The MBA (Artificial Intelligence) syllabus at Alva’s Institute of Engineering & Technology (AIET), Mangalore is designed to provide overall knowledge to the students with a strong foundation. MBA (Artificial Intelligence) faculty at Alva’s Institute of Engineering & Technology (AIET) specially focus on in-depth learning to relevant subjects. At first semester syllabus of MBA (Artificial Intelligence) at Alva’s Institute of Engineering & Technology (AIET), students learn the basics of programme. A strong foundation is very important for comprehensive learning. MBA (Artificial Intelligence) syllabus at Alva’s Institute of Engineering & Technology (AIET), Mangalore maintains a balance between theoretical knowledge and practical knowledge.
MBA (Artificial Intelligence) first year students at Alva’s Institute of Engineering & Technology (AIET) are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. Alva’s Institute of Engineering & Technology (AIET), Mangalore also provides practical training sessions, workshops, projects, and case studies to enhance student skills. MBA (Artificial Intelligence) syllabus at Alva’s Institute of Engineering & Technology (AIET), Mangalore is also frequently updated to give industry relevant training and knowledge to students. Alva’s Institute of Engineering & Technology (AIET) strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at Alva’s Institute of Engineering & Technology (AIET) enable MBA (Artificial Intelligence) students to apply knowledge and skills in a controlled environment and get required experience.
According to syllabus of MBA (Artificial Intelligence) progress, students learn advanced topics and complex concepts. The MBA (Artificial Intelligence) curriculum at Alva’s Institute of Engineering & Technology (AIET), Mangalore mainly focuses on analytical and critical thinking. As the MBA (Artificial Intelligence) course unfolds, students develop several important skills that increases their employability. As per syllabus of MBA (Artificial Intelligence) at Alva’s Institute of Engineering & Technology (AIET) also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.
MBA (Artificial Intelligence) curriculum at Alva’s Institute of Engineering & Technology (AIET) includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The MBA (Artificial Intelligence) syllabus at Alva’s Institute of Engineering & Technology (AIET) aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.
Additional curriculum at Alva’s Institute of Engineering & Technology (AIET)
Note: Given below syllabus is based on the available web sources. Please verify with the Alva’s Institute of Engineering & Technology (AIET), Mangalore for latest MBA (Artificial Intelligence) curriculum.
The MBA in Artificial Intelligence program is designed to equip students with a strong foundation in both business management and AI technologies. Core courses cover essential business subjects such as finance, marketing, and strategic management. Specialized AI courses delve into machine learning, natural language processing, computer vision, and AI ethics. Students also work on AI projects, applying their knowledge to real-world problems. The curriculum ensures graduates are prepared to lead AI-driven initiatives, make data-driven decisions, and leverage AI for innovation in various industries.
1st Year OR 1st & 2nd Semester Syllabus of MBA (Artificial Intelligence)
S.no | Subjects |
1 | Management Process and Organization Behavior |
2 | Fundamental of AI for Managers |
3 | Business Analytics |
4 | Business Environment |
5 | Corporate Finance |
6 | Statistics for Business Decision |
7 | Seminar |
2nd Year OR 3rd & 4th Semester Syllabus of MBA (Artificial Intelligence)
S.No | Subjects |
1 | Strategic Management |
2 | Privacy, Ethics & Regulations in AI |
3 | Artificial Neural Network |
4 | Regression and Time Series Models |
5 | Seminar |
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