MBA Data Analytics Syllabus - National Institute of Technology Srinagar

  • Years 2 Years
  • Type Course Post Graduate
  • stream Management
  • Delivery Mode
Written By universitykart team | Last updated date Jul, 07, 2024

The MBA (Data Analytics) syllabus at National Institute of Technology , Srinagar is designed to provide overall knowledge to the students with a strong foundation. MBA (Data Analytics) faculty at National Institute of Technology specially focus on in-depth learning to relevant subjects. At first semester syllabus of MBA (Data Analytics) at National Institute of Technology , students learn the basics of programme. A strong foundation is very important for comprehensive learning. MBA (Data Analytics) syllabus at National Institute of Technology , Srinagar maintains a balance between theoretical knowledge and practical knowledge.

MBA (Data Analytics) first year students at National Institute of Technology are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. National Institute of Technology , Srinagar also provides practical training sessions, workshops, projects, and case studies to enhance student skills. MBA (Data Analytics) syllabus at National Institute of Technology , Srinagar is also frequently updated to give industry relevant training and knowledge to students. National Institute of Technology strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at National Institute of Technology enable MBA (Data Analytics) students to apply knowledge and skills in a controlled environment and get required experience.

According to syllabus of MBA (Data Analytics) progress, students learn advanced topics and complex concepts. The MBA (Data Analytics) curriculum at National Institute of Technology , Srinagar mainly focuses on analytical and critical thinking. As the MBA (Data Analytics) course unfolds, students develop several important skills that increases their employability. As per syllabus of MBA (Data Analytics) at National Institute of Technology also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.

MBA (Data Analytics) curriculum at National Institute of Technology includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The MBA (Data Analytics) syllabus at National Institute of Technology 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 Technology

  1. Workshops and Seminars - Regular sessions with industry experts help MBA (Data Analytics) students at National Institute of Technology to stay updated with current trends.
  2. Group Projects - Collaborative projects according to National Institute of Technology syllabus develop teamwork and problem-solving skills.
  3. Case Studies - MBA (Data Analytics) syllabus offers analysis of real-world scenarios to apply theoretical knowledge.
  4. Extracurricular Activities - National Institute of Technology offers several activities like sports, clubs, societies, etc. to encourage overall development.

Note: Given below syllabus is based on the available web sources. Please verify with the National Institute of Technology , Srinagar for latest MBA (Data Analytics) curriculum.

MBA Data Analytics Syllabus:


The MBA in Data Analytics syllabus focuses on harnessing the power of data for informed decision-making. Core courses cover statistical analysis, data visualization, and machine learning. Specialized subjects include big data analytics, predictive modeling, and data-driven business strategy. Students often work on data projects and collaborate with industry partners. Graduates are well-equipped for roles in data analysis, business intelligence, and data science.

Semester 1 Semester 2
Data Analytics Foundations Machine Learning for Data Analytics
Statistical Methods for Business Analytics Big Data Analytics and Management
Managerial Economics Operations Research for Data Analytics
Financial Accounting for Analytics Marketing Analytics
Organizational Behavior and Leadership Data Visualization and Communication
Business Communication Skills Database Management and SQL
Business Analytics Capstone Project (Part 1) Business Analytics Capstone Project (Part 2)
Semester 3 Semester 4
Predictive Analytics and Modeling Text Analytics and Natural Language Processing
Data Mining Techniques Data Governance and Ethics
Supply Chain Analytics Customer Analytics and Relationship Management
Financial Analytics Social Media Analytics
Strategic Management for Analytics Strategic Analytics and Decision Making
Business Analytics Capstone Project (Part 3) Business Analytics Capstone Project (Part 4)

Projects

 

Throughout the MBA in Data Analytics program, students are required to work on various projects to apply their skills and knowledge in real-world scenarios. These projects aim to enhance their analytical abilities, problem-solving skills, and decision-making capabilities. 

 

The projects can involve tasks such as data analysis, data visualization, predictive modeling, and business strategy formulation based on data insights. Students typically work individually or in teams to complete these projects, which may culminate in a final capstone project where they showcase their skills and present their findings to faculty and industry experts.

 

Reference Books

 

(1). "Data Science for Business" by Foster Provost and Tom Fawcett

(2). "Python for Data Analysis" by Wes McKinney

(3). "R for Data Science" by Hadley Wickham and Garrett Grolemund

(4). "Big Data: A Revolution That Will Transform How We Live, Work, and Think" by Viktor Mayer-Schönberger and Kenneth Cukier

(5). "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die" by Eric Siegel

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