2 Years
Post Graduate
Management
The MBA (Artificial Intelligence) syllabus at National Institute of Industrial Engineering, Mumbai is designed to provide overall knowledge to the students with a strong foundation. MBA (Artificial Intelligence) faculty at National Institute of Industrial Engineering specially focus on in-depth learning to relevant subjects. At first semester syllabus of MBA (Artificial Intelligence) at National Institute of Industrial Engineering, students learn the basics of programme. A strong foundation is very important for comprehensive learning. MBA (Artificial Intelligence) syllabus at National Institute of Industrial Engineering, Mumbai maintains a balance between theoretical knowledge and practical knowledge.
MBA (Artificial Intelligence) first year students at National Institute of Industrial Engineering are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. National Institute of Industrial Engineering, Mumbai also provides practical training sessions, workshops, projects, and case studies to enhance student skills. MBA (Artificial Intelligence) syllabus at National Institute of Industrial Engineering, Mumbai is also frequently updated to give industry relevant training and knowledge to students. National Institute of Industrial Engineering strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at National Institute of Industrial Engineering 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 National Institute of Industrial Engineering, Mumbai 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 National Institute of Industrial Engineering also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.
MBA (Artificial Intelligence) curriculum at National Institute of Industrial Engineering includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The MBA (Artificial Intelligence) syllabus at National Institute of Industrial Engineering aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.
Additional curriculum at National Institute of Industrial Engineering
Note: Given below syllabus is based on the available web sources. Please verify with the National Institute of Industrial Engineering, Mumbai 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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