do in the background to make an AI system perform somewhat efficiently. From feeding the system the initial logic, if-this and algorithms to charting out a neural network - there are a lot of things that are to be done to make the system say something meaningful or do something useful. Artificial Intelligence is not magic. People have to work on it. Where there is work - as high profile and important as this - there will be a glittering career prospect around it.
Artificial Intelligence: Degrees & Levels
Courses on Artificial Intelligence are offered as B.Tech courses in India. One can further delve deeper into the intricacies of AI and opt for the M.Tech course too.
Undergraduate Level (4- year course) - B.Tech Computer Science with a focus on artificial intelligence is a course aimed at the class 12 pass-outs. This is a comprehensive course on artificial intelligence. The AI course involves the basics of artificial intelligence and Machine Learning (ML) as well as the advanced and practical aspects of AI and ML. Along with this, the B.Tech Artificial Intelligence course also includes the topics that are there in the normal computer science course - like - JAVA, C, electrical and electronics engineering, database management, design, operating systems etc.
Postgraduate Level (2-year course) - After the undergraduate course in Artificial Intelligence, you can also go for a postgraduate course in artificial intelligence. The PG in AI offers a more comprehensive study on artificial intelligence and machine learning.
Online Certification Courses - Today with the advent of so many edutech companies, learning online has become a breeze. When it comes to learning computer science courses online, it is quite worth it. Computer science courses do not require such practicals that require special types of machinery. You just need to have a computer. There are many reputed online edutech organisations that offer AI certification courses. Some of these courses are offered by Google, MIT or Stanford University.
There is, however, one issue. When it comes to robotics, you need special equipment for practical projects. And working with special equipment is not possible online. So, online edutech institutes can be of great value when it comes to the theoretical and computer-based practical aspects of the subject. However, in order to be industry-ready, you must look for offline courses that allow you to tinker with specialised equipment.
Minimum and Maximum Duration of Artificial Intelligence Courses
M.Tech in computer science with a specialisation in artificial intelligence is a 2-year course with 4 semesters. Some universities offer the course tailor-made for AI and ML. Others offer optional AI subjects with the usual M.Tech curriculum.
Since B.Tech and M.Tech courses are standardised courses in India, there is no variation in the duration of the B.Tech course- be it in any discipline. No institute can offer a B.Tech course having less than 4 years of duration- at least, not the accredited ones. Similarly, M.Tech courses are mandated to be of 2 years duration.
UG - Once again, since this is not a standardised course, the eligibility criteria for B.Tech CS Artificial Intelligence differs from institution to institution. Generally, you need to have passed 10+2 with Science stream. You must have read physics, chemistry and mathematics (PCM) in your higher secondary years.
As for the exact marks needed in the secondary and higher secondary to be eligible for the B.Tech Artificial Intelligence course, they vary from institute to institute. There are no standard eligibility criteria for enrollment in the AI course. For example, Sharda’s eligibility criteria look like this -
Then there is the entrance test of Sharda. If you get decent marks in JEE Main, you don't need to appear for the entrance test. Universities like LPU do not have such strict requirements, but still, you need to pass the entrance test - in this case - LPUNEST. Some universities like Srinivas University do not require any entrance test participation too. The eligibility criteria for B.Tech Artificial Intelligence fixed by Srinivas University is quite lenient too - 45% in 10+2.
PG - As for M.Tech, obviously you have to pass B.Tech in computer science to pursue M.Tech in Artificial Intelligence. As for the score needed to be eligible for the PG course in AI, it varies from university to university. UPES requires 60% marks in B.Tech along with 60% marks in Higher Secondary. The eligibility criteria fixed by IIIT- Kottayam is a little strict - You need to have a year of working experience in the related field along with 60% marks in B.Tech. Amrita Vishwa Vidyapeetham requires B.E or B.Tech in Computer Science or MCA or M.SC in Computer Science or Software Engineering.
Admission Criteria for AI Courses after Class 12
After class 12, students willing to study Artificial Intelligence in B. Tech or M. Tech has to first qualify JEE Advanced with decent marks above the set cutoff for the current year. Then after counselling and interview, they can enrol themselves into a college offering either an Artificial Intelligence-focused undergraduate course or postgraduate programme in AI. The aspirants have to have physics, chemistry, maths in their subject combination at the 10+2 level and must have passed the boards with more than 70% marks in aggregate. Knowledge of coding will be helpful which is soon going to be a part of the K-12 curriculum in India. Some premier institutes may have their own entrance examination and admission procedure. The candidates must stay updated on the news of the same and fill in the application forms as soon as they are made available on respective institute’s portal.
Entrance Exams For Artificial Intelligence Courses
Apart from passing the senior secondary exam, you also need to pass the entrance test of the institute of your choice. As said earlier, universities like Sharda or LPU have their own entrance tests. Apart from the independently organised entrance test, the scores of the national level entrance tests like JEE are also taken into account in case you do not wish to sit for the institute organised entrance test. However, there are universities like Srinivas University that have no entrance exams.
Fees and Expenses of Artificial Intelligence Courses
Traditional computers work on the input/output basis - you get output based on what you input. All the works done by computers today are basically the results of inputs. Artificial intelligence aims to change this. It is going to save the companies a huge amount of money every year. The takers for AI will come in droves. Even in its nascent stage, many reputed companies like Amazon or Facebook have already started implementing AI-based systems. The demand for AI (and hence AI experts) will increase phenomenally. Especially in the initial years, the demand will be greater than supply. And this is not what is expected in India only but globally too.
Today, more and more companies in India, especially, those located in Bengaluru, Hyderabad, Gurugram and the NCR are trying to adopt artificial intelligence in a big way. It can be a safe, quick and cost-effective solution for companies.
We have seen what SIRI or Alexa can do. One just needs to ask them questions and they give fairly coherent answers. And yet these are just basic examples of AI. Amazon is incorporating AI-based robots in its warehouses to sort products and carry them to the delivery vehicles. Another great use of AI is to detect and delete fake news from the websites. AI-based self-driving cars are about to be an in-thing. The possibility is endless. Here is a list of industries that can benefit from AI, all over the world:
Healthcare, disease detection, surgery and disease prediction
Defence sector. While this is far-fetched, using robots in wars can stop the futile killing of thousands of soldiers.
Space industry. We all know how robots and artificially intelligent systems are trying to find water on Mars, analysing the dust and mud of other planets, examining the poisonous gases present in the atmosphere of other planets.
Business and industries- retail, basic assistance to shoppers, warehousing, even delivery.
Robots that can do heavy-lifting and work deemed dangerous for humans.
Security and surveillance
The scope for growth for Artificial Intelligence is expanding every day. Naturally, one can build a glittering career around it.
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Generally, the syllabus for B.Tech or M.Tech in Artificial Intelligence includes the following topics:
Programming language - Python or C or other languages - Varies from university to university.
Database management and Big data
General topics include
Engineering - custom made for CS students
Biology for CS students
Physics - for CS students
Web and internet
As said, there is no standardised syllabus or curriculum for the B.Tech or M.Tech in Artificial Intelligence course. The topics and subjects will differ from one university to the other.
Artificial Intelligence is a course that will make one’s career future-proof. We all know that as days are passing by, people are trying to make computers think by itself. Without that, automated systems cannot work efficiently. Today we enjoy talking with SIRI. Today, we love the efficiency and quick delivery of Amazon. We need fact-checking software that can check facts automatically. We need to replace our soldiers with robotic soldiers so that no mother ever loses her son. The applications of artificial intelligence are endless. There are many jobs that will be available to a candidate opting for an artificial intelligence course. The three main areas that require the expertise of qualified AI engineers are:
Machine learning engineering: Although we think Artificial Intelligence machines think autonomously, to create the logic-based system in the AI, we need to feed the system with vast amounts of data. We cannot just feed unstructured data. The AI machines need a comprehensive, logical, and vast amount of data in order to let their algorithm work properly. This is the work of the machine learning engineers. Think of machine learning engineers as teachers who inculcate basic ethics and logic in the students. After that, the student uses the teachings of the teachers to come up with their own understanding of the world. The work of ML engineers is extremely critical. They must not feed any data that can make the AI biased.
Data Science: Similar to machine learning engineers, data scientists analyse Big Data to understand how it can be fed into the AI system to make the AI more efficient. Data scientists are perhaps the most important people in the AI world - they need to be aware of both AI and ML to use Big Data in a useful manner.
Artificial intelligence engineering: If machine learning engineers are the teachers, the artificial intelligence engineers are the parents that teach the AI system how to work using the data fed into it. They are the ones who build the neural network- the brain of the AI system. Building a neural network is a work of art- it needs patience as well as strong logical prowess
A quick look on the internet gives us a fair idea of what kind of job profiles do AI experts get. Let us understand what these job profiles mean:
Software engineer/AI engineer: The software engineer is the one who builds an ML algorithm ( not the ML model) and uses it to build the automated system. He is the one to feed Big-data into the system so as to come up with a coherent pattern. In robotics, the AI engineer, in collusion with other engineers, makes the neural networks and ML model work in a synchronised manner. He is the one who is responsible to make a system that can analyse the fed machine learning algorithms to ‘think’ independently based on the data.
Machine learning engineer: Machine learning is the one that builds models that the AI system consults to come up with a decision of its own. The big-data gathered by data scientists is fed to the AI system in an objective way by the ML engineer. He is the one to build the neural networks - the brain of the AI.
Research intern: This is an entry-level job. The primary task of the intern is to assist the senior AI engineer and look for any logical fallacies, potential issues with the AI system.
Research scientist: AI is a continuously evolving technology. There needs to be continuous research so that AI can graduate from infancy to a full-fledged thinking machine. The role of the research scientist is to fine-tune the ML algorithm, examine how and what data can be fed to the AI system to make it work optimally, increase the decision making power of the AI, making the neural networks much more advanced and many more
Cloud solutions architect: With the rise of cloud solutions like AWS or Azure, there is a growing tendency towards SaaS or software as a service. It is the duty of the Cloud solutions architect to guide customers in using AI in the cloud platform.
Data scientist: The work of the data scientist is to feed those data in as unbiased a way as possible. In the real-life scenario, a data scientist will look for instances when a customer abandons a cart and analyse the behaviour of the customer. This behavioural pattern is then fed to the AI system to search for a coherent pattern - the reasons for cart abandonment.
Customer Engineer: As a customer engineer, a person will show how cloud-based systems with integrated AI systems can help their business. It is the role of the customer engineer to show the differences between a traditional cloud platform and an AI-powered cloud platform.
The top recruiters who hire freshers and experienced candidates having a degree in artificial intelligence include:
Smartivity to name a few
Artificial Intelligence is going to spread faster and faster. It will be futile to fight the change. Rather, we must learn everything about AI and make AI-based systems work for us - not the other way round.
A strong sense of logic- Without a strict sense of logic, an AI engineer cannot feed the system with high-quality if-then logics and superior algorithms - the backbone of an AI’s independent thinking capability
Coding skills- People opt for AI to automate things. And this logic-based automation can only be successful with the successful implementation of high-quality codes. As we all know, Python is the king of automation. So, one needs to be adept in Python.
Knowledge in the language (for AI-based assistance apps)
Patience- When an artificial intelligence engineer builds a neural network, in the first few hundred or even thousand iterations of the same work, the AI will demonstrate poor logical thinking capability. Then, the engineer needs to be patient to wait for the AI to ‘grow.’
People skills: There is a growing concern over the fact that AI is going to take away many jobs. But that won’t be the case. The companies would like to have a smooth transition from manual labour to AI robots based labour. So, if one polishes his soft skills along with studying hard in his AI and ML course, his career can experience a great boost. It is because of this reason that most institutes in India offer people skills in the AI course curriculum.
Since this is a fairly modern subject that gets evolved and upgraded every passing day, the syllabus varies from university to university. For example, Amrita School Of Engineering includes lessons on drones and robotics in its B.Tech in computer science - artificial intelligence course. On the other hand, Sharda University focuses on soft skills in its B.Tech AI course. The basic course curriculum looks like this.
Computer Science focused on engineering.
Computer Science focused on Mathematics and Physics.
Introduction To AI
Biology with a focus in Computer Science
Common Subjects Taught In Computer Science - Design, Object-Oriented Programming, OS, C, Python, Industry Focused Lessons
Ingredients of AI - ML, Language Processing, Neural Network, NLP, Deep Learning etc.
Practical Aspects of AI
Ethics - AI focuses
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