Minors in Business Analytics
Business Analytics
Enquire now: 9480223900
why choose Business Analytics?
Learn comprehensive business analytics concepts, including data exploration, analysis, and application in specific business domains like marketing and accounting.
Earn certifications that validate your expertise in business analytics and its application across various business functions.
Gain hands-on experience through projects that apply machine learning and predictive analytics in business contexts.
Immerse in project-based learning through Capstone projects
Platform and tools to learn - R programming, SAS Visual Analytics, various business analytics software, and techniques for effective communication of analytics results.
Access to career resources - resume review, interview prep, career support on pathway completion
Accelerate your career with an Minors Degree
Online / 18 credits / Self-paced learning
Criteria
B.E / BTECH students in their 5th sem onwards who want to diversify their careers in the industry
Lectures from renowned subject matter experts from leading academia and industry across the world
Built in hands-on environment for practical implementation of the technologies covered with capstones.
Unlimited access to Coursera's catalog of 7,000+ world-class courses, hands-on projects, and job-ready
What will you learn from the program?
Total credits earned : 18 credits, 270 hours of learning
Gain hands-on experience through projects that apply machine learning and predictive analytics in business contexts.
Platform and tools to learn - R programming, SAS Visual Analytics, various business analytics softwares
Key Learnings: data exploration, analysis, and application in specific business domains like marketing and accounting.
Immerse in project-based learning through Capstone projects
Access to career resources - resume review, interview prep, career support on pathway completion
Curriculum
This comprehensive pathway provides a robust foundation in business analytics, equipping learners with the skills to apply data analysis across various business functions. It covers the essentials of business analytics, including introductory concepts and tools for exploratory data analysis. Specialized courses focus on applying analytics in marketing and accounting, utilizing machine learning algorithms in R for deeper insights. The pathway also includes training in business statistics, data preparation with SAS, and predictive modeling techniques. Learners will develop proficiency in analyzing, reporting, and communicating data-driven insights, culminating in a capstone project that synthesizes all learned skills in a practical, real-world business analytics scenario.
Business Analytics
Business Analytics Executive Overview
- Businesses run on data, and data offers little value without analytics. The ability to process data to make predictions about the behavior of individuals or markets, to diagnose systems or situations, or to prescribe actions for people or processes drives business today. Increasingly many businesses are striving to become “data-driven”, proactively relying more on cold hard information and sophisticated algorithms than upon the gut instinct or slow reactions of humans. This course will focus on understanding key analytics concepts and the breadth of analytic possibilities. Together, the class will explore dozens of real-world analytics problems and solutions across most major industries and business functions. The course will also touch on analytic technologies, architectures, and roles from business intelligence to data science, and from data warehouses to data lakes. And the course will wrap up with a discussion of analytics trends and futures.
Introduction to Business Analytics with R
- Nearly every aspect of business is affected by data analytics. For businesses to capitalize on data analytics, they need leaders who understand the business analytic workflow. This course addresses the human skills gap by providing a foundational set of data processing skills that can be applied to many business settings. In this course you will use a data analytic language, R, to efficiently prepare business data for analytic tools such as algorithms and visualizations. Cleaning, transforming, aggregating, and reshaping data is a critical, but inconspicuous step in the business analytic workflow. As you learn about the business analytic workflow you will also consider the interplay between business principles and data analytics. Specifically, you will explore how delegation, control, and feasibility influence the way in which data is processed. You will also be introduced to examples of business problems that can be solved with data automation and analytics, and methods for communicating data analytic results that do not require copying and pasting from one platform to another.
Introduction to Business Analytics: Communicating with Data
- This course introduces students to the science of business analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide businesses and managers with the foundation needed to apply data analytics to real-world challenges they confront daily in their professional lives. Students will learn to identify the ideal analytic tool for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data; and utilize data in decision making for their agencies, organizations or clients.
Tools for Exploratory Data Analysis in Business
- This course introduces several tools for processing business data to obtain actionable insight. The most important tool is the mind of the data analyst. Accordingly, in this course, you will explore what it means to have an analytic mindset. You will also practice identifying business problems that can be answered using data analytics. You will then be introduced to various software platforms to extract, transform, and load (ETL) data into tools for conducting exploratory data analytics (EDA). Specifically, you will practice using PowerBI, Alteryx, and RStudio to conduct the ETL and EDA processes.
Introduction to Data Analytics for Business
- This course will expose you to the data analytics practices executed in the business world. We will explore such key areas as the analytical process, how data is created, stored, accessed, and how the organization works with data and creates the environment in which analytics can flourish. What you learn in this course will give you a strong foundation in all the areas that support analytics and will help you to better position yourself for success within your organization. You’ll develop skills and a perspective that will make you more productive faster and allow you to become a valuable asset to your organization. This course also provides a basis for going deeper into advanced investigative and computational methods, which you have an opportunity to explore in future courses of the Data Analytics for Business specialization.
Machine Learning Algorithms with R in Business Analytics
- One of the most exciting aspects of business analytics is finding patterns in the data using machine learning algorithms. In this course you will gain a conceptual foundation for why machine learning algorithms are so important and how the resulting models from those algorithms are used to find actionable insight related to business problems. Some algorithms are used for predicting numeric outcomes, while others are used for predicting the classification of an outcome. Other algorithms are used for creating meaningful groups from a rich set of data. Upon completion of this course, you will be able to describe when each algorithm should be used. You will also be given the opportunity to use R and RStudio to run these algorithms and communicate the results using R notebooks.
Applying Data Analytics in Marketing
- This course introduces students to marketing analytics through a wide range of analytical tools and approaches. We will discuss causal analysis, survey analysis using regression, textual analysis (sentiment analysis), and network analysis. This course aims to provide the foundation required to make better marketing decisions by analyzing multiple types of data related to customer satisfaction.
Applying Data Analytics in Accounting
- This course explores business analytic applications in accounting. First, it presents a survey of technology topics in accounting, including process mining, blockchain and applications in audit, tax, and assurance. Next, the course explores visualization and basic analytics in audit and control testing using R and Alteryx. Next, the course examines the uses of text analysis in accounting and conducts text analysis using R and RStudio. Finally, the course examines robot process automation in general using UiPath and its applications in accounting.
Inferential and Predictive Statistics for Business
- This course offers an analytical framework to help you systematically address key business issues and manage the uncertainties that complicate business processes. It dives into statistical ideas relevant to managers, focusing on recognizing and describing variations and then modeling and making decisions considering these variations. While it introduces the science behind the teachings, the emphasis is on the application of methodologies using Excel and diverse data sets. The course facilitates understanding the meaning of obtained results and enables you to test beliefs about a population, compare differences between populations, and use a linear regression model for prediction. It is a part of Gies College of Business' suite of online programs, including the iMBA and iMSM.
Exploring and Producing Data for Business Decision Making
- The course offers an analytical framework to help you examine key business issues in a structured manner and equip you with methodologies to manage uncertainties within business processes. It imparts extensive knowledge of data summarization, frequency, normal distribution, statistical studies, sampling, and confidence intervals. Keeping application as its focus, the course employs data sets from various disciplines and Excel, facilitating a wide range of uses for the learned statistics. You'll learn not just the explanation of these concepts, but also the interpretation of the results drawn. By the end, you'll be proficient in summarizing large data sets, understanding sampling significance, applying normal distribution, making population inferences from sample data with confidence intervals, and using Excel for statistical analysis. The course is a part of the Gies College of Business' suite of online programs, including the iMBA and iMSM.
Getting Started with SAS Visual Analytics
- In this course, you learn more about SAS Visual Analytics and the SAS Viya platform, how to access and investigate data in SAS Visual Analytics, and how to prepare data for analysis using SAS Data Studio.
Data Analysis and Reporting in SAS Visual Analytics
- In this course, you learn how to use SAS Visual Analytics on SAS Viya to modify data for analysis, perform data discovery and analysis, and create interactive reports.
Predictive Modeling and Analytics
- This course will introduce you to some of the most widely used predictive modeling techniques and their core principles. By taking this course, you will form a solid foundation of predictive analytics, which refers to tools and techniques for building statistical or machine learning models to make predictions based on data. You will learn how to carry out exploratory data analysis to gain insights and prepare data for predictive modeling, an essential skill valued in the business. You’ll also learn how to summarize and visualize datasets using plots so that you can present your results in a compelling and meaningful way. We will use a practical predictive modeling software, XLMiner, which is a popular Excel plug-in.
Business Analytics for Decision Making
- In this course you will learn how to create models for decision making. We will start with cluster analysis, a technique for data reduction that is very useful in market segmentation. You will then learn the basics of Monte Carlo simulation that will help you model the uncertainty that is prevalent in many business decisions. A key element of decision making is to identify the best course of action. Since businesses problems often have too many alternative solutions, you will learn how optimization can help you identify the best option. What is really exciting about this course is that you won’t need to know a computer language or advanced statistics to learn about these predictive and prescriptive analytic models. The Analytic Solver Platform and basic knowledge of Excel is all you’ll need. Learners participating in assignments will be able to get free access to the Analytic Solver Platform.
Communicating Business Analytics Results
- The analytical process does not end with models than can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations. This depends on the ability to communicate results to those who make decisions. Presenting findings to decision makers who are not familiar with the language of analytics presents a challenge. In this course you will learn how to communicate analytics results to stakeholders who do not understand the details of analytics but want evidence of analysis and data. You will be able to choose the right vehicles to present quantitative information, including those based on principles of data visualization. You will also learn how to develop and deliver data-analytics stories that provide context, insight, and interpretation.
Advanced Business Analytics Capstone
- The analytics process is a collection of interrelated activities that lead to better decisions and to a higher business performance. The capstone of this specialization is designed with the goal of allowing you to experience this process. The capstone project will take you from data to analysis and models, and ultimately to presentation of insights. In this capstone project, you will analyze the data on financial loans to help with the investment decisions of an investment company. You will go through all typical steps of a data analytics project, including data understanding and cleanup, data analysis, and presentation of analytical results. In the last week, you are expected to present your analytics results to your clients. Since you will obtain many results in your project, it is important for you to judiciously choose what to include in your presentation. You are also expected to follow the principles we covered in the courses in preparing your presentation.
Minor Degree from VTU University
|
||
Program Fee
Paid |
|
|
Application Process
Register to Honour/Minor degree by filling online application and by paying registration fee.
Get your online application approved.
Start enrolling to Honour/Minor degree program.
Admissons are closed once the requisite number of participants enroll for the upcoming cohort. Apply early to secure your seat.
Deadline:30-May-2024
Frequently Asked Questions
What Is a Minor Degree?
The Minors degree programme is designed to empower graduate engineering students with industry and career readiness through skill-based learning and application tools.
How will this programme help students in building their proficiency?
This programme is envisaged to help build a strong foundation across various streams through digital lectures, industry interviews, formative and summative assessments, capstone projects, and
How is this programme different from other industry programmes?
This programme is designed by globally renowned industry and university content partners to combine academic concepts with emerging industry skills and technologies for the students entering
What will students get once they enroll and complete this Minors pathway?
Once you enroll into the Minors pathway, you will get unlimited access to Coursera for Campus catalog of 10,000+ world-class courses, hands-on projects, and job-ready certificate programs. Yo
Contact
Still have queries?
Contact Us
Please fill in the form and a Program Advisor will reach out to you. You can also reach out to us at onlineprograms@vtu.ac.in or 9480223900