Artificial Intelligence

What Is Eligibility for Artificial Intelligence Course?

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Artificial Intelligence is rapidly gaining ground in the world, and a lot of modern-day industries are using AI to enhance their products and services. As the need for AI experts increases, so does the availability of courses that individuals can undertake to inform themselves about this subject. Each of the various available AI courses has different content and eligibility. The readers of this article can expect to have a decent level of understanding of all the different types of available courses, their eligibility criteria, their advantages and disadvantages, the scope of AI in India, and various industries, among other things. 


After completing their schooling, one can pursue an artificial intelligence course (after 10+2). Suppose one wants to be eligible for graduation or Masters in AI from a university in India, then typically in senior optional. In that case, the score to qualify is 70%, with at least 60 % marks in Physics, Science, and Arithmetic. 

Competitors need to meet all such requirements and may even have to sit for the National JEE entrance test or other tests such as SUAT, UPSEE, etc. One must remember that the term ‘Artificial Intelligence’ and ‘Machine Learning course’ varies at various levels. The Under Graduate degree is four years, while Post Graduate (Masters) degree is of 2-year. Apart from this traditional way of gaining knowledge, multiple certification platforms exist, each with its eligibility criteria.

These programs comprise of various courses that, in totality, help the learner to understand

  • Understand the functioning of various AI-based algorithms
  • Take care of issues identified with robots and machines
  • Create AI applications and do the necessary programming
  • Advance the capabilities of robots

AnalytixLabs is the premier Data Analytics Institute specializing in training individuals and corporates to gain industry-relevant knowledge of Data Science and its related aspects. It is led by an alumnus of McKinsey, IIT, and IIM alumni who have outstanding practical expertise. Being in the education sector for a long enough time and having a wide client base, AnalytixLabs helps young aspirants greatly to have a career in Data Science. 

1. What is Artificial Intelligence

Artificial Intelligence (AI) makes it workable for machines to learn new facts, acclimate to new sources of information and perform human-like errands. Most AI models that we find out about today – from chess-playing computers to self-driving vehicles – depend intensely on deep learning algorithms and, in some cases, natural language processing. Utilizing these advances, computers can be prepared to perform complex tasks by making them handle a lot of information and recognizing patterns in the data.

What is artificial intelligence

The term artificial intelligence was introduced in 1956; however, artificial intelligence has become more famous today because of expanded information volumes, progressed algorithms, and enhancements in computing power and storage. 

Earlier artificial intelligence researchers, during the 1950s, investigated subjects like critical thinking and symbolic strategies. During the 1960s, the US Division of Protection checked out this sort of work and started preparing computers to impersonate essential human thinking. Defense Advanced Research Projects Agency (DARPA) finished road planning projects during the 1970s. Furthermore, DARPA delivered wise individual assistance in 2003, sometime before Siri, Alexa or Cortana became recognized names. 

This research created the ground for the automation and formal thinking that we find in computers today, including decision-making and intelligent search systems that can be intended to supplement and expand human capacities. 

While Hollywood movies and sci-fi books portray artificial intelligence as human-like robots that assume control over the world, the current advancement of artificial intelligence advances isn’t so terrifying – or that shrewd. All things considered, artificial intelligence has developed to provide numerous advantages to particular industries. In contrast, others continue to pursue avenues for AI application with the recent advancements being made in medical services, retail and others.

For more details, also read: 101 of Artificial Intelligence – What to know as a beginner?

2. Why Artificial Intelligence

Today, the volume of information produced by people and machines far outperforms people’s capacity to assimilate, decipher, and identify patterns to settle on complex choices and decision-making. This is where AI comes in handy, as it can find patterns and predict values for us by looking at large quantities of structured, semi-structured, and even unstructured data. 

Artificial intelligence is becoming the basis of all computer learning and is the eventual fate of all business decision-making. For instance, some people can figure out a way to not lose at tic-tac-toe (noughts and crosses), even though there are 255,168 interesting maneuvers, of which 46,080 end in a draw. However, far fewer people would be viewed as excellent masters of checkers, with more than 500 x 1018, or 500 quintillions, diverse likely moves. This is where a highly trained human brain is useful. However, with AI, it can figure out all the possible techniques and use the best one to win the game. This idea is then extrapolated to solve other complex problems ranging from image recognition to driving cars for humans.

You may also like to read: Learn About the Future of Data Science and Artificial Intelligence

3. Artificial Intelligence in India

In June 2018, the Indian government characterized a public approach to artificial intelligence in a paper named “National Strategy for Artificial Intelligence.” The NITI Aayog paper distinguishes five center regions where artificial intelligence advancement could empower both the development and incorporation of AI in numerous industries such as medical services, farming, metropolitan/brilliant city planning, and transportation and portability. The paper additionally talks about five obstructions to be tended to:

  • Absence of AI exploration skills
  • Absence of empowering biological information systems
  • High asset cost and low awareness of AI
Artificial Intelligence in India

The most recent five years have seen colossal take-up of automated reasoning (artificial intelligence)- centered developments in India. More than 4,000 AI patents were recorded during the period, multiple times higher than the figure for 2011-2015, uncovers a Nasscom study. India was positioned eighth in the best 10 nations by artificial intelligence patent families worldwide, a remarkable achievement considering it had no artificial intelligence-related patent documenting before 2002.

Thus, there is a lot of scope in AI in a country like India, which has a large population, potential, and problems. AI can be used to ease the life of the common folk. One of the examples can be seen where AI-based algorithms are put in place to alleviate document verification and speed up government processes. And in the coming years, the use of AI in India will only expand.

4. Artificial Intelligence Course Eligibility

Artificial intelligence course eligibility in India is clearly laid out in B.Tech courses. One can additionally dive further into the complexities of AI and decide on the M.Tech course as well. 

Artificial Intelligence Course Eligibility
  • Undergrad Level (4-year course)

For the B.Tech artificial intelligence course, eligibility is the class 12 pass-outs. These are the thorough artificial intelligence courses. The B.Tech artificial intelligence course in India includes the fundamentals of artificial intelligence and Machine Learning (ML) and their typical applications. The Artificial intelligence course eligibility in 2021 is similar to other ordinary software engineering courses, which require individuals to have their 12th done in the Science field and have high scores in STEM subjects. For some courses, one may have to sit through the National JEE entrance test or other tests such as SUAT, UPSEE, etc. These AI courses also typically incorporate the topics that are there in the other ordinary software engineering course, such as JAVA, C, electrical and hardware designing, database management, design, operating systems, etc.

  • Postgraduate Level (2-year course)

Postgraduate Level Artificial intelligence course eligibility in India is typically graduation in a STEM-based course. This includes Computer Science, Mathematics, Statistics, and of course, Data Science and Artificial Intelligence. The PG in AI offers a more extensive review of artificial intelligence and machine learning.

  • Professional Certification Courses (Online and Offline)

Today with the availability of so many ed-tech organizations, learning through the web has turned easy, cost-efficient, and effective. Artificial intelligence course eligibility in 2022 for such courses is also comparatively relaxed, with some allowing candidates with a non-STEM background. Also, as many reputed online ed-tech institutes offer AI certificate courses, and as there is high competition among them, the quality of the courses has also seen a rise. A portion of these courses is presented by Google, MIT, and Stanford University. 

The minimum and maximum Duration of Artificial Intelligence Courses are as follows-

  • In India, B. Tech in artificial intelligence is presented as a B.Tech Computer Science course. Like other B.Tech courses, this AI course is likewise 4 years in length, and there will be a sum of 8 semesters. 
  • M.Tech in software engineering specializing in artificial intelligence is a 2-year course with four semesters. A few colleges offer courses customized for AI and ML, and others provide discretionary AI subjects with the typical M.Tech educational plan. (Since B.Tech and M.Tech courses are normalized courses in India, there is no variety in the length of the B.Tech and M.Tech course in any discipline. No organization can offer a B.Tech course having under 4 years and M.Tech under one year, at least not the popular or licensed ones.)
  • Courses from Eu-tech organizations can be highly varied. They can range from 1 month (if you have prior knowledge of ML) to 1 year (for nano degrees and diplomas). The aforementioned Artificial intelligence course by AnalytixLabs has a duration of 6-months, and candidates get one year complete the course certification.

5. Types of Artificial Intelligence Courses

Artificial Intelligence (AI) is the future, and in many industries, it has arrived and is there to stay. It has been assessed that by 2030, the AI market will offer more than $15 trillion to the world economy. There is an enormous lack of expertise in artificial intelligence; hence, getting suitably skilled in AI can ensure a promising profession for the future. For those in the workforce, re-skilling, and up-skilling for future AI-based jobs. Thus, because of this reason, there is a huge demand for Artificial intelligence courses after the 12th. These courses, however, can be broadly classified into two categories.

  • Content-based AI courses
  • Certificate-based AI courses

A: Content-based AI courses

We are seeing the application of artificial intelligence across industries (medical care, finance, mobile, automobile, smart home gadgets, music and film suggestion, administration, retail, security surveillance, fraud detection, virtual player games, web-based media applications). Pretty much every business is attempting to carry out AI in their processes. Learning AI can consequently open a universe of chances for anybody. As AI has diverse application possibilities, the various available courses can be distinguished based on their contents. Broadly they can be classified as follows.

Type A1: Programming centered courses

Python is where you need to begin if you’re new to Artificial Intelligence. Through this type of course, you’ll become familiar with all the skills essential to acquire a strong foundation in programming, math, and deep learning. This will empower you to become a master in practically any aspect of AI.  The focal point of these courses is Python — one of the most generally utilized programming languages in AI. Such programs mainly focus on crucial library bundles for AI in Python, such as Pytorch (the most helpful open-source AI library for Python) and Tensorflow. Neural networks are additionally integral to the educational program. They are the principal building blocks of current AI frameworks. In such a program, you’ll get familiar with the numerical abilities essential to see how to plan and build these networks. You’ll additionally figure out the potential of a neural network. The particular focus is on deep neural networks, which are the main impetus behind most present-day AI frameworks.  Before finishing such a program, you’ll typically have the option to assemble your own AI application — an image classifier or something similar by utilizing a deep neural network that you would have prepared without help from anyone else.

Such Programming centered courses explore mainly five areas. 

1. Prologue to Python 

This is the place where you learn Python. You’ll find the capabilities of python, why it is used for AI, and the use of python fundamentals.

2. Coding tools 

Here, you’ll figure out how to utilize Jupyter Notebooks to make reports consolidating code, text, images, and others. You’ll be acquainted with Python library bundles, for example, Anaconda (an environment manager built specifically for data) and other libraries such as Numpy (to add support for big data), Pandas (utilized for data control and analysis), and Matplotlib (which is utilized for data visualization), etc.

3. Linear Algebra Essentials 

Such courses also briefly venture into Linear Algebra, as it’s a particularly significant mathematical concept in the realm of AI. You’ll understand various concepts and their implementation in Python, such as vectors, matrices, linear combinations, and linear transformations. 

4. Calculus Essentials 

Here, you will become familiar with calculus basics, which will assist you with various aspects of neural network-based algorithms such as backpropagation, gradient descent, etc. The main focus here is on plotting, derivatives, understanding partial derivatives, chain rules, etc. Through this, you will be able to study the universe of neural networks and how exactly these concepts are used to make neural networks functional. 

5. Neural Networks 

Last but not least, one will gain knowledge of the various neural network-based algorithms, their characteristics, use cases, types, advantages, and disadvantages. You’ll also explore the preparation procedures required for developing a machine learning and neural network-based model and utilizing PyTorch and Tensorflow to develop different predictive models powered by the various deep learning algorithms.

Type A2: Future AI-based courses

Lately, deep neural networks have been used to identify images just as we people do. However, this was a dream for many scientists working on AI technology some time back. Yet, today, with the abilities of AI, we can do several things that previously were thought to be impossible. However, still, there are use cases where the application of AI is still developing. Here, those programs come in handy that talk about application areas that are still nascent.  Such courses you will be- 

  • Acquainted with the ideas and processes expected to turn into an AI expert. 
  • Trained to look further into deep learning and explore the new state-of-the-art or less explored neural network algorithms.
  • Exploring advanced projects such as Computer Vision, Natural Language Processing, Self-Driving Cars, etc. 

Type A3: Courses based on the Utilization of AI in specific Industries

Certain courses develop and train individuals to identify ways and avenues where AI can be applied in their domain. These courses are designed especially for non-specialized partners to take. 

In these types of courses, you learn: 

  • The importance and understanding behind typical AI jargon, including neural networks, AI, deep learning, and data science 
  • What AI reasonably can and can’t do 
  • How to spot places for applying AI to resolve issues in your industry 
  • What are the pre-requisites for undertaking AI-based projects 
  • How to function with an AI team and construct an AI methodology in your organization 
  • How to explore moral and cultural conversations encompassing AI 

However, these types of courses are, to a great extent, non-specialized and mainly helps an individual in gaining proficiency with the business and managerial aspect of AI. 

Type A4: Courses based on engineering, statistical aspects, and major applications of AI

These courses are a complete package that can cover AI topics from basic to advanced. The concepts covered in these courses include data munging, statistics, machine learning and deep learning, and numerous case studies on artificial intelligence.

In this category, AnalytixLabs offers one of the highly-rated Artificial Intelligence courses, which provides a great deal of practical knowledge for real-world job challenges.

The typical curriculum looks like this-

1: Outline of AI and Machine Learning Engineering Stack 

  • Find out about the various streams of AI and the distinction between AI, Machine Learning, and Data Science. 
  • Get acquainted with the devices and libraries utilized in the realms of data science and engineering. 
  • Learn computer programming best practices that apply to AI/ML experts. 

2: Data Munging at Scale and Statistics for AI 

  • Gather information at scale from APIs, real-time systems, and sites. 
  • Change this information proficiently and adequately with the goal that ML calculations can crunch it down the pipeline. 
  • Use frequentist statistical deduction and hypothesis testing to draw data insights. 

3: Establishments of Machine Learning 

  • Investigate the supervised and unsupervised ML algorithms. 
  • Realize when and how to execute these algorithms at scale. 

4: A Deep Dive into Deep Learning 

  • Set up an intensive understanding of deep learning and develop actual applications. 
  • Find out (regarding neural networks) standards and design structures using Keras and PyTorch. 

5: Natural Language Processing 

  • Become familiar with the essentials of message information, including how to clean and handle data and how to extract insights from messages and other similar data. 
  • Work through an itemized contextual study and take care of genuine NLP issues utilizing deep learning strategies. 

6: Computer Vision 

  • Learn image processing methods and ways to tackle image handling issues. 
  • Dive into the basics of computer vision and deep learning for images. 

7: Building and Deploying Large-Scale AI Systems 

  • Apply what you’ve realized by deploying a practical, enormous AI framework. 
  • Find ways to keep the model up to date, establish continuous data processing, and make your application accessible through API or web administration. 

8: Capstone Projects

  • Perform projects based on different business problems using all the knowledge gained throughout the course.

9: Profession Support 

  • Such courses may even include support from professional mentors to secure your job positions.
  • This support incorporates resume feedback, mock interviews, negotiation strategies, etc.

Type A5: Courses based on Stock Market

AI Stock Prediction

“Artificial intelligence is to exchanging what fire was to the mountain men.” That’s the level at which one industry player explained the effect of AI on the stock market industry. AI is forming the fate of the stock exchange. Utilizing AI, Robo-consultants examine a vast number of data centers and execute exchanges at excellent value with precision, and exchanging firms productively mitigate risk to accumulate better returns. In these types of courses, you’ll learn

1: Basic Quantitative Trading 

Understanding of the several monetary and institutional fundamentals needed for trading. You will likewise learn essential data handling and momentum techniques. For example, here, Data Analysis is understood using libraries like Pandas for discovering diverse Alpha Signals. 

2: Advanced Quantitative Trading 

In such a course, advanced aspects of trading are also explored with regard to data analysis. One will initially understand predictive modeling with AI models and learn to manage anomalies and perform filtering. Here concepts such as breakout strategy are discussed, and how AI can be used in identifying such breakouts and getting familiar with the fundamentals of mean inversion and pair trading strategies. 

3: Sentiment Analysis with Natural Language Processing 

Such a course also makes the trainee learn some extremely incredible methodologies for sentiment analysis and text processing from websites like Twitter, StockTwits, and so forth, and on organization records or filings. This way, the mood of the market can be determined, and better decisions can be taken. 

4: Combining Multiple Signals 

Such courses also explain how to unite everything. Here, systems and techniques from before are used to discover improved alphas, exchange signals, and genuinely enhance a portfolio efficiently and safely.

All of this is done, along with coming up with various strategies to improve alphas and moderate risk factors in a portfolio.

These courses also focus on things like simulating trades with historical data, backtesting, etc.

B: Certificate-based AI courses

Learning Artificial Intelligence (however not extremely simple) has become genuinely open now with various courses and pieces of training available on the web. These are instructed by the best AI teachers, analysts, and specialists. While such certificates do exist, there are other courses also which are provided by larger academic institutions that offer a bachelor’s or masters degree. However, in such a course, the classes are extraordinarily exhaustive and time-consuming. 

To assist you with settling on the best decision, here is the type of courses based on the type of certificate they provide-

Type B1: Bachelors certificate-based AI courses artificial intelligence course eligibility is that you must be at least 12th pass out. In India, B. Tech in artificial intelligence is introduced as a B.Tech Computer Science course. Like other B.Tech courses, this AI course is, in like manner, 4 years long. There will be an amount of 8 semesters. 

Type B2: Masters certificate-based AI course

M.Tech in computer programming specializing in artificial intelligence is a 2-year course with four semesters. A couple of colleges offer courses customized for AI and ML, and others provide optional AI subjects with the typical M.Tech educational plan.

Type B3: Diploma certificate-based AI courses

The diploma-based course can be 1 or 2 years long. These courses can be beneficial for learning the basics and practical applications of AI.

Type B4: Professional certificate-based AI course

Professional certificate-based courses can be up to 6 months long. These courses can be beneficial for working professionals and freshers to improve their skills and enter the field of AI.

Thus, there are multiple ways through which AI can be learned. While the longer-duration courses require a higher time commitment and are tough to get in, they provide a more recognized certificate. In contrast, other courses work more in terms of practical knowledge and can help you to crack an interview based on the display of your AI knowledge base. 

6. Skills required for Artificial Intelligence Course

Skills required for artificial intelligence jobs

While AI is a vast field and requires an amalgamation of skills to master the field, these are at least five skills you need to have to construct extraordinary ML/AI solutions:

  • Programming Skills 

The primary expertise needed to turn into an AI engineer is coding. To become knowledgeable in AI, it’s important to pick up programming languages like Python, R, Java, or C++ as they help develop and implement AI models. 

  • Linear Algebra, Probability, and Statistics 

To comprehend the functioning of the various AI algorithms and their related concepts, for example, Hidden Markov models, Back Propagation, Gaussian combination models, straight discriminant examination—you need to have a knowledge base in maths, likelihood, probabilities, calculus, algebra, etc.

  • Spark and Big Data Technologies 

Modern-day AI engineers work with vast volumes of information, which could be a continuous stream of data weighing in terabytes or petabytes. These professionals need to utilize big data tools such as Spark to process such information. Alongside Apache Spark, one can similarly use other big data tools like Hadoop, Cassandra, MongoDB, etc. 

  • Data Understanding

Various AI models work with unstructured information, and one needs to know about data structures. One needs to know the techniques to convert data formats such as audio, video, images, and text into a structured format such that the AI algorithm can be used to implement a model. The need to understand the data structures found in different libraries such as PyTorch, Theano, TensorFlow, and Caffe is also there.

  • Communication and Problem-solving Skills 

AI engineers need to have good communication skills to convey their ideas to their co-workers or leadership. This is required because the projects are often complex, and it’s essential that everyone understands what’s going on and is on the same page. Excellent critical thinking abilities are also required as the problems faced in real life are not straight out of books or tutorials. Also, one needs to accommodate the business side of knowledge during their model implementation.

You may also like read: Know about Artificial Intelligence Career Paths | Job Roles & Skills

7. Top Sectors using Artificial Intelligence

Top sectors using artificial intelligence

There are multiple sectors where AI is being implemented rapidly. As of 2021, common application areas include-

  • Spam filters

Spam is a big problem with email providers and users, and AI-based algorithms can identify such spam messages and help the user in using their inbox. Spam channels utilize modern algorithms to break down a ton of emails with a long list of criteria to consider. 

  • Voice to text features

Voice-to-text is a kind of speech recognition program. Voice-to-text was initially evolved as an assistive innovation for the hearing impaired. Its applications were essentially restricted because the voice-to-text program must be trained to perceive a particular individual’s speech before accomplishing a satisfactory precision. However, more recent versions can decipher the individual’s speech without training. This has opened up opportunities for new utilizations, including intelligent cell phone functions, for example, voice-to-text message conveyance and voice recognition.

  • Smart Digital assistants

Digital assistants can play out specific tasks for a person with the assistance of a specific client data source and access to GPS location. Digital assistants are acquiring greater prominence, with upgrades being designed consistently. Such personal digital assistants can help get data from the web like weather information, stock prices, traffic conditions, news, and so on. Today, with quick headways in innovation, most digital assistants can even plan and schedule meetings, oversee messages, daily agendas, records, etc. Digital assistants are acquiring ubiquity as time passes with the assistance of upgraded technologies. Individuals utilize these assistants to give them a smooth experience and fast outcomes. The most famous computerized partners that are being used by humans today include: 

  • Siri: Created by Apple, Inc., Siri is a smart digital assistant that permits clients to send instant messages, make plans, settle on decisions, play music and recordings, etc. It is a voice enacted smart assistant that was first fused into the iPhone through iOS 5 delivered in 2011, and it was continuously made accessible on a couple of various platforms. 
  • Google Now: Google’s smart assistant, Google Now, is available on all Android gadgets. Launched without precedent in 2012, Google Now is utilized to plan arrangements, send instant messages, look for headings, etc. With the most recent upgrades of Android, another feature called Google Now on Tap is likewise accessible for the most recent Android handsets. 
  • Cortana: This is an essential intelligent digital assistant created by Microsoft and launched alongside the arrival of Windows Phone 8.1 in the year 2014. Aside from an excellent sense of humor and capacity to make wisecracks, Cortana can be utilized to set updates, discover documents on the telephone, track bundle conveyances, and so forth. 
  • Facebook M: This digital assistant created by Facebook is, in effect, leisurely consolidated in Facebook Messenger. At present accessible just to a couple of clients, this service will be moved to the remainder of the Facebook using people soon. Once functional, it tends to be utilized in planning occasions, discovering eateries, booking tickets, and purchasing online stuff in an exceptionally advantageous way. 
  • Blackberry Assistant: Blackberry Limited or RIM created this smart digital assistant, which permits users to perform various tasks dependent on voice-based data sources. Blackberry Assistant helps you give voice orders or type in the question and afterward show the necessary outcomes. 
  • Braina: This is a virtual computerized colleague which is created to be utilized in Windows PC working frameworks. Created by Brainasoft, this assistant assists clients with performing errands dependent on voice input. It predominantly centers around voice recognition and utilizes a natural language interface. 
  • Teneo: This digital assistant is created by Artificial Solutions; and assists organizations with making natural language applications that can be utilized to provide their clients with added personalization and improved client support. 
  • Speaktoit Assistant: This specific Assistant is created by Speaktoit and assists clients with performing different tasks like setting updates, answering questions, informing about significant occasions, and so forth. 
  • Hound: Hound is an exceptionally smart and accommodating digital assistant which gives a quick and definite list of items of climate, sending instant messages, settling on a decision, tracking down an appropriate lodging for you, exploring help, actually looking at the securities exchange, and so on. It can likewise be utilized to play music and play different interactive games. 
  • Amazon Echo (Alexa): Created by Amazon, this is a voice-empowered computerized speaker which reacts to the name Alexa. The gadget permits the client to play music, set cautions, make plans for the day, stream podcasts, give climate information, and even order products from the Amazon site. It can also be utilized to control other smart gadgets with the assistance of the automation center.
  • Automated responders and online customer support

Automated customer service permits customers to take care of issues without collaborating with another human. It might appear illogical to remove individuals from the critical thinking situation from the get-go. However, AI had progressed significantly since the times when customers had to frantically attempt to reach human support as automated support was useless.  Today, in contrast to humans, automated support systems are accessible to offer help every minute of every day, 365 days per year, and provide accurate information. What’s more, they help customers by dealing with basic, common problems and guiding them to easy, simple, and fast attainable solutions. This opens up those human resources that need to be delegated to those customers who are in need of human help.

  • Robotic Process Automation (RPA)

RPA is more developed than ever and has dramatically helped in business-process automation. The fact that the “robots” (AI models on a server) behave like a human in contributing and burning-through data from different IT frameworks has made their adaption widespread.

Such  ‘robots’ can take care of multiple tasks. A handful of these tasks include: 

  • Transferring information from email and call center frameworks into systems of record—for instance, refreshing client documents with address changes or service increments; 
  • Identifying anomalous credit card transactions and reaching into various frameworks to refresh records and handle client communications;
  • Reducing losses by auto charge for services across billing frameworks

RPA is the most economical and straightforward way to execute AI technologies to speed up daily operations. These systems were initially minimally “smart” as these applications weren’t customized to learn and improve. However, designers have gradually added more intelligence and learning ability to these systems. These systems are also especially appropriate for working across various back-end frameworks. 

One might think that robotic process automation would immediately put individuals jobless. Among the 71 RPA projects surveyed (47% of the aggregate), replacing representative workers was neither the essential goal nor a typical result. As innovation improves, robotic automation projects will probably prompt some employment misfortunes, especially in the offshore business process outsourcing industry. However, by and large, other industries will come up to absorb the workforce.

  • E-commerce

E-commerce also has been greatly benefiting from AI technologies. Here AI is being used for the following-

  • smart searches and relevance features
  • personalization as a service
  • product recommendations and purchase predictions
  • fraud detection and prevention for online transactions
  • dynamic price optimization 
  • Artificial Intelligence in marketing

One of the relatively new domains to take up AI in their operations has been Marketing. A great deal of work has been chalked out by the industry leaders where AI can come in handy such as-

  • recommendations and content curation
  • personalization of news feeds
  • pattern and image recognition
  • language recognition – to digest unstructured data from customers and sales prospects
  • ad targeting and optimized, real-time bidding
  • customer segmentation
  • social semantics and sentiment analysis
  • automated web design
  • predictive customer service

While these have been the common sectors where AI has found its place, this is by no means an exhaustive list. Other sectors of AI application include

  • Defense: For enhanced security on and within borders.
  • Medical: For quick identification of diseases and aid during operations
  • Insurance: For quick redressals of claims and correct identification of frauds
  • Transportation: The automobile industry has embraced AI, and self-driving cars are one of its shining examples.
  • Real-Estate: To predict the house prices and the growth

You may also like to read about: Top 15 Real World Applications of Artificial Intelligence | Uses of AI

8. FAQs – Frequently Asked Questions

Q1. Who can study Artificial Intelligence in India?

The Artificial Intelligence course qualification for candidates is to have selected a Science stream after 10th grade. It ought to have qualified their +2 with at least 50% marks and with Mathematics and Physics as main subjects. Candidates can then seek various Artificial Intelligence Courses in India after the twelfth, which are mainly available alongside or within computer science courses (Note- BTech or MTech in Artificial Intelligence are probably the most advanced courses in UG and PG and thus sometimes require a substantial score in JEE Main or GATE).  Students can also get into an online certificate or diploma-based artificial intelligence program. Generally, they are easier to enter and are short. Ed-Tech companies lead in providing such certificate programs and often provide good quality content. 

Q2. Can I do Artificial Intelligence after the 12th?

There are different Artificial Intelligence courses available after successfully completing the twelfth. The eligibility criteria can differ for different courses, but one can definitely pursue AI after the 12th.

The table below will assist with picking up the type of artificial intelligence course after the 12th:

Course TypeDuration
BTech./B.E. in Artificial Intelligence4 years
BTech in Computer Science (with AI specialization)4 years
MTech/ME/MSc in Artificial Intelligence2 years
Certificate in AI, Machine Learning, Deep Learning, Natural Language Processing6 months – 1 year
Diploma in AI and Machine Learning1 year
Post Graduate Diploma in AI and Machine Learning2 years
Ph.D. in Artificial Intelligence3 years

Q3. Which course is best after the 12th?

Till now, the field of data science and AI has been a favored subject for postgraduate individuals; however, the expanding need for data experts is making people begin in data science at an early stage. Thus, learning AI after the 12th is a good idea as there are a good number of things that can be learned at this stage. For this, one can go for either a proper bachelor’s degree or master’s degree or can go for various courses available online such as-.

  • Artificial Intelligence Engineering (AnalytixLabs)
  • AI Programming with Python Nanodegree (Udacity)
  • Artificial Intelligence A-Z: Learn How to Build an AI (Udemy)
  • Columbia’s Artificial Intelligence MicroMasters Program (edX)
  • Artificial Intelligence A-Z: Learn How to Build an AI (Udemy)
  • ColumbiaX’s Artificial Intelligence MicroMasters Program (edX)
  • Introduction to Artificial Intelligence (edX)
  • Google AI Education (Google)
  • IIT Delhi (NPTEL platform) – Artificial Intelligence Online Course
  • DeepLearning.AI – AI for Everyone (Coursera)
  • IBM (through edX) – Professional Certificate in Applied AI
  • Delft (through edX) – Professional Certificate in AI in Practice

9. Conclusion

AI is being rapidly adopted across numerous industries, and day after day, the list of possible use cases is increasing. There is a massive requirement for AI professionals, and thus, this sector has a considerable possibility of mass employment with high-paying jobs. To enter this field successfully, one must start early and, based on their eligibility, start learning Artificial Intelligence.

For any assistance or questions please feel free to reach out to us!

You may also like to read: 

1. How to Become an AI Engineer? Know about Skills, Roles & Salary

2. Artificial Intelligence Tutorial – Guide For Beginners

3. Components Of Artificial Intelligence – How It Works?

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