About Course

The B.Tech in Artificial Intelligence program is aimed at giving students a thorough understanding of technological innovation and the employment of the technologies. The fundamental parts of the study involving machine learning, deep learning, natural language processing, robotics, and data analytics are covered. The program is a mix of theoretical knowledge and practice, equipping students with problem-solving capabilities to think and create solutions in different spheres. New technologies, with real-world applications as the main focus, form the curriculum and prepare the students for careers in AI and data science that are up to date. The curriculum stresses the importance of thorough involvement by making the students do practical work in advanced labs and projects, through which they gain technical as well as creative problem-solving skills.

Artificial Intelligence is the instrument driving the future of technology and society. As AI enters domains like healthcare, finance, and automotive while breaking into every other industry, the AI professional's job market will only see an increment in employment. The program not only opens doors for exciting careers but also gives the graduates an edge in technological innovations, enabling them to be the change agents in industries.

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Objectives of the Program

  • Gain comprehensive knowledge in algorithms, data structures, and computer systems.
  • Develop proficiency in machine learning techniques, data science methodologies, and feature engineering.
  • Master the application of AI technologies in practical scenarios, including robotics, healthcare, and cybersecurity.
  • Understand and engage with emerging trends such as quantum computing, blockchain, and advanced analytics.

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Future in CSE [Artificial Intelligence]

40% Market Growth

40% Market growth projected by industry reports.

Expertise

High demand for expertise in machine learning, data analysis, and AI-driven technologies.

3 Million Jobs

3 million job opportunities globally, for skilled professionals.

Eligibility

Admission Procedure

  • Admission notification for the current session will be published by the University on the website, in newspapers, on university notice boards, and through appropriate media along with the schedule of admissions.
  • Aspiring candidates can apply for admission through online mode by visiting our website or through offline mode by directly reporting to the university.
  • Applications received will be scrutinized based on the eligibility criteria, and candidates will be shortlisted on the basis of merit. The merit list will be displayed on the website and university notice boards, and students will be informed telephonically well before the cutoff date for admission.
  • Shortlisted students will be provisionally admitted to the allotted course after completing the necessary formalities of fee payment and document submission.
  • The application form of the candidate may be rejected due to any of the following reasons:
    • Failing to fulfill the eligibility criteria
    • Failure to pay the prescribed fees for the course
    • Incomplete application form
    • Supporting documents not enclosed or found unauthentic
  • Enrollment/Registration numbers will be allotted by the university to the provisionally admitted candidates.
  • Students are required to abide by the rules and regulations framed by the university from time to time.

Note: G H Raisoni Skill Tech University, Nagpur, does not demand any capitation fees or donations and does not appoint any agents or external consultancy for admissions.

Documents Required
  • HSC Marksheet
  • SSC Marksheet
  • Passing Certificate/Board Certificate of Std. 10th/SSC
  • RUCET/CET/JEE Scorecard (if any)
  • MHT-CET 2023 Scorecard / JEE (Main) 2023 Scorecard (if any)
  • Nationality Certificate
  • HSC Leaving Certificate
  • Aadhar Card (Photocopy)

Core Skills

Career Opportunities

Entry Level
  • AI Developer
  • Data Analyst
  • Machine Learning Engineer
  • Research Assistant
Mid Level
  • AI Engineer
  • Data Scientist
  • Robotics Engineer
  • Cybersecurity Analyst
Senior Level
  • Lead AI Engineer
  • Senior Data Scientist
  • Chief Data Officer
  • AI Solutions Architect

Future Studies

B.Tech AI graduates have several opportunities for advanced studies, including:

M.Tech (Master of Technology)

in fields such as AI and Machine Learning, Data Science, Robotics, and Computer Vision.

MS (Master of Science)

in areas like Artificial Intelligence, Data Science, or Robotics.

MBA (Master of Business Administration)

for those interested in management roles within the tech industry.

PhD (Doctor of Philosophy)

for advanced research and academic careers in Artificial Intelligence or related fields.

Specialised Courses

in areas such as Deep Learning, Advanced Robotics, and Quantum Computing.

Course Available at College

Top Recruiters

FAQ

What does the qualification cover?

A B.Tech in Artificial Intelligence covers a comprehensive curriculum including machine learning, deep learning, natural language processing, robotics, and data analytics. The program integrates theoretical knowledge with practical applications in AI technologies.

The starting salary for AI engineers in India typically ranges from ₹3.5 to ₹6 lakhs per annum, depending on the company, location, and individual skills. Salaries can increase significantly with experience and specialisation.

Essential technical skills include proficiency in programming languages (such as Python and R), knowledge of machine learning frameworks (such as TensorFlow and PyTorch), understanding of algorithms, data analysis, and familiarity with AI tools and technologies.

To be eligible for admission to a B.Tech in Artificial Intelligence, candidates generally need to have completed their 12th grade with a strong background in mathematics and science. They must also pass an entrance exam such as JEE Main, MHT-CET, or a similar test as required by the institution.

Career opportunities include roles such as AI research scientist, machine learning engineer, data scientist, robotics engineer, NLP engineer, and automation specialist. Graduates can work in various industries including technology, healthcare, finance, and manufacturing.

The course is typically assessed through a combination of written exams, practical assignments, projects, and presentations. Continuous assessment through lab work and coursework also plays a significant role in evaluating student performance.

Useful certifications include those in specific AI technologies and skills such as AWS Certified Machine Learning - Specialty, Google Professional Machine Learning Engineer, TensorFlow Developer Certificate, and Microsoft Certified: Azure AI Engineer Associate.

Skills and languages that often command higher salaries include expertise in machine learning and deep learning, proficiency in Python and R, experience with AI frameworks (e.g., TensorFlow, PyTorch), and advanced knowledge in data science and analytics.

Kimba

Applications of admission are now
open for academic year 2024-2025

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