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SSBM

Doctor of Business Administration SSBM, Geneva

4,563 Ratings

Offer: Get Advanced Certification in Data Analytics by IHub, IIT Roorkee

Ranked Top 10 in Europe

Take your skills to new heights with this DBA program from the Swiss School of Business and Management in Geneva. Made for experienced executives and business leaders, this program prioritizes hands-on learning to refine your leadership, strategic thinking, and decision-making skills. SSBM, a global business school, has developed this DBA program in collaboration with experienced industry partners. Receive guaranteed Swiss-quality education with this DBA degree.

Accredited & Certified by

ACBSP CHEA EDU
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SSBM
Course Introduction

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Learning Format

Online

Program Duration

36 Months

Career Services

by Intellipaat

DBA

by SSBM

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About Program

This course was designed to empower experienced professionals with advanced knowledge and research skills to enable them to drive innovation. Upon completion, learners will be awarded an DBA degree from SSBM, Geneva.

Key Highlights

36 months DBA program
SSBM Connect
ACBSP Accredited
DBA degree from SSBM, Geneva
24*7 Support
SSBM Alumni Status
1:1 Mentor Support
Multiple Case Studies
Career Services by Intellipaat
120 ECTS Credits
Free Adv. Certification in Data Analytics from iHUB, IIT Roorkee
One-on-one Thesis Supervision with SSBM Faculty
Learn Data Analytics from Industry experts by Intellipaat
No-Cost EMI Option
Access to SSBM e-Library and ESBCO
Swiss Quality Education

About SSBM (Swiss School of Business and Management, Geneva)

SSBM is a renowned college in Geneva, Switzerland, and is known for its Swiss-quality education and excellence all over the world. The institute has partnered with over 30 top companies to design its courses and has a remarkable set of alumni across the globe.

Key Achievements:

  • The university holds the EduQua (a Swiss national quality assurance body) label for delivering quality education to students.
  • It is an ACBSP-accredited institution.
  • Ranked as the #1 leader in providing innovative financial educational programs by Silcom Consulting
  • Ranked #6th best private institution in Switzerland by Primavera
  • Ranked #2 globally for its learning management system by LMS.

Upon Completion of this course, you will:

  • Receive Doctorate of Business Administrations (DBA) degree from SSBM, Geneva
SSBM DBA Click to Zoom

About iHUB DivyaSampark, IIT Roorkee

iHUB DivyaSampark aims to enable innovative ecosystem in new age technologies like AI, ML, Drones, Robots, data analytics (often called CPS technologies) and becoming the source for the next generation of digital technologies, products and services by promoting, enhancing core competencies, capacity building, manpower training to provide solutions for national strategic sectors andRead More..

Key Achievements of IIT Roorkee:

Advanced Certification in Data Analytics iHUB IIT R Click to Zoom

Who can apply for the course?

  • Individuals with a master’s degree and a keen interest in learning business strategy, human resources, and marketing
  • Senior managers operating at a strategic level in the workplace
  • IT professionals with a master’s degree looking for a career transition to management
  • Professionals who wish to upgrade to the C-suite
who can apply

What roles can a DBA graduate play

C-Level Executive

Guiding the operational course of an organization requires adept high-level executives. Businesses value professionals who guarantee the achievement of their objectives. A DBA will furnish you with the sharp insight and capabilities needed for this role.

Economic Analyst

Economists drive a nation’s economy by researching, analyzing data, and tracking consumer trends. They also address resource distribution and work to bridge any gaps.

Professor and Postdoctoral Researcher

DBA offers a definite way to launch your career in academics. Universities consistently seek skilled and knowledgeable teaching faculty, making the DBA an ideal choice if you are enthusiastic about pursuing a career in teaching.

Corporate Treasury

The role involves managing a firm’s liquid assets, capital, and risk, along with assessing the creditworthiness of its counterparties.

Risk Manager

They analyze risks associated with major business decisions and develop scenarios to avert future damage to the company.

Director of Human Resources

The HR director oversees organizational staffing, managing recruitment, hiring, training, performance evaluations, and addressing disciplinary matters, including termination.

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Skills to Master

Leadership

Accounting

Entrepreneurship

Business Ethics

Financial Management

Corporate Finance

Managerial Economics

Strategy Management

Research

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Meet Your Mentors

Curriculum

Live Course Self Paced Industry Expert Academic Faculty

Concept Paper – This is a short summary that provides a high-level idea of the topic the learner would like to research.

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Literature Review – This is a thorough, systematic, and advanced summary of the literature to be used for research.

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Research Proposal – This is the guiding document that provides details about the research and why it is important.

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Dissertation/Thesis

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Adv. Certification in Data Analytics by iHub IIT Roorkee Live Sessions (Optional)

  1. Introduction to SQL
  2. Database Normalization and Entity Relationship Model(self-paced)
  3. SQL Operators
  4. Working with SQL: Join, Tables, and Variables
  5. Deep Dive into SQL Functions
  6. Working with Subqueries
  7. SQL Views, Functions, and Stored Procedures
  8. Deep Dive into User-defined Functions
  9. SQL Optimization and Performance
  10. Advanced Topics
  11. Managing Database Concurrency
  12. Practice Session

Case Study

Writing comparison data between past year to present year with respect to top products, ignoring the redundant/junk data, identifying the meaningful data, and identifying the demand in the future(using complex subqueries, functions, pattern matching concepts).

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Introduction to Python and IDEs – The basics of the python programming language, how you can use various IDEs for python development like Jupyter, Pycharm, etc.

Python Basics – Variables, Data Types, Loops, Conditional Statements, functions, decorators, lambda functions, file handling, exception handling ,etc.
Object Oriented Programming – Introduction to OOPs concepts like classes, objects, inheritance, abstraction, polymorphism, encapsulation, etc.

Data Manipulation with Numpy, Pandas, and Visualization – Using large datasets, you will learn about various techniques and processes that will convert raw unstructured data into actionable insights for further computations i.e. machine learning models, etc.

Case Study – The culmination of all the above concepts with real-world problem statements for better understanding.

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Descriptive Statistics

  1. Measure of central tendency, measure of spread, five points summary, etc.

Probability

  1. Probability Distributions, Probability in Business Analytics
  2. Probability Distributions, Binomial distribution, Poisson distribution, bayes theorem, central limit theorem.

Inferential Advanced Statistics (by Academic Faculty)

  1. Correlation, covariance, confidence intervals, hypothesis testing, F-test, Z-test, t-test, ANOVA, chi-square test, etc.

Case Study

This case study will cover the following concepts:

  1. Building a statistical analysis model that uses quantification, representations, and experimental data
  2. Reviewing, analyzing, and drawing conclusions from the data
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Introduction to Machine learning

  1. Supervised, Unsupervised learning.
  2. Introduction to scikit-learn, Keras, etc.

Regression

  1. Introduction classification problems, Identification of a regression problem, dependent and independent variables.
  2. How to train the model in a regression problem.
  3. How to evaluate the model for a regression problem.
  4. How to optimize the efficiency of the regression model.

Classification

  1. Introduction to classification problems, Identification of a classification problem, dependent and independent variables.
  2. How to train the model in a classification problem.
  3. How to evaluate the model for a classification problem.
  4. How to optimize the efficiency of the classification model.

Clustering

  1. Introduction to clustering problems, Identification of a clustering problem, dependent and independent variables.
  2. How to train the model in a clustering problem.
  3. How to evaluate the model for a clustering problem.
  4. How to optimize the efficiency of the clustering model.

Supervised Learning

  1. Linear Regression – Creating linear regression models for linear data using statistical tests, data preprocessing, standardization, normalization, etc.
  2. Logistic Regression – Creating logistic regression models for classification problems – such as if a person is diabetic or not, if there will be rain or not, etc.

Unsupervised Learning

  1. K-means – The k-means algorithm that can be used for clustering problems in an unsupervised learning approach.
  2. Dimensionality reduction – Handling multi dimensional data and standardizing the features for easier computation.
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  1. Classification reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
  2. Confusion matrix – To evaluate the true positive/negative, false positive/negative outcomes in the model.
  3. r2, adjusted r2, mean squared error, etc.
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Making use of time series data, gathering insights and useful forecasting solutions using time series forecasting.

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Business Domains – Learn about various business domains and understand how one differs from the other.

  1. Finance
  2. Marketing
  3. Retail
  4. Supply Chain

Understanding the business problems and formulating hypotheses – Learn about formulating hypotheses for various business problems on samples and populations.

Exploratory Data Analysis to Gather insights – Learn about the exploratory data analysis and how it enables a fool proof producer of actionable insights.

Data Storytelling: Narrate stories in a memorable way – Learn to narrate business problems and solutions in simple relatable format that makes it easier to understand and recall.

Case Study
This case study will cover the following concepts:

  1. Create actionable insights from raw unstructured data to solve real world business problems.
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Feature Selection – Feature selection techniques in python that includes recursive feature elimination, Recursive feature elimination using cross validation, variance threshold, etc.

Feature Engineering – Feature engineering techniques that help in reducing the best features to use for data modeling.

Model Tuning – Optimization techniques like hyperparameter tuning to increase the efficiency of the machine learning models.

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Problem Statement and Project Objectives – You will learn how to formulate various problem statements and understand the business objective of any problem statement that comes as a requirement.

Approach for the Solution – Creating various statistical insights based solutions to approach the problem will guide your learnings to finish a project from scratch.

Optimum Solutions – Formulating actionable insights backed by statistical evidence will help you find the most effective solution for your problem statements.

Evaluation Metrics – You will be able to apply various evaluation metrics to your project/solution. It will validate your approach and point towards shortcomings backed by insights, if any.

Gathering Actionable insights – You will learn about how a problem’s solution isn’t just creating a machine learning model, the insights that were gained from your analysis should be presentable in the form of actionable insights to capitalize on the solutions formulated for the problem statement.

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Customer Churn – The case study involves studying the customer data for a given XYZ company, and using statistical tests and predictive modeling, we will gather insights to efficiently create an action plan for the same.

Sales Forecasting – By studying the various patterns and sales data for a firm/store, we will use the time series forecasting method to forecast the number of sales for the next given time period(weeks, months, years, etc.)

Census – After studying the population data, we will gather insights and through predictive modeling try to create actionable insights on the same, it could be average income of an individual, or most likely profession, etc.

Predictive Modeling – Various case studies on categorical and continuous data, to create predictive models that will predict specific outcomes based on the business problems.

HR Analytics – Based on the data provided by a firm, we will study the HR analytics data, and create actionable insights using various statistical tests and hypothesis testing.

Dimensionality Reduction – To understand the impact of multidimensional data, we will go through various dimensionality reduction techniques and optimize the computational time on the same that will eventually be used for various classification and regression problems.

Housing – A case study that will give you insight into how real estate firms can narrow down on the pricing, customer choices, etc. using various predictive modeling techniques.

Customer Segmentation – Using unsupervised learning techniques, we will learn about customer segmentation, which can be quite useful for e-commerce sectors, stores, marketing funnels, etc.

Inventory Management – In this case study, you will learn about how meaningful insights can be used to drive a supply chain, using predictive modeling and clustering techniques.

Disease Prediction – A medical endeavor that is achieved through machine learning will give you an insight into how the predictive model can prove to be a great marvel in early detection of various diseases.

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Elective

Excel Fundamentals

  1. Reading the Data, Referencing in formulas , Name Range, Logical
  2. Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering
  3. Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security
  4. VBA Macros, Ranges and Worksheet in VBA
  5. IF conditions, loops, Debugging, etc.

Excel For Data Analytics

  1. Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.

Data Visualization with Excel

  1. Charts, Pie charts, Scatter and bubble charts
  2. Bar charts, Column charts, Line charts, Maps
  3. Multiples: A set of charts with the same axes, Matrices, Cards, Tiles

Ensuring Data and File Security

  1. Data and file security in Excel, protecting row, column, and cell, the different safeguarding techniques.

Getting started with VBA Macros

  1. Learning about VBA macros in Excel, executing macros in Excel, the macro shortcuts, applications, the concept of relative reference in macros, In-depth understanding of Visual Basic for Applications, the VBA Editor, module insertion and deletion, performing action with Sub and ending Sub if condition not met.

Statistics with Excel

  1. ONE TAILED TEST AND TWO TAILED T-TEST, LINEAR REGRESSION,PERFORMING STATISTICAL ANALYSIS USING EXCEL, IMPLEMENTING LINEAR REGRESSION WITH EXCEL
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Power BI Basics

  • Introduction to PowerBI, Use cases and BI Tools , Data Warehousing, Power BI components, Power BI Desktop, workflows and reports , Data Extraction with Power BI.
  • SaaS Connectors, Working with Azure SQL database, Python and R with Power BI
  • Power Query Editor, Advance Editor, Query Dependency Editor, Data Transformations, Shaping and Combining Data ,M Query and Hierarchies in Power BI.

DAX

  • Data Modeling and DAX, Time Intelligence Functions, DAX Advanced Features

Data Visualization with Analytics

  • Slicers, filters, Drill Down Reports
  • Power BI Query, Q & A and Data Insights
  • Power BI Settings, Administration and Direct Connectivity
  • Embedded Power BI API and Power BI Mobile
  • Power BI Advance and Power BI Premium

Case Study:

This case study will cover the following concepts:

  • Creating a dashboard to depict actionable insights in sales data.
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Program Highlights

36 months DBA program
ACBSP Accreditation
Receive SSBM Geneva Alumni Status
24*7 Support

Career Services By Intellipaat

Career Services
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3 Guaranteed Interviews
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Exclusive access to Intellipaat Job portal
Mock Interview Preparation
1 on 1 Career Mentoring Sessions
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Career Oriented Sessions
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Resume & LinkedIn Profile Building
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Admission Details

The application process consists of three simple steps. An offer of admission will be made to selected candidates based on the feedback from the interview panel. The selected candidates will be notified over email and phone, and they can block their seats through the payment of the admission fee.

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Submit Application

Tell us a bit about yourself and why you want to join this program

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Application Review

An admission panel will shortlist candidates based on their application

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Admission

Selected candidates will be notified within 1–2 weeks

Program Fee

Total Admission Fee

₹ 6,99,048 (Inclusive of All)

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EMI Starts at

₹ 8,000

We partnered with financing companies to provide competitive finance options at 0% interest rate with no hidden costs

Financing Partners

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The credit facility is provided by a third-party credit facility provider and any arrangement with such third party is outside Intellipaat’s purview.

Upcoming Application Deadline 14th Dec 2024

Admissions are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.

Program Cohorts

Next Cohorts

Date Time Batch Type
Program Induction 14th Dec 2024 08:00 PM IST Weekend (Sat-Sun)
Regular Classes 14th Dec 2024 08:00 PM IST Weekend (Sat-Sun)
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Frequently Asked Questions

What are the prerequisites for enrolling in this DBA program from SSBM?

Learners must have completed a master’s degree to be eligible for this DBA program from SSBM. Candidates must be comfortable with English as all classes will be conducted in English only.

In the present professional landscape, possessing knowledge and skills in management and administration is essential for career progression. This certification, led by prominent experts from SSBM, aims to support you in launching a successful managerial career by leveraging their extensive industry-relevant experience.

Also, the course curriculum, along with videos, live sessions, and assignments, will help you gain in-depth knowledge of the modern business environment and processes.

The instructors for this DBA program are accomplished experts and leading academics from SSBM.

Yes, please speak to the course advisor for more details.

The DBA program from SSBM, Geneva has a total duration of 36 months.

SSBM Connect is a global platform provided by the university, fostering student interaction, engagement, and communication with fellow students, alumni, professors, and industry partners.

To register for the program, you can reach out to our learning consultants or contact us through the above-given details on this page.

Intellipaat actively supports all learners who successfully complete the training by offering placement assistance. Through our exclusive partnerships with over 80 leading multinational corporations globally, you have the opportunity to secure positions in renowned organizations like Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, Cisco, and other equally esteemed enterprises. Additionally, we provide assistance with job interviews and résumé preparation.

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What is included in this course?

  • Non-biased career guidance
  • Counselling based on your skills and preference
  • No repetitive calls, only as per convenience
  • Rigorous curriculum designed by industry experts
  • Complete this program while you work