Post Graduate Diploma in Management (Big Data Analytics)
PGDM-Big Data Analytics
Post Graduate Diploma in Management (Big Data Analytics) is an AICTE approved Two-Year Full-Time programme at Asia Pacific Institute of Management New Delhi.
Data analytics for businesses is given importance throughout the programme. Students will be trained to core managerial concepts, Big Data, data-driven decision making, learning through case studies, hands-on experience to handle various analytical software and toolsfor data visualization, reporting, data manipulation, and statistical analysis. Through this program, the participantswill learn the skills, technologies, applications, and processes to be ready for industry to work as business analysts and data scientists.
PGDM-BDA Programme
The PGDM-BDA program will expose students to statistical concepts, data management, analysing big data, and building intelligent systems using emerging technologies like artificial intelligence, machine learning, deep learning, blockchain and related tools, techniques, and algorithms.
In today’s globalized business environment, data is becoming important part of strategy and decision making from board room to local shop floor. Themajor emphasis will be on providing hands-on training to the students using all major software tools in vogue and working on actual industry projects.
The PGDM-BDA program is a job-oriented demanding program which enhances the career prospects of the students.
Programme Objectives
- To acquaintthe students with the increasing role of Big Data & Analytics and drawn insights bring to managerial decision making at different levels of Management.
- Developing analytical skills to work in the diverse set of data driven industries like E-commerce, banking and financial services, customer relation management, operations, supply chain and healthcare etc.
- Developing analysis & synthesis frameworks for analytical models, strategies, and their deployment in various industries.
- Enhancing skills to build capabilities among students to work in technological driven environments.
- Creating optimal data-driven innovative strategies for the organizations or businesses
Exciting job roles and opportunities in MNC’s and Tech companies are-
- Data Scientist
- Data Analyst
- Business Analyst.
Pedagogy
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, individual or group presentations.
Curriculum
In two years of the programme, students must undergo both 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 rigorous grounding in the discipline of management and the understanding of business in multidimensional context. The core courses are taught in the First year, which is divided into three Terms (a Term is typically of 10 weeks of classes and at most 2 weeks of examinations). Elective courses begin from Term-3 onwards. Thus, while Term-1 and Term-2 have only core courses, Term-3 have both core and elective courses. The elective courses allow students to choose and develop proficiency in their Area of Specialization.
Programme Structure and Credits
The Programme structure and credit of Post Graduate Diploma in Management (Big Data Analytics) is 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 weight age of a course. One credit equals 10 in-class contact hours. The rule of the thumb is that a 3.0 credit course involves around 100 hours of work with 30 hours in the classroom, and the rest for preparation and assignments
The students are required to complete 102 credits (in total) for the award of Post Graduate Diploma in Management (Big Data Analytics). 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. The students are expected to become Data Analytics professional as an outcome of the course
Participant profile
- Admission is open for both fresh graduates and a graduate with relevant work experience.
- Applicants for the PGDM-BDA may be from any discipline including Engineering, Humanities, Commerce, and Economics, or any other branch of education preferably with Math’s at 10+2 level or at graduation.
Eligibility for PGDM-BDA
The eligibility criteria are as follows-
- Candidate should hold an undergraduate degree with minimum 50% marks in aggregate of all the subjects studied at any of the Universities recognised under UGC Act 1956, the Ministry of Education, Government of India.
- It is desirable that candidate fulfill all the academic requirements before enrolling for the program. In case of any mismatch of information provided by the applicant, with the original documents, will lead to cancellation of candidature.
- The students appearing in final year degree examination in the year 2022 may also apply subject to furnishing the proof of having passed graduation by obtaining minimum 50% marks in aggregate total of all the subjects studied.
- The institute also prefers valid CAT/XAT//CMAT/MAT scores for the admission process.
- Final selection is based on group discussion (GD) and personal interview (PI). However, management holds the right to add or change some of the selection criteria as per AICTE norms.
How to Apply
Candidates interested in applying for this program are requested to note the following-
- Candidates can apply online/offline by visiting our website. For online application submission candidates need to pay either through net banking or credit/debit card.
- The admission is subjected to verification of the original documents and approval of the graduation degree by UGC/AICTE/AIU.
- The Institute reserves the right to change any information mentioned above.
Institute reserves the right to cancel the same in a pandemic like situation.
Note: In case of a dispute, the jurisdiction would be Delhi only.
Online Admission Process
- Create your new account to apply online.
- After logging in successfully, the admission form will be displayed.
- Kindly fill up all the details correctly as the same details will be used for filling up the admission form and for checking the status of the application later on.
- Applicants must fill up complete online application form with all mandatory star marked rows filled up.
- Finally submit the application form along with the non-refundable application fee.
Note:-Please fill up the data carefully and correctly since incorrect data will lead to rejection of the application. Admission to the PGDM-BDA Program at AIM, NEW DELHI is through CAT/XAT//CMAT/MAT valid score card.
Payment Instructions:-
The fee for admission application form will be as follows- - Cost of application form: Rs.1000/- for PGDM Big Data Analytics Program
The admission fee can be paid using either of these methods- Credit Card/ Debit Card/ Net Banking through a special dedicated and fully secure gateway to remove any glitches during payment process.
The admission fee can be paid using either of these methods- Credit Card/ Debit Card/ Net Banking through a special dedicated and fully secure gateway to remove any glitches during payment process.
In case of any difficulty, the candidates may contact admission office through email id admission@asiapacific.edu
PGDM-BDA Programme Fee Structure
2 years full time Programme | Batch 2022-24 | Academic Fee to be Paid
(Approved by All India Council for Technical Education, Ministry of Education, Govt. of India)
Note: Each student is required to pay Refundable security deposit of Rs.10, 000/- (payable at the time of registration) in addition to the total fees, which will be refunded after the completion of the PGDM-BDA program.
Cost of application form: Rs.1000/- for PGDM Big Data Analytics Program
Fee Composition: Tuition fee, Library Charges, Computer Lab, Internet Charges, books and fee for other activities such as Placement activities, Seminars, Workshops, Conferences, etc.
Fee Payment Details: The fee can be paid by Demand Draft drawn in favor of “Asia-Pacific Institute of Management” payable at "New Delhi". Student must write his/her name and phone numbers on the back side of Demand Draft and send it of the address of the Institute. Alternatively, students can also deposit the fees by RTGS/NEFT for credit of Asia Pacific Institute of Management.
The PGDM-BDA program course fee at Asia-Pacific Institute of Management is considered as one of the best within B-schools of Delhi-NCR region, it includes tuition fee and other related costs.
Essential courseware will be provided to the students from the well-stocked book bank of the campus library for the duration of the course on returnable basis. The academic fees is payable in installments as communicated in the admission offer letter.
Post Graduate Diploma in Management (Big Data Analytics)
A Post Graduate Diploma in Management-Big Data Analytics (PGDM-BDA) is a Two Year full-time Diploma course offered by the Institute that is recognized by the All India Council for Technical Education (AICTE), Ministry of Education, Government of India.
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Programme Structure and Credits: Course & Credit Briefings
The Programme structure and credit of Post Graduate Diploma in Management (Big Data Analytics) is 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 weight age of a course. One credit equals 10 in-class contact hours. The rule of the 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 student is required to do 102 credits (in total) for the award of Post Graduate Diploma in Management (Big Data Analytics). 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.
Year and Term Wise Credit Course Structure
Summer internship Programme (SIP) & Project work is a complementary component of the PGDM-BDA programs.
Courses in PGDM-BDA
Courses and Credits
The Courses & their Area along with their Credits offered to the students in the First Year is mentioned below:
Term-1
| 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 |
Term-2
| S.No | Name of the Course | Area | Credits |
|---|---|---|---|
| 1 | Written Analysis and Communication | Communication | 3.0 |
| 2 | Data Exploration with Analytical Tools | Information Technology | 2.0 |
| 3 | Management Technology Systems (MIS) | Information Technology | 3.0 |
| 4 | Marketing Management-II | Marketing | 1.0 |
| 5 | Human Resource Management | OB & HR | 1.0 |
| 6 | Organizational Design and Change | OB & HR | 1.0 |
| 7 | Business Research Methods | QT & OM | 1.0 |
| 8 | Cloud Computing & HPC Applications | Information Technology | 3.0 |
| 9 | Operations Management | QT & OM | 1.0 |
| Total Credits | 16.0 |
Term-3
| 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 |
Term-4
| 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 |
Term-5
| 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 |
Term-6
| 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 |
Electives
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:
- Advanced Analytics
- Programming with Python
- Business forecasting
- Descriptive Analytics
- Predictive Analysis
- Digital Economy and Emerging Business Models
- Data Analytics Using R
- Artificial Intelligence in Business
- Marketing Analytics
- Data Visualization for mangers
- Data Mining and Business Intelligence
- Advance Prescriptive Analytics
- Machine Learning
- Block chain and its Business Application
- Data Warehouse and SQL
- Data Analysis with Python (project work).
- Advance Data Visualization
- Big Data using Spark
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