MBA (Data Analytics) Course at St. Peter's Institute of Higher Education And Research - (SPIHER), Chennai Syllabus & Subjects Semester Wise

The MBA (Data Analytics) syllabus at St. Peter's Institute of Higher Education And Research - (SPIHER), Chennai is designed to provide overall knowledge to the students with a strong foundation. MBA (Data Analytics) faculty at St. Peter's Institute of Higher Education And Research - (SPIHER) specially focus on in-depth learning to relevant subjects. At first semester syllabus of MBA (Data Analytics) at St. Peter's Institute of Higher Education And Research - (SPIHER), students learn the basics of programme. A strong foundation is very important for comprehensive learning. MBA (Data Analytics) syllabus at St. Peter's Institute of Higher Education And Research - (SPIHER), Chennai maintains a balance between theoretical knowledge and practical knowledge.

MBA (Data Analytics) first year students at St. Peter's Institute of Higher Education And Research - (SPIHER) are introduced with core subjects. Then they are encouraged to explore other area for a broader perspective. St. Peter's Institute of Higher Education And Research - (SPIHER), Chennai also provides practical training sessions, workshops, projects, and case studies to enhance student skills. MBA (Data Analytics) syllabus at St. Peter's Institute of Higher Education And Research - (SPIHER), Chennai is also frequently updated to give industry relevant training and knowledge to students. St. Peter's Institute of Higher Education And Research - (SPIHER) strives to provide a nurturing environment where students can learn new skills. The hands-on training sessions at St. Peter's Institute of Higher Education And Research - (SPIHER) 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 St. Peter's Institute of Higher Education And Research - (SPIHER), Chennai 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 St. Peter's Institute of Higher Education And Research - (SPIHER) also includes real-life projects and internship programs. It helps students critical thinking and gives them real-world experience.

MBA (Data Analytics) curriculum at St. Peter's Institute of Higher Education And Research - (SPIHER) includes group discussions, guest lectures, case studies, and skill development workshops to enhance the learning experience. The MBA (Data Analytics) syllabus at St. Peter's Institute of Higher Education And Research - (SPIHER) aims to create well-rounded professionals equipped with the necessary skills and knowledge to succeed in their chosen fields.

Additional curriculum at St. Peter's Institute of Higher Education And Research - (SPIHER)

Workshops and Seminars - Regular sessions with industry experts help MBA (Data Analytics) students at St. Peter's Institute of Higher Education And Research - (SPIHER) to stay updated with current trends.
Group Projects - Collaborative projects according to St. Peter's Institute of Higher Education And Research - (SPIHER) syllabus develop teamwork and problem-solving skills.
Case Studies - MBA (Data Analytics) syllabus offers analysis of real-world scenarios to apply theoretical knowledge.
Extracurricular Activities - St. Peter's Institute of Higher Education And Research - (SPIHER) 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 St. Peter's Institute of Higher Education And Research - (SPIHER), Chennai 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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