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Qualifications Required for Enrolling in an M.Tech Course in AIML
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Qualifications Required for Enrolling in an M.Tech Course in AIML

Introduction about AIML in M.Tech Course

Firstly, let us understand the term AIML.

AIML: AI stands for “Artificial Intelligence”, and ML stands for “Machine Learning.”

Master of Technology in Artificial Intelligence (AI) and Machine Learning (ML) is designed to provide in-depth technical knowledge to students related to software applications to predict more accurate results. The program aims to graduate students with advanced technical skills, knowledge and increase their ability to research both primary and experimental components of Artificial Intelligence and Machine Learning. Through these offline or online courses for AIML, students are matured through a series of carefully advanced subjects that include dissertations to demonstrate research potential in specific disciplines such as natural language processing, computer vision, and robotics. The focus of this course is to solve industry and society-centric problems.

What is M.Tech in AI?

M.Tech in Artificial Intelligence is a two-year post-graduate course that is divided into four semesters. This course aims to provide students with science and technology to create computer machines capable of performing tasks that usually require human intelligence. To qualify for the M.Tech in AI program, candidates must have a BE/B.Tech Degree in Computer Science or Artificial Intelligence from an accredited university. Additionally, a minimum of 50% points or equivalent GPA is required to be eligible for admission.

There are several offline and online courses in Artificial Intelligence.

Mtech in artificial intelligence provides the basics and advanced skills used in artificial intelligence. Anyone can also do this course offline while taking admission to accredited colleges and universities.

Eligibility Criteria for M.Tech in AI

A student who wants to enrol in the M.Tech in AI course must follow the minimum eligibility criteria. The student must have a BE/B.Tech degree in Computer Science or Artificial Intelligence from an accredited university with a cumulative score of at least 50%.

Admission Process for M.Tech in AI

Some colleges and universities follow Entrance Exams, Group Discussion, and Personal Interviews for final admission to M.Tech in AI.

Some universities select students based on their bachelor’s degree test scores. Students must achieve at least 50% of the marks in the bachelor’s degree exam. Universities that conduct entrance examinations based on entrance examinations generally conduct National Level Entrance Examinations such as GATE. However, some universities conduct their own entrance examinations.

The step-by-step process of applying for an admission based on the entrance exam is as follows:

Step 1: Students must register themselves on the official website of the college/university.

Step 2: After confirmation, the list of abbreviations will be posted on the website. Positions are assigned to candidates based on their entrance exam scores.

Step 3: Some universities conduct face-to-face interviews and written tests for final selection.

Step 4: If the student is found eligible, admission will be granted.

Some of the colleges offer admission to an M.Tech in AI program based on merit.

The step-by-step process of applying for an admission is as follows:

Step 1: Students must fill out an application form through the online process, depending on their qualifications.

Step 2: The list of exceptions will be posted on the university’s official website.

Step 3: Students are invited to a one-on-one interview and will be asked many questions about the topic.

Step 4: Selected candidates may enroll in the course.

 

Key Highlights of M.Tech AI
The period for the course Two years
Eligibility to do the course B.Tech with 50% aggregate in Computer Science
Admission Process Based on entrance exams like GATE, etc.
Area of employment AI Research Companies and Robotics companies

 

ML – Machine Learning

Machine Learning is a type of artificial intelligence and is the scientific study of algorithms and statistical models used in computer systems. It can be used to perform specific tasks with the help of templates and data outputs. Its primary purpose is to allow computer systems to research automatically without human interference, and it should also be capable of modifying and adapting the actions accordingly.

Eligibility Criteria for M.Tech in ML

Candidates who want to apply for the M.Tech in ML Course must have completed their graduation (B.E/B.Tech) with a reputed university or college. Students should have a good knowledge of high school Mathematics as well. Students must clear the entrance examination.

Some colleges or universities may take their entrance exam for admission, and some colleges may grant admission based on the merit list.

People with a passion for Mathematics and creativity are ideal for Machine Learning. Mathematics, Statistics, and Computing are the foundations of Machine Learning. It is built on top of machine learning algorithms. Machine Learning models are built using multivariate calculus. Linear Algebra, which deals with matrices, vectors, and linear transformations, is used to perform operations. This clearly shows that mathematics plays a vital role in machine learning. Programmers interested in Python programming are also invited for the same.

Machine Learning techniques are widely used in banking and finance because machines provide excellent results and improvements. Machine Learning also prevents fraud and works as a marketing tool. Traditional advertising or marketing is done by analyzing web activity. Suspicious patterns are also efficiently identified using Machine Learning. It is also used to detect or prevent cyber-attacks. This is a service that every country in the world needs. Surprisingly, the amount of machine learning is enormous in India and elsewhere. Machine learning designs systems that use historical data to predict outcomes. There are many opportunities in this field. Many technologists are passionate about machine learning and are working to make it a career. It is an excellent course to develop skills and abilities for a job.

The following skill sets are required for Machine Learning.

  1. Statistics: Machine Learning requires statistics to build models. The generated algorithm requires statistical branching, such as analysis of variance and hypothesis testing. Statistics are the key to making machine learning algorithms. To accelerate the machine learning career, gaining knowledge of statistical tools is very important.
  2. Probability:It leads to outcomes and improvements in Machine Learning. Probability helps with prediction. Machine Learning handles uncertainty conditions to make reliable decisions. Mathematical equations of probability help in predicting the future.
  3. Data Modeling: Unformed records should be analyzed and modeled to create algorithms. Data modeling is needed in this case. Data modeling ideas should be recognized to emerge as a device mastering professional.
  4. Programming Skills: One of the most critical parts of a computer science career is programming skills. Coding is a skill that every recruiter expects from a computer science candidate. Machine Learning mostly requires Python programming, but knowing other programming languages is a plus.It also helps us in creating scripts for web pages and performing other little activities needed for machine learning. Basic skills such as computer architecture, algorithms, and data structures must be strong.

Applications of Artificial Intelligence

Artificial Intelligence is widely used today because it can effectively solve complex problems in many industries such as healthcare, entertainment, finance, and education. AI makes everyday life more comfortable and faster.

Following are some sectors which implement the application of Artificial Intelligence:

  • Data Security
  • Social Media
  • Healthcare
  • Automotive Industry
  • Finance
  • Travel & Transport

Applications of Machine Learning

Machine Learning is a modern technology that is proliferating every day. We use machine learning in our daily life without even realizing it.

Following are some sectors which implement the application of Machine Learning:

  1. Image Recognition
  2. Traffic Prediction
  3. Speech Recognition
  4. Product Recommendation
  5. Automatic Driving Cars
  6. Virtual Personal Assistant
  7. Automatic Language Translation
  8. Medical Diagnosis

Conclusion

Managers need Artificial Intelligence and Machine Learning abilities to satisfy the organization’s innovative requirements. Therefore, a profession in Artificial Intelligence and Machine Learning isn’t just drawing in the work searchers towards it, but it is seeing enormous development. An ai ml course can you help you gain the skills and advance your career.

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