Admissions
The admission process for the Bachelor of Machine Learning program at Technocrats Institute of Technology is highly competitive and designed to identify students with exceptional aptitude, motivation, and potential for success in this challenging field. The process follows a structured approach that ensures fairness and transparency while maintaining academic excellence.
Admission Process Overview
The admission process begins with the submission of applications through the official online portal during the designated application window. Prospective students must register, fill out the required forms, upload necessary documents, and pay the application fee. After the initial screening, candidates proceed to subsequent stages including written examinations, interviews, and counseling sessions.
Step-by-Step Admission Procedure
The following steps outline the complete admission procedure for the Bachelor of Machine Learning program:
- Application Submission: Candidates must submit their applications online via the official website within the specified timeframe. Applications include personal details, academic history, and preferences for courses and categories.
- Document Verification: Once applications are submitted, candidates undergo document verification to confirm eligibility and authenticity of information provided.
- Written Examination: Shortlisted candidates appear for a written examination conducted by the institute. The exam assesses candidates' knowledge in Mathematics, Physics, and English Language Proficiency.
- Interview Process: Selected candidates from the written examination are invited for an interview round where their analytical thinking, communication skills, and interest in machine learning are evaluated.
- Counseling Session: Final admission decisions are made based on combined performance in the written exam and interview. Candidates attend a counseling session to choose their preferred seats and complete the admission formalities.
Eligibility Criteria
The eligibility criteria for admission into the Bachelor of Machine Learning program are as follows:
Category | Age Limit | Qualifying Exam | Minimum Percentage in 12th Grade | Subject Combinations |
---|---|---|---|---|
General | 17-25 years | 12th Grade or Equivalent | 60% | Physics, Chemistry, Mathematics |
EWS | 17-25 years | 12th Grade or Equivalent | 50% | Physics, Chemistry, Mathematics |
OBC-NCL | 17-25 years | 12th Grade or Equivalent | 50% | Physics, Chemistry, Mathematics |
SC | 17-25 years | 12th Grade or Equivalent | 45% | Physics, Chemistry, Mathematics |
ST | 17-25 years | 12th Grade or Equivalent | 45% | Physics, Chemistry, Mathematics |
PwD (General) | 17-25 years | 12th Grade or Equivalent | 45% | Physics, Chemistry, Mathematics |
PwD (SC) | 17-25 years | 12th Grade or Equivalent | 40% | Physics, Chemistry, Mathematics |
PwD (ST) | 17-25 years | 12th Grade or Equivalent | 40% | Physics, Chemistry, Mathematics |
Admission Statistics - Last Five Years
The following table presents the opening and closing ranks for the last five years across different admission categories:
Year | General | EWS | OBC-NCL | SC | ST | PwD (General) | PwD (SC) | PwD (ST) |
---|---|---|---|---|---|---|---|---|
2023 | 1500 | 2800 | 3200 | 4500 | 5800 | 6200 | 6700 | 7200 |
2022 | 1650 | 3000 | 3400 | 4800 | 6100 | 6500 | 7000 | 7500 |
2021 | 1800 | 3200 | 3600 | 5000 | 6400 | 6800 | 7300 | 7800 |
2020 | 1950 | 3400 | 3800 | 5200 | 6700 | 7000 | 7500 | 8000 |
2019 | 2100 | 3600 | 4000 | 5400 | 7000 | 7200 | 7700 | 8200 |
Aspirant Preparation Strategy
To succeed in the admission process, aspirants should follow a strategic preparation plan that includes:
- Focused Study Plan: Develop a structured study schedule focusing on core subjects—Mathematics, Physics, and Chemistry. Use standard textbooks and online resources to strengthen fundamentals.
- Practice Tests: Regularly attempt practice tests and previous year question papers to understand the exam pattern and improve time management skills.
- Mock Interviews: Participate in mock interviews to build confidence and improve communication skills. Prepare answers to common questions about career goals, interests, and motivations.
- Counseling Strategy: Understand the counseling process thoroughly, including seat allocation criteria, choice filling strategy, and reservation policies. Consult guidance from seniors or mentors for effective selection of preferences.