B.Voc in Machine Learning & AI
Program Overview
The B.Voc in Machine Learning & AI at Manipur International University (MIU University) is a three-year undergraduate vocational degree program designed to develop foundational and applied knowledge in Artificial Intelligence, Machine Learning, programming, data science, and related technologies. The curriculum combines theoretical concepts with programming labs and practical learning areas.
Students are introduced to Artificial Intelligence and Machine Learning, Python programming, mathematics, statistics, data structures, algorithms, and R programming in the early stages of the program. As they progress, the curriculum covers advanced areas such as Neural Networks, Pattern Recognition, Advanced Database Systems, Natural Language Processing, Deep Learning, Machine Learning Applications, and Internet of Things.
The later semesters focus on Machine Vision Systems, Big Data Analytics, statistical programming, Web Mining, Recommender Systems, and Data Science using Python. The program also includes discipline-specific electives, skill enhancement courses, laboratory work, and a Project Work component in the final semester.
With its combination of programming, data analysis, AI, machine learning, and practical laboratory components, the program can help students develop technical skills relevant to emerging areas of computing and intelligent technologies.
Eligibility Criteria
Applicants should have completed their 12th grade from an accredited educational board, with an optimal percentage of 50% or higher. The university requires candidates to present essential documents, including academic records and identity proof. Candidates are expected to meet the minimum age requirement of 17 years.
Approval Details
MHRD, Government of India and UGC
Curriculum
The first semester introduces students to the fundamentals of Artificial Intelligence and Machine Learning while building programming and mathematical foundations.
1. Basics of Artificial Intelligence and Machine Learning
Introduces the fundamental concepts, approaches, and applications of AI and Machine Learning.
Key Topics:
- Artificial Intelligence fundamentals
- Machine Learning concepts
- Learning approaches
- AI applications
- Basic problem-solving concepts
2. Object Oriented Programming using Python
Introduces Python programming through object-oriented programming concepts.
Key Topics:
- Python programming
- Object-oriented concepts
- Classes and objects
- Programming logic
- Application development
3. Python Programming Lab
Provides practical programming experience using Python.
Key Topics:
- Python coding
- Programming exercises
- Object-oriented programming practice
- Problem solving
- Program implementation
4. Mathematics-I
Builds the mathematical foundation required for computing and AI-related studies.
5. Language-I
Develops language and communication abilities.
6. English-I
Strengthens fundamental English language and communication skills.
The second semester develops students' understanding of algorithms, data structures, statistics, and statistical programming using R.
1. Data Structures and Algorithm
Introduces methods for organizing data and designing efficient algorithms.
Key Topics:
- Data structures
- Algorithms
- Data organization
- Algorithmic problem solving
- Computational techniques
2. Statistical Structure in Data using R
Introduces statistical analysis of data using the R programming environment.
3. R Programming Lab
Provides hands-on practice in R programming and statistical data analysis.
4. Statistics-I
Develops fundamental statistical concepts useful for data analysis and machine learning.
5. Language-II
Continues language development through the second semester.
6. English-II
Further develops English communication and language skills.
The third semester moves toward advanced programming and AI-related concepts, including neural networks, pattern recognition, and database systems.
1. Java Programming
Introduces Java programming and its application in software development.
2. Neural Networks
Introduces computational models inspired by neural systems and their role in AI.
3. Java Programming Lab
Provides practical experience in Java programming.
4. Advanced Database System
Covers advanced concepts related to database systems and data management.
5. Advanced Database System Lab
Provides practical exposure to advanced database concepts and implementation.
6. Pattern Recognition
Introduces techniques for identifying patterns and extracting meaningful information from data.
7. Generic Electives-I
Provides an opportunity to study an elective area according to the prescribed curriculum.
8. Skill Enhancement Course-I
Focuses on developing additional skills alongside the core curriculum.
The fourth semester focuses strongly on advanced AI and Machine Learning concepts, including Natural Language Processing, Deep Learning, and Machine Learning applications.
1. Natural Language Processing
Introduces computational techniques for processing and understanding human language.
2. Deep Learning
Covers advanced learning approaches based on deep neural network architectures.
3. Machine Learning and its Applications
Explores Machine Learning concepts and their applications in different problem domains.
4. Machine Learning using WEKA Lab
Provides practical experience in Machine Learning using the WEKA environment.
5. Internet of Things
Introduces connected devices, data exchange, and IoT-based technologies.
6. Generic Electives-II
Provides an additional elective learning component.
7. Skill Enhancement Course-II
Develops supplementary skills relevant to the academic and professional curriculum.
8. Environmental Science
Introduces important concepts related to the environment and environmental awareness.
The fifth semester expands into computer vision, Big Data, and statistical analysis while providing opportunities for discipline-specific and skill-based learning.
1. Machine Vision Systems
Introduces computer-based systems that process and interpret visual information.
2. Big Data Analytics
Explores methods and concepts used to analyze large and complex datasets.
3. Statistical Analysis System/SPSS Programming
Introduces statistical analysis and programming using SAS/SPSS-related tools.
4. Statistical Analysis System / SPSS Programming Lab
Provides practical experience with statistical analysis and programming tools.
5. Discipline Specific Elective-I
Provides an elective learning component related to the student's discipline.
6. Discipline Specific Elective-II
Provides another discipline-specific elective area.
7. Skill Enhancement Course-III
Develops additional skills supporting the student's academic and professional development.
The final semester focuses on advanced data-oriented applications and concludes with project-based learning.
1. Web Mining & Recommender Systems
Introduces techniques for extracting information from web data and developing recommendation-based systems.
2. Data Science using Python
Explores data science concepts and their implementation using Python.
3. Data Science Lab
Provides practical experience in data science techniques and Python-based analysis.
4. Discipline Specific Elective-III
Provides an advanced discipline-specific elective component.
5. Discipline Specific Elective-IV
Continues specialized learning through another discipline-specific elective.
6. Project Work
Provides an opportunity to apply concepts and skills developed throughout the program to a project.
Fee Structure
Admission Process
Students can apply for theย B.Vocย Machine Learning & AI programme through EasyShiksha. The complete application process is designed to make admission simple and convenient for eligible students.
Step 1: Click on Apply Now
Click theย Apply Nowย button on the B.Voc Machine Learning & AI programme page and begin your application through EasyShiksha.
Step 2: Complete Personal Information
Fill in the required personal, contact and academic details accurately in the application form.
Step 3: Upload Required Documents
Upload the required documents for eligibility and admission verification as specified during the application process.
Step 4: Pay Application Fee
Pay the applicableย application feeย through the available online payment options to submit your application and initiate the admission process.
Step 5: Application Review
Theย EasyShiksha team reviews your application and submitted documentsย to verify your eligibility and ensure that the required information and documents have been provided.
Step 6: University Enrollment
Once the application is successfully reviewed and the student is found eligible, EasyShiksha facilitates theย enrollment process withย Manipur International University.
Step 7: LMS Access
After successful enrollment, the student is provided access to theย Learning Management System (LMS)ย to begin their academic journey and access the available learning resources.
Start Your Application
Ready to begin your journey in Software Development? Clickย Apply Nowย to submit your application through EasyShiksha.
Career & Placements
The curriculum covers AI, Machine Learning, programming, data science, computer vision, NLP, databases, Big Data, and related technologies. Graduates can explore career opportunities in areas such as:
AI & Machine Learning
- Machine Learning Engineer โ Works with machine learning models and applications.
- AI Engineer โ Develops AI-based software and solutions.
- AI Software Developer โ Builds software incorporating AI capabilities.
- AI Consultant โ Supports organizations in applying AI technologies.
Data & Analytics
- Data Scientist โ Works with data analysis and predictive models.
- Data Analyst โ Analyzes data to identify useful patterns and insights.
- MLOps Engineer โ Supports the deployment and management of machine learning systems.
- Big Data Professional โ Works with large-scale data processing and analytics.
Specialized AI Roles
- Computer Vision Engineer โ Works with image and visual-data applications.
- NLP Engineer โ Develops systems involving human language and text processing.
- AI Researcher โ Explores AI and machine learning methods.
- AI Trainer/Annotation Specialist โ Supports the preparation and annotation of data for AI systems.
Emerging Technology Roles
- Robotics Engineer โ Applies AI and computational techniques to robotic systems.
- AI Product Manager โ Works on the development and management of AI-focused products.
- AI Gaming Developer โ Applies AI concepts to gaming applications.
- AI in Cybersecurity Analyst โ Explores AI-based approaches for cybersecurity analysis.
ย
Manipur International University, Imphal
Manipur International University is a UGC-recognized private university located in Imphal, Manipur, India. Known for its strong industry connections, cutting-edge curriculum, and commitment to technology-driven education, Manipur International University has established itself as one of central India's premier higher education institutions.
The university's vision is to foster academic excellence, industry readiness, and global competitiveness among its graduates โ making it an ideal partner for EasyShiksha's mission of accessible, quality online education.
EasyShiksha has signed an MoU with Manipur International University to facilitate applications for various university programs and jointly offer B.Voc programs. All degrees and certifications under these programs will be awarded by Manipur International University. The EasyShiksha team will provide complete assistance and support throughout the admission and program process.
Manipur International University, Manipur
Sample Degree
Documents
Media Gallery
Frequently Asked Questions
Yes, Manipur International University (MIU) is recognized as per the sections 2(f) and 22 of the UGC Act, 1956. This is a recognized university by the university grant commission and is allowed to award undergraduate, postgraduate and doctoral degrees. Recognition by UGC implies that degrees awarded by MIU are recognized for higher education, competitive exams and job opportunities in India. MIU is an institution where students desiring quality higher education in Northeast India can achieve their educational goals without any difficulty
Students must opt for Manipur International University as it provides degree courses that are recognized. MIU provides numerous choices of courses from undergraduate, graduate to doctorate level. The curriculum of the course is in accordance with National Education Policy (NEP) 2020. Practical learning, innovative research and industry-oriented education is what MIU students believe in to ensure that the students create successful careers. Experienced faculty and modern facilities provided by MIU to its students.
Manipur International University is located at MIU Palace, Luwangsangbam Makha Leikai, Luwangsangbam, Imphal East, Imphal, Manipur-795002.
Manipur International University provides its students with a student-friendly, modern campus equipped with all the necessary facilities that would aid both academic and social life. Smart classes, laboratories, library, computer labs, Wifi-equipped rooms for learning, sports, recreation, cultural and extracurricular activities and many other facilities are offered at MIU.
After doing 12th PCB, there are various courses available for pursuing further studies. Some of the popular courses which can be taken after 12th are Biotechnology, Microbiology, Nursing, Allied Health Science, Medical Laboratory Technology, Environmental Science, Psychology, Pharmacy and many others. These courses will provide a lot of opportunities in hospitals, laboratory, pharmaceutical industries, research institutions and healthcare institutes. Students can select a course on the basis of their interests and future career plans.
There are many career paths for students pursuing PCM in engineering and other sciences and technologies. The popular courses that students may join include B.Tech, BCA, Computer Science, Information Technology, Data Science, Artificial Intelligence, Cyber Security, Mathematics, Architecture, and Engineering subjects. These courses provide various opportunities in software development, engineering, robotics, research, telecommunication, and new technologies. The students should choose any one of the courses based on their personal and professional interest.
Yes, MIU focuses on industry based education by including practical learning projects, skill development, and real world applications in its curriculum. This helps students gain the knowledge and experience needed to handle workplace challenges. MIU has industry based education that helps students improve important skills like critical thinking, communication, teamwork, and leadership. By learning about the latest industry trends, students stay updated and become better prepared for future career opportunities.
MIU does encourage research, innovations, and curiosity among their students and faculty. Research allows students to learn more through exploring new areas, solving problems and gaining deeper insights into their respective fields. Innovations enable the students to think out of the box and increase their analytical abilities. Students can increase their knowledge through research activities, conferences and seminars.
Yes, MIU does motivate its students to participate in several co-curricular and extra-curricular activities that will assist them in developing themselves. These activities include several cultural functions, physical games and sports, leadership, seminars, workshops, etc. These activities not only help the students develop their confidence and leadership qualities but also contribute towards their educational development.
The programme information lists 71 Certification programmes under the Certification category.
A B.Voc programme typically has a duration of three years, with Class 12 or an equivalent qualification generally serving as the entry point.
Yes. A B.Voc can provide a foundation for further education, including M.Voc, which allows learners to pursue advanced specialisation in a vocational field.
Depending on the curriculum, D.Voc programmes may include practical training, projects, workshops, and other occupational learning components focused on applied and skill-based education.
MBA programmes may be offered with specialisations such as Finance, Marketing, Human Resource Management, International Business, Operations Management, Business Analytics, Entrepreneurship, Healthcare Management, and Information Technology Management, depending on the university and programme.
A B.Lib programme can introduce students to areas such as library administration, cataloguing, classification, documentation, reference services, information retrieval, library automation, and digital information management.
The B.Voc in Machine Learning & AI is a three-year undergraduate vocational degree at MIU University covering Artificial Intelligence, Machine Learning, Python, statistics, data science, deep learning, computer vision, Big Data, and related technologies.
The curriculum includes Basics of Artificial Intelligence and Machine Learning, Python, Data Structures and Algorithm, R Programming, Neural Networks, Pattern Recognition, Natural Language Processing, Deep Learning, Machine Learning and its Applications, Big Data Analytics, Data Science using Python, Web Mining & Recommender Systems, and other related subjects.
Yes. The curriculum includes practical components such as Python Programming Lab, R Programming Lab, Java Programming Lab, Advanced Database System Lab, Machine Learning using WEKA Lab, Statistical Analysis System/SPSS Programming Lab, Data Science Lab, and Project Work in the sixth semester.
Students can develop skills in Python and Java programming, statistical analysis, data structures, databases, Machine Learning, Deep Learning, Natural Language Processing, Big Data Analytics, Data Science, and computer vision.
Graduates can explore roles such as Machine Learning Engineer, AI Engineer, Data Scientist, Data Analyst, Computer Vision Engineer, NLP Engineer, AI Software Developer, MLOps Engineer, Robotics Engineer, and other technology-related positions.
