The massive advances made in computational technologies in recent decades has radically changed the way businesses operate. Data is being increasingly referred to as the new “oil”. Businesses can get access or have access to vast amounts of information about their operations, customers, and products. Interpreting this information to get actionable insights and turn them into productive and profitable business solutions requires trained professionals who are adept at utilizing this data. To meet the burgeoning demand for experts who are skilled in the use of technology, data analysis, and business processes for strategic decision making, the interdisciplinary area of Business Analytics has come into existence.
The Business Analytics specialisation offers courses in the disciplines of Business and Data Analytics, Advanced Operations Research, and Enterprise Data Management, besides introducing the student to Big Data and AI and ML. Relevant skill sets are imparted to the students through an appropriate blend of academic and experiential learning. Also, a solid foundation is laid in the application of statistical methods, techniques, and tools to large datasets. The specialisation provides students with the background needed to apply statistical methods and techniques through use of decision support systems (DSS), expert systems (ES), business intelligence (BI) reporting tools, and business analytics (BA) data mining tools. The specialisation is built upon a strong and holistic understanding of business areas such as finance, marketing, research methods, accounting, ethics, and entrepreneurship. Graduates will be prepared for business analytics and reporting positions in any industry and also to pursue higher education in data science or allied areas.
SPECIALISATION AIMS:
The Business Analytics Major and Minor intends to:
- To be able to mine and extract data from disparate set of sources
- To be able to investigate business transactions and data, especially in the areas of supply chain, marketing, human resources and finance, to establish new relationships and patterns
- To build a competency in data analysis, especially the correlation between different variables
- Be able to apply knowledge to business problems and help managers make data-driven decisions
- Be able to identify, formulate, analyse and solve business problems using programming techniques such as Linear and Goal programming
- To build prescriptive and predictive business models
- To be able to confidently use commercial/open-source tools, as well as write custom programs using platforms like Python, as part of problem solution
- To be able to explore areas of application of futuristic techniques such as Artificial Intelligence, Machine Learning, and Natural Language Processing
- To be able to build visual models to enhance interactions during problem-solution discussions, and improve quality of solutions
MAJOR OUTCOMES: After successful completion of the Major, the student will be able to:
- Demonstrate basic knowledge in accounting, economics, finance, management, Entrepreneurship, and marketing in application of concepts and theories.
- Integrate the concepts of the core areas of business and apply it in various contexts.
- Understand the importance of the ethics in business activities.
- Demonstrate basic knowledge in accounting, economics, finance, management, Entrepreneurship, and marketing in application of concepts and theories.
- Understand the basic concepts of data and its different forms (numbers, text, images, audio etc.)
- Apply methods of extracting relevant data from different sources
- Identify business problems using patterns of data
- Develop an ability to formulate business problems mathematically
- Develop an ability to interpret solutions
- Demonstrate the technical skills required for solving business problems, including using relevant tools/platforms and commercial programming languages
- Identify and apply knowledge acquired in the classroom on different domains such as supply chain, finance, marketing and human resources
- Articulate research ideas from futuristic topics such as artificial intelligence, machine learning etc.,
- Identify areas of applications of these futuristic topics
MINOR OUTCOMES: After successful completion of the Minor, the student will be able to:
- Develop a sound understanding of the basic concepts of data and its different forms (numbers, text, images, audio etc.)
- Develop a deep understanding of methods of extracting relevant data from different sources
- Develop the ability to identify business problems using patterns of data
- Develop an ability to formulate business problems mathematically
- Develop an ability to interpret solutions
- Demonstrate the technical skills required for solving business problems, including using relevant tools/platforms and commercial programming languages
- Identify and apply knowledge acquired in the classroom on different domains such as supply chain, finance, marketing and human resources
COURSES (CORE AND ELECTIVE) **
39 MAJOR COURSES
| Introduction to Operations Research | Financial Management | Machine Learning - 2: Introduction to Deep Learning |
| Introduction to Finance and Accounting | Introduction to Big Data & Cloud Computing | Data Analytics Services |
| Consumer & Markets | Data Mining for Business Intelligence | E-Commerce |
| Introduction to People Management | Design Thinking for Managers | Enterprise Data Management |
| Introduction to Entrepreneurship & Family Business | Enterprise Risk Management | Special Topics in Business Analytics |
| Introduction to Spreadsheet Modeling | Business Ethics and Corporate Governance | Web and Social Media Analytics |
| Introduction to Quantitative Methods | Machine Learning – 1: Introduction | Advanced Analytical Modeling |
| Introduction to Programming | Statistical Data Analysis and Visualisation | Supply Chain Analytics |
| Managerial Economics | Advanced Operations Research | Special Topics in Business Analytics |
| Accounting for Managers | Negotiations | Advanced Optimization and Simulation |
| Marketing Management | Special Topics in Business Analytics | Gamification |
| Organisational Behaviour | Business Innovation, Entrepreneurship and Strategy | Special Topics in Business Analytics |
| Research Methods for Managers | Business Applications of Analytics | Graduation Project |
Introduction to Operations Research
The course exposes students to fundamental optimization procedures and techniques to attain skills at structuring business problems and modelling them as a mathematical program, Microsoft Excel to solve such models, interpret solutions and use the solutions to answer the business problem. The focus of this course will be on applications of quantitative methods in modelling business situations.
Introduction to Finance and Accounting
The course is aimed at baptising the students to the vocabularies of accounting theories and practices. Begining with the accounting concepts, introducing the basic tenets in maintaining the books of accounts, the course finally culminates into the preparation of the financial statements like Income statement, Balance Sheet as well as the Cash flow statement. It also covers the Bank reconcilation statement and Bills of Exchange
Consumer & Markets
This course provides a conceptual framework to the students to understand the various dimensions of marketing as a disciline. It focuses on exploring various aspects of marketing, markets, consumers, their shopping behaviour and motivations. It gives broad understanding of the exciting world of Shop, Shopping and Shopper.
Introduction to People Management
The course familiarizes students with the history and functions of management. It gives an overview of the various functions of human resource management and the concepts of organizational behaviour. It prepares students to go deeper into the area of people management equipping them with the basic background knowledge.
Introduction to Entrepreneurship & Family Business
This course introduces students to entrepreneurship and family businesses. It provides an overview on how they come into being, their perspective on the ecosystem, their mindset and how they manage their enterprises.
Introduction to Spreadsheet Modeling
This course deals with the use of the Spreadsheet to solve managerial problems. It merely highlights the use of Microsoft Excel as an aid in formulating business problems and invoking appropriate functions to resolve them.
Introduction to Quantitative Methods
This course is designed to give undergraduate students an introduction to decison making. The use of quantitative techniques is increasingly being adopted in all areas of human endeavour. The need to collect, analyze and interpret mathematical output is increasingly being appreciated for arriving at conclusions or in strategic decision making. This course will deal with fundamental concepts required to model, analyse and solve quantitative problems arising in any discipline. A student undertaking this course can have little to no formal introduction to mathematics and statistics at the higher secondary level.
Introduction to Programming
This is a first course in problem solving through computer programming; no previous programming experience is assumed. Programming is introduced as an executable form of mathematics. The course brings a clean separation between the problem, the model and the machine and the 2 basic binding times: program development and program execution
Managerial Economics
This course provides a foundation of economic theories and models for use in managerial decision-making. The course provides students with an overview of theories of demand, supply, production and competition and equips them with the tools and techniques to make effective economic decisions under different business environments.
Accounting for Managers
Financial accounting provides the means of recording and reporting financial information in a business. Accounting plays a vital role as an information system for monitoring, problem solving and decision-making. This course provides the fundamentals of Financial Accounting and goes on to demonstrate how accounting fits into the overall business environment of an organization. In addition to this, Management Accounting systems, which have a strong internal focus can be effective tools in providing information that is useful in decision making at all levels in the organization. Management accountants play a strategic role in developing and providing both financial and non-financial information that is critical to the success of an organization.
Marketing Management
This course provides a conceptual framework to the students to understand the function of marketing in an organization. The course helps students to apply the marketing concepts and theories to solve case studies and projects. The course makes them vigilant of the marketing happenings in the real world and therefore importance of creating effective marketing strategies.
Organisational Behaviour
This course is an introduction to organizational behaviour for undergraduates. It discusses behaviour in organizations at individual, group & organizational levels and provides an understanding of the underlying aspects that drive behavior. It provides insights into the different theories and their application in the organizational context. It also enables students to understand theutilisation of different tools and practices in directing individual actions towards organizational objectives.
Research Methods for Managers
The objective of the course is to enable students to understand the role and importance of research in improving managerial decisions when faced with uncertainty. Research methods are applied in all functional areas of business viz. operation management, accounting, finance and marketing. The issue facing managers is not a shortage of information but how to use the available information to make better decisions. Learning this course helps students recognise that data are inherently variable and that the identification measurement, control, and reduction of variation provide opportunities for quality improvement.
Financial Management
This course in Financial Management provides a detailed understanding of the Finance Function and its interrelationship with other areas of Business. It seeks to develop the foundation for financial management concepts. It primarily helps the student to understand how businesses make investment, Financing, working capital management and dividend decisions and what are the key factors that influence these decisions.
Introduction to Big Data & Cloud Computing
Big data and cloud computing technologies have gained lot of relevance for aspiring managers in the context of data-driven decision making process. These technologies are also very useful for IT-driven business transformations for organizations. Basic knowledge about Hadoop big data framework, Google cloud platform (GCP), Amazon web services (AWS) etc. are essential for managers now-a-days for handling storage and analysis of huge amount of heterogeneous data collected from omni-channel sources/touchpoints. This course will help the participants to acquire basic, hands-on knowledge on these technology domains and find out how these can be adopted and applied for business transformations. The approach will involve case studies, hands-on learning, and real-world problem-solving exercises to assist students acquire the skills necessary for the profession.
Data Mining for Business Intelligence
Data mining (DM) is the technique of extracting useful pattern or knowledge from large amount of data which is generated by business organizations now-a-days. It can be used to discover hidden relationships of variables or for prediction of future events based on historical data. Hence, organizations are adopting data mining technologies in order to understand/predict business outcomes more accurately and build their business intelligence (BI) capabilities. This course intends to build basic understanding of core data mining techniques which are very common these days for data-driven decision making. Case studies, hands-on learning, and real-world problem-solving exercises will be included in the pedagogy to assist students obtain the skills needed for employment.
Design Thinking for Managers
Design Thinking (DT) is a powerful tool to tackle the unstructured & the unknown. DT is a ‘human centered’ approach to problem solving which emerged at Stanford in the 1960’s primarily as a systematic, immersive approach to product design. In recent years, it was found that these approaches can be extended to a wide category of ill-structured, real world problems, both in emerging and developed markets alike. DT is getting increasingly popular not only across top corporates, but also in rural, semi-urban and underserved sections of society. Given the diversity of challenges that we face today, it therefore becomes necessary to have thinkers and doers who can focus on addressing such challenges. DT helps in building those capabilities.
Enterprise Risk Management
Risk management has traditionally been associated with financial institutions, banking, and insurance businesses. In today's business world, whether large or small, risk management is a crucial success factor. Enterprise risk management encompasses risk-based decision making in its essence. The increased likelihood of a startup's survival and the development of a resource-efficient growth model can be ascribed to risk-based decision making. This course's objectives are to increase participants' risk awareness and instil a culture of risk management. In this comprehensive course, students will gain an in-depth understanding of enterprise risk management (ERM).
Business Ethics and Corporate Governance
The course aims to develop in the student a clear perspective on the role and responsibilities of business in society. It helps the student understand the role of ethics in business. It also dwells on corporate governance frameworks and their relevance to contemporary business environment.
Machine Learning -1: Introduction
This course provides a basic level analysis of machine learning algorithms. This course will introduce supervised learning algorithms such as decision tree learning, support vector machines, and neural networks, unsupervised learning algorithms including k-means and herarchial clustering. Evaluation of learning algorithms and dimensionality reduction techniques will also be discussed. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Statistical Data Analysis and Visualisation
This course provides advanced techniques in statistics. Business applications generate large amounts of unstructured data. This data needs visulaization techniques for ease of interpretation and handling. Further, rigorous statistical analysis is needed to convert it into information , knowledge and models readily applicable to real life applications. This course aims to give students a good understanding of the undelying concepts of statistical data analysis along with data visualization techniques. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Advanced Operations Research
The course exposes students to advanced optimization techniques to model and solve complex business problems. Microsoft Excel will continue to be used to solve these problems, and the student is expected to have completed the prerequisite courses. The focus of this course will be on applications of quantitative methods in modelling business situations.
Negotiations
Negotiation is a commonly used and vital tool to make decisions in the organizational context. Based on the position and role of an employee, he or she has to engage in some kind of negotiation at one point of time or the other. Negotiation is driven by assumptions, perceptions and understanding about human behavior. This course would be designed to familiarize future professionals and managers about when to engage in negotiation, how to understand the negotiation partner, what negotiation technique to use at what point in time and how to develop negotiation skills.
Business Innovation, Entrepreneurship and Strategy
In a rapidly changing business environment, Innovation has been recognised as one of the key drivers of competitive advantage. This course is an introduction to the concept of innovaton for corporate managers and entrepreneurs.
Business Applications of Analytics
The course will expose the students to business applications of data science & data analytics. Specifically, a student will be able to apply the concepts learnt in lower level classes to an existing business problem. The focus will be on supply chain management domain, but a few general management topics, including finance and marketing will also be taught. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Machine Learning - 2: Introduction to Deep Learning
This course covers introductory aspects of deep learning techniques. Some of the tools we learn are deep learning techniques, including Convolutional networks, RNNs, LSTM , deep auto encoders. Applications of Deep learning to text mining , image and Video Processing will be covered . Applications of deep learning to Business and Social media analytics will also be introduced The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Data Analytics Services
Analytics as a Service brings the advantages of data analysis within reach of more companies. In addition to reducing the burden on in-house IT staff, AaaS reduces risk.AaaS is also an option if a business has on-premises resources for analytics, but needs expanded, temporary capabilities to analyze additional data or to research a one-time event or project. Data analysis services allow businesses to get their data collected, processed and presented to them in the form of actionable insights while avoiding investments in the development and administration of an analytics solution. With subscription-based data analysis, or Analytics as a Service, businesses carry out data analysis on a fully customized analytics platforms. The course focuses on analysing the specific business needs and give recommendations on designing, developing, implementing or upgrading your analytics solution. Case studies, hands-on learning, and real-world problem-solving exercises will be included in the pedagogy to assist students obtain the skills needed for employment.
E-Commerce
Today ecommerce happens to be an integral part of our daily life and one of the most effective channels for marketers. Especially with COVID pandemic, this model of buying and selling has proliferated extremely fast across the world. Today every budding manager needs to understand various aspects of ecommerce. This course will cover several fundamental concepts related to ecommerce needed for business students. The approach will involve case studies, hands-on learning, and real-world problem-solving exercises to assist students acquire the skills necessary for the profession.
Enterprise Data Management
Enterprise data management (EDM) is the process of inventorying and governing your business’s data and getting your organization onboard with the process. In other words, EDM is as much about managing people as it is about managing data. Data management means making sure your people have the accurate and timely data they need, and that they follow your standards for storing quality data in a standardized, secure, and governed place. In this course, the students learn the basic and detailed frameworks and concepts as well as the case scenarios about implementations of enterprise data management. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Web and Social Media Analytics
Web and Social Media have become an integral part of our daily life today and marketers are leveraging its power for their business. This course is intended as a primer for various analytics techniques involving web and social media which are relevant for business professionals. Case studies, hands-on learning, and real-world problem-solving exercises will be included in the pedagogy to assist students obtain the skills needed for employment.
Advanced Analytical Modeling
The Advanced Analytical Modeling course helps students understand advanced topics on analytical models. The course covers advanced forecasting, advanced regression, structural equation models, advanced bayesian model and markov model.
Supply Chain Analytics
The Introduction into Supply Chain Analytics course will help you hone your skills in supply chain analytics to either help you get to the next level in your current role or transition into a role in Supply Chain Analytics. The course is split into 4 concepts of supply chain, logistics, operations, planning, and sourcing. The concepts we will go over will cover the entire supply chain from sourcing raw materials to products ending up at your front door. We go into depth on how these processes work, how data can increase key KPIs in the space so you can add value to the company. We will talk about how to gather data ,where to gather data, and what are the common ways data is gathered. There are a lot of key places that you would be surprised individuals can find data to add value. then go into the multiple ways data can be analyzed using SQL , EXCEL and Python.These skills will help you move to the next level in your career so you can make the big bucks and make decisions in the organization.
Advanced Optimization and Simulation
Application of optimization & simulation is found to be very effective for solving many business decision problems. This course will help the participants to understand these two very important topics of data analytics. It will cover basic concepts of optimization theory, how to formulate optimization problems for managerial decision making, different types of optimization problems and their solution approaches, different types of simulation and their applications. The students will be exposed to some popular tools and techniques in this domain with hands-on problem solving. The approach will involve case studies, hands-on learning, and real-world problem-solving exercises to assist students acquire the skills necessary for the profession.
Gamification
Learn how fashion and luxury companies work and understand their brands, products, retail, and communication strategies. Travel through business models, international development, and product categories with industry influent experts.
Adopting a case-study approach, the course presents strategic brand management in luxury and fashion companies as a balancing act: tradition vs. innovation, expertise vs. experimentation, casual vs. stylish; in order to increase the brand value by nurturing the brand heritage and at the same time staying fresh, relevant, and contemporary in the global marketplace.
Topics such as the impact of new retail channels, new media channels, and new business declinations for the brand and emerging markets will be discussed in the course
30 MINOR COURSES
| Introduction to Operations Research | Introduction to Big Data & Cloud Computing | E-Commerce |
| Introduction to Finance and Accounting | Data Mining for Business Intelligence | Enterprise Data Management |
| Consumer & Markets | Enterprise Risk Management | Special Topics in Business Analytics |
| Introduction to People Management | Machine Learning – 1: Introduction | Web and Social Media Analytics |
| Introduction to Entrepreneurship & Family Business | Statistical Data Analysis and Visualisation | Advanced Analytical Modeling |
| Introduction to Spreadsheet Modeling | Advanced Operations Research | Supply Chain Analytics |
| Introduction to Quantitative Methods | Special Topics in Business Analytics | Special Topics in Business Analytics |
| Introduction to Programming | Business Applications of Analytics | Advanced Optimization and Simulation |
| Managerial Economics | Machine Learning - 2: Introduction to Deep Learning | Gamification |
| Marketing Management | Data Analytics Services | Special Topics in Business Analytics |
Introduction to Operations Research
The course exposes students to fundamental optimization procedures and techniques to attain skills at structuring business problems and modelling them as a mathematical program, Microsoft Excel to solve such models, interpret solutions and use the solutions to answer the business problem. The focus of this course will be on applications of quantitative methods in modelling business situations.
Introduction to Finance and Accounting
The course is aimed at baptising the students to the vocabularies of accounting theories and practices. Begining with the accounting concepts, introducing the basic tenets in maintaining the books of accounts, the course finally culminates into the preparation of the financial statements like Income statement, Balance Sheet as well as the Cash flow statement. It also covers the Bank reconcilation statement and Bills of Exchange
Consumer & Markets
This course provides a conceptual framework to the students to understand the various dimensions of marketing as a disciline. It focuses on exploring various aspects of marketing, markets, consumers, their shopping behaviour and motivations. It gives broad understanding of the exciting world of Shop, Shopping and Shopper.
Introduction to People Management
The course familiarizes students with the history and functions of management. It gives an overview of the various functions of human resource management and the concepts of organizational behaviour. It prepares students to go deeper into the area of people management equipping them with the basic background knowledge.
Introduction to Entrepreneurship & Family Business
This course introduces students to entrepreneurship and family businesses. It provides an overview on how they come into being, their perspective on the ecosystem, their mindset and how they manage their enterprises.
Introduction to Spreadsheet Modeling
This course deals with the use of the Spreadsheet to solve managerial problems. It merely highlights the use of Microsoft Excel as an aid in formulating business problems and invoking appropriate functions to resolve them.
Introduction to Quantitative Methods
This course is designed to give undergraduate students an introduction to decison making. The use of quantitative techniques is increasingly being adopted in all areas of human endeavour. The need to collect, analyze and interpret mathematical output is increasingly being appreciated for arriving at conclusions or in strategic decision making. This course will deal with fundamental concepts required to model, analyse and solve quantitative problems arising in any discipline. A student undertaking this course can have little to no formal introduction to mathematics and statistics at the higher secondary level.
Introduction to Programming
This is a first course in problem solving through computer programming; no previous programming experience is assumed. Programming is introduced as an executable form of mathematics. The course brings a clean separation between the problem, the model and the machine and the 2 basic binding times: program development and program execution
Managerial Economics
This course provides a foundation of economic theories and models for use in managerial decision-making. The course provides students with an overview of theories of demand, supply, production and competition and equips them with the tools and techniques to make effective economic decisions under different business environments.
Marketing Management
This course provides a conceptual framework to the students to understand the function of marketing in an organization. The course helps students to apply the marketing concepts and theories to solve case studies and projects. The course makes them vigilant of the marketing happenings in the real world and therefore importance of creating effective marketing strategies.
Introduction to Big Data & Cloud Computing
Big data and cloud computing technologies have gained lot of relevance for aspiring managers in the context of data-driven decision making process. These technologies are also very useful for IT-driven business transformations for organizations. Basic knowledge about Hadoop big data framework, Google cloud platform (GCP), Amazon web services (AWS) etc. are essential for managers now-a-days for handling storage and analysis of huge amount of heterogeneous data collected from omni-channel sources/touchpoints. This course will help the participants to acquire basic, hands-on knowledge on these technology domains and find out how these can be adopted and applied for business transformations. The approach will involve case studies, hands-on learning, and real-world problem-solving exercises to assist students acquire the skills necessary for the profession.
Data Mining for Business Intelligence
Data mining (DM) is the technique of extracting useful pattern or knowledge from large amount of data which is generated by business organizations now-a-days. It can be used to discover hidden relationships of variables or for prediction of future events based on historical data. Hence, organizations are adopting data mining technologies in order to understand/predict business outcomes more accurately and build their business intelligence (BI) capabilities. This course intends to build basic understanding of core data mining techniques which are very common these days for data-driven decision making. Case studies, hands-on learning, and real-world problem-solving exercises will be included in the pedagogy to assist students obtain the skills needed for employment.
Enterprise Risk Management
Risk management has traditionally been associated with financial institutions, banking, and insurance businesses. In today's business world, whether large or small, risk management is a crucial success factor. Enterprise risk management encompasses risk-based decision making in its essence. The increased likelihood of a startup's survival and the development of a resource-efficient growth model can be ascribed to risk-based decision making. This course's objectives are to increase participants' risk awareness and instil a culture of risk management. In this comprehensive course, students will gain an in-depth understanding of enterprise risk management (ERM).
Machine Learning - 1: Introduction
This course provides a basic level analysis of machine learning algorithms. This course will introduce supervised learning algorithms such as decision tree learning, support vector machines, and neural networks, unsupervised learning algorithms including k-means and herarchial clustering. Evaluation of learning algorithms and dimensionality reduction techniques will also be discussed. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Statistical Data Analysis and Visualisation
This course provides advanced techniques in statistics. Business applications generate large amounts of unstructured data. This data needs visulaization techniques for ease of interpretation and handling. Further, rigorous statistical analysis is needed to convert it into information , knowledge and models readily applicable to real life applications. This course aims to give students a good understanding of the undelying concepts of statistical data analysis along with data visualization techniques. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Advanced Operations Research
The course exposes students to advanced optimization techniques to model and solve complex business problems. Microsoft Excel will continue to be used to solve these problems, and the student is expected to have completed the prerequisite courses. The focus of this course will be on applications of quantitative methods in modelling business situations.
Business Applications of Analytics
The course will expose the students to business applications of data science & data analytics. Specifically, a student will be able to apply the concepts learnt in lower level classes to an existing business problem. The focus will be on supply chain management domain, but a few general management topics, including finance and marketing will also be taught. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Machine Learning - 2: Introduction to Deep Learning
This course covers introductory aspects of deep learning techniques. Some of the tools we learn are deep learning techniques, including Convolutional networks, RNNs, LSTM , deep auto encoders. Applications of Deep learning to text mining , image and Video Processing will be covered . Applications of deep learning to Business and Social media analytics will also be introduced The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Data Analytics Services
Analytics as a Service brings the advantages of data analysis within reach of more companies. In addition to reducing the burden on in-house IT staff, AaaS reduces risk.AaaS is also an option if a business has on-premises resources for analytics, but needs expanded, temporary capabilities to analyze additional data or to research a one-time event or project. Data analysis services allow businesses to get their data collected, processed and presented to them in the form of actionable insights while avoiding investments in the development and administration of an analytics solution. With subscription-based data analysis, or Analytics as a Service, businesses carry out data analysis on a fully customized analytics platforms. The course focuses on analysing the specific business needs and give recommendations on designing, developing, implementing or upgrading your analytics solution. Case studies, hands-on learning, and real-world problem-solving exercises will be included in the pedagogy to assist students obtain the skills needed for employment.
E-Commerce
Today ecommerce happens to be an integral part of our daily life and one of the most effective channels for marketers. Especially with COVID pandemic, this model of buying and selling has proliferated extremely fast across the world. Today every budding manager needs to understand various aspects of ecommerce. This course will cover several fundamental concepts related to ecommerce needed for business students. The approach will involve case studies, hands-on learning, and real-world problem-solving exercises to assist students acquire the skills necessary for the profession.
Enterprise Data Management
Enterprise data management (EDM) is the process of inventorying and governing your business’s data and getting your organization onboard with the process. In other words, EDM is as much about managing people as it is about managing data. Data management means making sure your people have the accurate and timely data they need, and that they follow your standards for storing quality data in a standardized, secure, and governed place. In this course, the students learn the basic and detailed frameworks and concepts as well as the case scenarios about implementations of enterprise data management. The pedagogy will include case-studies, hands-on learning, and real-world problem-solving activities that helps in equipping the student with the skills required in the workforce.
Web and Social Media Analytics
Web and Social Media have become an integral part of our daily life today and marketers are leveraging its power for their business. This course is intended as a primer for various analytics techniques involving web and social media which are relevant for business professionals. Case studies, hands-on learning, and real-world problem-solving exercises will be included in the pedagogy to assist students obtain the skills needed for employment.
Advanced Analytical Modeling
The Advanced Analytical Modeling course helps students understand advanced topics on analytical models. The course covers advanced forecasting, advanced regression, structural equation models, advanced bayesian model and markov model
Supply Chain Analytics
The Introduction into Supply Chain Analytics course will help you hone your skills in supply chain analytics to either help you get to the next level in your current role or transition into a role in Supply Chain Analytics. The course is split into 4 concepts of supply chain, logistics, operations, planning, and sourcing. The concepts we will go over will cover the entire supply chain from sourcing raw materials to products ending up at your front door. We go into depth on how these processes work, how data can increase key KPIs in the space so you can add value to the company. We will talk about how to gather data ,where to gather data, and what are the common ways data is gathered. There are a lot of key places that you would be surprised individuals can find data to add value. then go into the multiple ways data can be analyzed using SQL , EXCEL and Python.These skills will help you move to the next level in your career so you can make the big bucks and make decisions in the organization.
Advanced Optimization and Simulation
Application of optimization & simulation is found to be very effective for solving many business decision problems. This course will help the participants to understand these two very important topics of data analytics. It will cover basic concepts of optimization theory, how to formulate optimization problems for managerial decision making, different types of optimization problems and their solution approaches, different types of simulation and their applications. The students will be exposed to some popular tools and techniques in this domain with hands-on problem solving. The approach will involve case studies, hands-on learning, and real-world problem-solving exercises to assist students acquire the skills necessary for the profession.
Gamification
Learn how fashion and luxury companies work and understand their brands, products, retail, and communication strategies. Travel through business models, international development, and product categories with industry influent experts.
Adopting a case-study approach, the course presents strategic brand management in luxury and fashion companies as a balancing act: tradition vs. innovation, expertise vs. experimentation, casual vs. stylish; in order to increase the brand value by nurturing the brand heritage and at the same time staying fresh, relevant, and contemporary in the global marketplace.
Topics such as the impact of new retail channels, new media channels, and new business declinations for the brand and emerging markets will be discussed in the course