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About
The
Program
Bringing value to stakeholders of the company by analyzing the data to propel the business towards growth is what Business Analytics is all about.
Knowledge of analytical tools and techniques, data visualization techniques, forecasting methods and analyzing business processes is the required skill set for a successful business analyst.
Post Graduate Certificate Program Management in Business Analytics is designed in such a way that you will get expertise in the latest Business Analytics tools and techniques. This course will train you in a practical manner with real-world case studies, ensuring that you are market ready. Throughout the course, you will receive clear guidance on how to implement analytical techniques and this course will demystify data analysis and will equip you with concrete skills to apply at your workplace.
Unique Pedagogy
The online course gives a detailed understanding of the latest technologies and developments in the finance domain. Industry Experts conduct Live interactive online sessions where you get hands-on training through a Capstone Project.
Industry Collaboration
Launch your global career with MITSDE. Partner with us to gain industry-leading expertise from renowned institutions. Our curriculum integrates global best practices, equipping you with the skills and connections to thrive on the international stage. Graduate with a competitive edge and unlock a world of career possibilities.
World Class Faculty
Industry experts from global financial institutions with over 15 years of work experience in top management positions will help you develop your skills and impart real-time knowledge through this course.
Learning
Outcomes
Course Syllabus
| S.No | Code | Subject | Credits |
|---|---|---|---|
| 1 | FS1F01 | Foundations of Business Management (HR, Marketing, Finance & Operations) | 4 |
| 2 | FS1LA1 | Legal Aspects of Business | 4 |
| 3 | FS2C10 | Strategic Management | 4 |
| 4 | FS2C07 | Management Information System | 4 |
| 5 | FS2C11 | Business Analytics | 4 |
| S.No | Code | Subject | Credits |
|---|---|---|---|
| 1 | FS2DB1 | Data Mining for Business Analytics | 4 |
| 2 | FS3EL6 | Predictive Modeling | 4 |
| 3 | FS3FM4 | Financial Analytics | 4 |
| 4 | FS3EL4 | Marketing Analytics | 4 |
| 5 | FS3LSC1 | Supply Chain Analytics | 4 |
| 6 | PWPGC | Project Work | 6 |
- The above course curriculum is subject to revision as per AICTE guidelines from time to time and as per industry updates.
- Exams would be conducted during the January and July exam cycles.
- All the Exams at MITSDE (Internal & External) are in the form of Multiple Choice Questions.
- Student will have to attempt all the components in the Learning Management System and submit TWO Quizzes (30 marks each) for each subject.
- Internal Examinations carry 60% marks (2 Quizzes of 30 Marks each) and External Proctored Exam carry 40% weightage (passing criteria for both internal & external exam is 50%).
Program Fees
₹ 64,000 /-
Fees Options
- Installment 1
- Installment 2
- Installment 3
Course fee - Installment
- ₹ 25,000 /-
- Within 3 months - ₹ 19,500/-
- Within 6 months - ₹ 19,500/-
Course fee - Lumpsum
- Discount- ₹ 06,000 /-
- -
- Total Lumpsum- ₹ 58,000 /-
- Students are required to pay additional exam fee per exam per attempt and Project Evaluation Fees. For Installments
- First Installment needs to be paid at the time of admission.
- Second Installment needs to be paid within 3 months from the date of admission.
- Third Installment needs to be paid within 6 months from the date of admission
Bridging
The Data
Science
Talent
Supply
Gap
The demand and interest for data science is growing on an ever-increasing pace, but there is a gap between talent demand and availability. As businesses increasingly rely on data analytics to drive sustainable growth, the demand for skilled data scientists is soaring.
According to a 2018 report by Indeed, there has been a staggering 29% year-over-year increase in demand for data scientists. Since 2013, this demand has surged by an incredible 344%. Despite this rapid rise, the supply of qualified data science professionals has not kept pace, with job seeker interest growing at a much slower rate of just 14%.
This growing talent supply gap presents a significant opportunity for professionals looking to advance their careers in this dynamic field. MITSDE in collaboration with KPMG, is aiming to address this critical gap. The Business Analytics and Business Intelligence Certification will equip students with the comprehensive skills and knowledge required to excel in data analytics and meet the industry's escalating demands.
KPMG’s Data
Science Academy
The Business Analytics and Business Intelligence Certification leverages the extensive expertise of KPMG's Data Science Academy. This partnership ensures that our curriculum is not only academically rigorous but also highly practical and aligned with industry demands. Here are the key features of the Data Science Academy that enhance the learning experience:
Covers All Data
Science Roles and Users
Our program is meticulously designed to cater to a diverse range of roles within the data science field. The course covers all levels of proficiency, ensuring that every participant gains the knowledge they need to succeed.
Competency-Based
Curriculum
The curriculum is structured around a standard competency model for data science professionals. This model addresses various proficiency levels, ensuring that each learner can progress at their own pace and build a solid foundation in data science.
Practitioner Oriented
The course is led by experts from KPMG's data science practice, who bring a wealth of experience from real-world consulting assignments. This practitioner-oriented approach provides students with practical insights and hands-on experience, preparing them to tackle real data science challenges in their careers.
Multi-Modal Delivery
Flexibility is at the core of our program delivery. The curriculum is available through various modes, including virtual and online classes, in-person classroom sessions, and a blend of both. Additionally, students have access to reading materials, assessments, and labs, allowing them to learn in a manner that suits their schedule and learning style.
Continued Coaching and Mentorship
Learning doesn't end with the completion of classes. Our program offers continued access to experts through mentorship and project coaching. This ongoing support ensures that students can apply their learning in practical scenarios and continue to grow their skills even after the formal training ends.
Customized for Context and Need
We understand that each learner's journey is unique. To address this, a thorough analysis is conducted to assess the learning gap between current and required skills. Based on this assessment, a customized learning plan is prepared, tailored to the specific needs and context of each student. This personalized approach maximizes learning outcomes and ensures that students are well-prepared to meet their career goals.
Course Content (Modules)
- Introduction to Python
- Data Types in Python
- Data Manipulation using Pandas
- Introduction to Data Analytics
- Types of Analytics and industry used cases
- Standard process and algorithms involved in Analytics for Business
- Types of data - which data requires regression analysis
- Understanding the concepts of Linear Regression
- Performing regression, and understanding the EDA parameters
- Univariate and Multivariate linear regression - Case Study
- Regression vs Classification
- Understanding the requirement of Logistic Regression
- Performing Logistic Regression and understanding error analysis
- Basics of classification models – types and differences
- Performing classification models – Case Study
- Evaluation metrics for classification and confusion matrix
- Introduction to Time Series Analysis - What makes a data Time series data
- Components - Trends, Seasons and Cycles
- Basic Forecasting Techniques - Moving Average, Naïve Bayes with error analysis
- Monte Carlo Simulation, Exponential smoothening with examples
- ARIMA forecasting - Case Study
- Introduction and Importance of Data Visualization, Introduction to Tableau Interface
- Connecting data sources in Tableau
- Types of charts in visualization, Basic and advanced filters in Tableau
- Parameters, sets and groups in Tableau, Data joins and Data blending
- Creating calculated fields, Dashboard Creation in Tableau, Story cards in Tableau
Key Course Features
The program is designed to provide 95% hands-on learning experience. This will allow you to gain practical skills in applying business analytics and business intelligence concepts to real-world scenarios.
The program covers Python and Tableau, which are the most popular programming languages used in business analytics and data science.
The program includes a 35 Hrs of live session and 5 Hrs of project component, which will allow you to apply your learnings to a real-world problem.
The program is open to anyone interested in learning business analytics and business intelligence, regardless of their background.
The program is delivered online, so you can learn from anywhere in the world.
| S.No | Course Duration | Extension | Validity |
|---|---|---|---|
| 1 | 1 Year | 6 Months | 1 Year 6 Months |
Successful completion of the program will ready you to pursue multiple roles in Business Analytics, across various domains. Few exceptional job prospects are:
- Big Data Analyst
- Financial Analyst
- Marketing Analyst
- Business Intelligence and Analytics Consultant
- Research analyst
- Data Scientist
- Data Visualization Analyst
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