The Asia Pacific Institute of Management in New Delhi offers an AICTE-approved two-year full-time Post Graduate Diploma in Management (big data analytics).
The programme emphasizes the significance of data analytics for businesses. Students are taught fundamental managerial concepts such as big data, data-driven decision-making, and case studies and gain hands-on experience with various analytical software and tools for data visualization, reporting, data manipulation, and statistical analysis. The PGDM in data analytics programmes teaches the participants about skills, technologies, applications, and processes needed to work as business analysts and data scientists in the industry.
This PGDM programme introduces students to statistical concepts, data management, big data analysis, and the development of intelligent systems using emerging technologies such as artificial intelligence, machine learning, deep learning, blockchain, and related tools, techniques, and algorithms.
Data is becoming increasingly crucial in strategy and decision-making in today's globalized business environment, from the boardroom to the local shop floor. The primary emphasis is on providing students with hands-on training in all major software tools currently in use and working on actual industry projects.
The PGDM programme is a job-oriented, demanding programme that improves students' career prospects.
The instructional methodology comprises an optimum mix of synectics, brainstorming, lectures, classroom discussions, case studies, simulations, role-plays, group discussions, sessions from industry professionals and trade, management games, sensitivity training, management films, industrial visits, and industry interaction. Students are encouraged to present their case analysis through written case reports and individual or group presentations.
In the programme's first two years, students must take core and elective courses. These courses are an eclectic mix of foundational, perspective-building, tools and techniques-oriented, and functional courses. The core courses provide a rigorous grounding in management and understanding business in a multidimensional context. They are taught in the first year, divided into three terms (typically 10 weeks of classes and at most 2 weeks of examinations). Elective courses begin from term 3 onwards. Thus, while terms 1 and 2 have only core courses, term 3 has both core and elective courses. The elective courses allow students to choose and develop proficiency in their area of specialization.
The programme structure and credit for the PGDM (Post Graduate Diploma in Management ) are designed as per AICTE. The concept of credits is used to indicate the number of in-class contact hours in a course and thus to define the weighted average of a course. One credit equals 10 in-class contact hours. The rule of thumb is that a 3.0 credit course involves around 100 hours of work, 30 hours in the classroom, and the rest for preparation and assignments.
The students must complete 101 credits (in total) for the award of a Post Graduate Diploma in Management (PGDM in big data analytics or PGDM in data analytics). Out of the required credits, 90 come from classroom teaching, and the balance comes from a summer internship and project work on big data analytics. The students are expected to become data analytics professionals as an outcome of the course.
Admission is open to both recent graduates and graduates with relevant work experience. Applicants for the PGDM in big data analytics and the PGDM in data science can belong to any discipline, including engineering, the humanities, commerce, economics, or any other branch of education, preferably with math at the 10+2 or graduation level.
The eligibility criteria are as follows-
Candidates interested in applying for this programme are requested to note the following:
The Institute reserves the right to cancel the same in a pandemic-like situation.
Note: In a dispute, the jurisdiction would be Delhi only.
The admission fee can be paid using either of these methods: credit card, debit card, or net banking, through a special dedicated and fully secure gateway to remove any glitches during the payment process.
The admission fee can be paid using either of these methods: credit card, debit card, or net banking, through a special dedicated and fully secure gateway to remove any glitches during the payment process.
In case of any difficulty, the candidates may contact the admission office through email at admissions@asiapacific.edu.
2-year full-time programme | Batch 2024-26 | Academic Fee to be Paid
(Approved by All India Council for Technical Education, Ministry of Education, Govt. of India)
A Post Graduate Diploma in Management (PGDM in big data analytics) is a 2-year full-time diploma course offered by the Institute recognized by the All India Council for Technical Education (AICTE), Ministry of Education, Government of India.
The programme structure and credit for the Post Graduate Diploma in Management (PGDM in big data analytics or PGDM in data analytics) are designed as per AICTE. The concept of credits is used to indicate the number of in-class contact hours in a course and thus to define the weighted average of a course. One credit equals 10 in-class contact hours. The rule of thumb is that a 3.0 credit course involves around 100 hours of work-30 hours in the classroom and the rest for preparation and assignments.
Asia-Pacific Institute of Management students must do 102 credits (in total) for the PGDM ( Post Graduate Diploma in Management ) award. Out of the required credits, 90 credits come from classroom teaching and the balance 12 credits from summer internship & Project work on big data analytics.
Summer internship Programme (SIP) & Project work is a complementary component of the PGDM-BDA programs.
Courses in PGDM-BDA
The Courses & their Area along with their Credits offered to the students in the First Year is mentioned below:
S.No | Name of the Course | Area | Credits |
---|---|---|---|
1 | Basics of Data Science | Data Analytics | 3.0 |
2 | Business statistics | Statistics | 3.0 |
3 | Marketing Management-I | Marketing | 2.0 |
4 | Human Behaviour in Organizations | OB & HR | 2.0 |
5 | Data Analytics for Decision Making | Analytics | 3.0 |
6 | Quantitative Techniques | QT | 3.0 |
7 | Managerial communication | Communication | 3.0 |
8 | Financial Accounting | Finance & Accounting | 2.0 |
Total Credits | 21.0 |
S.No | Name of the Course | Area | Credits |
---|---|---|---|
1 | Written Analysis and Communication | Communication | 3.0 |
2 | Data Exploration with Analytical Tools | Information Technology | 3.0 |
3 | Management Technology Systems (MIS) | Information Technology | 3.0 |
4 | Marketing Management-II | Marketing | 3.0 |
5 | Human Resource Management | OB & HR | 3.0 |
6 | Organizational Design and Change | OB & HR | 3.0 |
7 | Business Research Methods | QT & OM | 3.0 |
8 | Cloud Computing & HPC Applications | Information Technology | 3.0 |
9 | Operations Management | QT & OM | 1.0 |
Total Credits | 24.0 |
S.No | Name of the Course | Area | Credits |
---|---|---|---|
1 | Languages & Tools of Data Science | Analytics | 3.0 |
2 | Data Visualization | Information Technology | 3.0 |
3 | Digital Commerce | Information Technology | 3.0 |
4 | Project Management | QT & OM | 3.0 |
5 | Strategic Entrepreneurship and New Age Business Models | Strategy | 3.0 |
6 | Applied Programming | Analytics | 3.0 |
7 | Elective-1 Advanced Analytics | Analytics | 3.0 |
8 | Elective-2 Web Analytics | Analytics | 3.0 |
Total Credits | 24.0 |
S.No | Name of the Course | Area | Credits |
---|---|---|---|
1 | Business forecasting | Analytics | 2.0 |
2 | Descriptive Analytics | Analytics | 2.0 |
3 | Predictive Analysis with Modeling | Analytics | 2.0 |
4 | Digital Economy and Emerging Business Models | Analytics | 2.0 |
5 | Data Analytics Using R | Analytics | 3.0 |
6 | Artificial Intelligence in Business | Analytics | 2.0 |
7 | Marketing Analytics | Analytics | 2.0 |
8 | SIP | Analytics | 6.0 |
Total Credits | 21.0 |
S.No | Name of the Course | Area | Credits |
---|---|---|---|
1 | Advance Data Visualization | Analytics | 3.0 |
2 | Data Mining and Business Intelligence | Analytics | 3.0 |
3 | Advance Prescriptive Analytics | Analytics | 3.0 |
4 | Machine Learning | Analytics | 3.0 |
Total Credits | 12.0 |
S.No | Name of the Course | Area | Credits |
---|---|---|---|
1 | Block chain and its Business Application | Strategy | 1.0 |
2 | Big Data using Spark | Analytics | 1.0 |
3 | Data Analysis with Python (project work ) | Analytics | 6.0 |
Total Credits | 8.0 |
From Term-3 in the First Year, students will be required to undertake Elective courses. A student enrolled in the PGDM (BDA) program, is required to complete 47 credits from the Elective courses spread over Term-3 to Term-6 in the Second year of the Two Year Program.
In order to provide the opportunities to students to specialize in their Area of choice, each sentient area will offer Elective courses. The Sentient Area may specify certain Elective courses as Specialization Area Pre-requisite (SAPR) courses that must be taken by those students who have chosen that Area to Specialize in.
The Elective courses will be offered by the following Sentient Areas:
1. What is PGDM in Big Data Analytics?
Ans. The Postgraduate Diploma in Management in Big Data Analytics is a programme designed to train students in big data analytics. The programme is intended to provide students with the knowledge and skills needed to analyze large amounts of complex data using specialized tools and techniques.
2. How is PGDM in Big Data Analytics different from PGDM in Data Science?
Ans.While both the PGDM in Big Data Analytics and the PGDM in Data Sciences are focused on analytics, they have some differences. The main distinction is that the PGDM in big data analytics focuses on analyzing large data sets using tools and techniques. In contrast, the PGDM in data science is a broader curriculum that includes data management, statistics, and machine learning topics.
3. What career roles are offered in PGDM in Data Analytics and PGDM in Data Science?
Ans.Big data analytics PGDM offers roles such as data analyst, business analyst, and data engineer. The PGDM in data science prepares students for various data science careers, including data scientist, machine learning, and data analyst.
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