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Marvin A. Pomerantz Business Library

Business Analytics & Information Systems Toolkit

BAIS Courses

List of skills and activities in courses taken by all BAIS students.


 

BAIS:3020 - Computational Thinking:

Coding or programming is considered a must-have job skill for business and other professionals. However, it is much more than that. Coding is a way of thinking about problems and solving them with the use of computers. Python is one of the most popular languages for writing general-purpose programs. In this class, we learn to solve problems by writing Python programs.

 

Students will learn:

  • Anaconda programming environment
  • Python programming language, including:
    • Variables and functions
    • Loops and logic
    • String manipulation
    • Structured types
    • Dictionaries
    • Exceptions
    • Object oriented programming
    • Plotting
    • Libraries

 

Students will be able to:

  • Write robust Python applications that utilize multiple functions
  • Scrape web pages for data
  • Perform text analytics on data
  • Produce visualizations
  • Process images

 


 

BAIS:3200 - Database Management:

Due to exponentially growing computation power and storage capacity, as well as the as increasingly digital nature of business operations, modern organizations collect and store a wealth of data about their interactions with various stakeholders, including customers, employees, shareholders, government, and suppliers. It is critical to manage data effectively so that it supports business strategy and provides competitive advantage. In this class, we learn the core concepts needed to design and utilize database management systems (DBMS) and Structured Query Language (SQL).

 

Students will learn:

  • SQL language & syntax
  • Modeling databases using ER and EER diagrams
  • Designing a relational schema and normalization
  • Constructing database tables
    • Specifying field data types
    • Primary and foreign key relationships
  • Designing and writing SQL queries to extract data

 

Students will be able to:

  • Draw Entity Relationship diagrams to conceptually model databases and business rules
  • Create logical models of databases including normalization to 3rd normal form
  • Design and create tables and fields in a relational database
  • Manipulate and load data into a database using database management software
  • Perform queries on relational data using:
    • Joins
    • Sub-queries
    • Compound queries
    • Conditional logic

 


 

BAIS:3050 - BAIS Professional Preparation:

This course is an introduction to the many career avenues available to a BAIS major and how to successfully search for for and landing one of those careers. Along the way students will be guided as they build their personal brand and prepare for their future internships and careers.

 

Students will learn:

  • To write a technical resume
  • To navigate technical interviews
  • To navigate case interviews
  • different careers in BAIS
  • Utilizing Career Service's tools and professionals
  • Life in BAIS from an industry panel
  • Negotiating the offer!

 

Students will be able to:

  • Better understand career opportunities within the business analytics and information systems field
  • Learn about the course curriculum - including the capstone course and additional educational options
  • Identify how to best manage your career search - from creating a technical resume to managing applications to networking and more
  • Learn about the industry from leading experts
  • Understand various types of interviews (behavioral, technical, case) and have the opportunity to practice your interview skills
  • Gain an understanding of the importance of hard and soft skills required in the workplace
  • Learn how to translate your knowledge and skills to match job posting requirements

 


 

BAIS:3250 - Data Wrangling:

In 2012, data scientist was named the “the sexiest job of the 21st century” by Harvard Business Review. But, recent surveys of professionals and researchers in the field suggest that the reality is much less glamorous. On average, data scientists spend 80% of their time on the task of data wrangling, including obtaining, cleaning, transforming, and formatting data. In addition to being the most time-consuming, these tasks are the most critical for any analytics project, as they impact the outcome of all further experiments/analysis.

 

Students will learn:

  • R and R Studio
  • File Handing
  • Data Cleaning and Transformation
  • Data Collection and Integration
  • Descriptive Analytics and Visualization
  • Web Scraping
  • APIs

 

Students will be able to:

  • Build foundational programming skills, including variable assignment, data types, data structures, functions, indexing, and subsetting
  • Read and write plain text, delimited, and nested file formats (XML, JSON), including file encoding
  • Learn methods to identify and correct common types of errors, handle missing values, and create derived features
  • Access data via APIs, Web scraping, and external database connections and perform vertical and horizontal data integration
  • Use statistical methods (summary tables, hypothesis testing, regression) and visualizations to describe data
  • Utilize techniques for time-series analysis and text analytics, including regular expressions and term frequency representation

 


 

BAIS:3500 - Data Mining:

In this course you will learn the basic concepts and techniques of data mining and knowledge discovery as applied to business problems. The focus will be on using recent data mining software to solve practical problems. Students will learn the process of turning raw data into intelligent decisions, and the algorithms that are commonly used to build predictive models and find relevant patterns in data.

 

Students will learn:

  • R
  • Knowledge discovery process
    • data mining problem formulation
    • data cleaning & transformation
    • data visualization
    • model evaluation & comparison
    • dimensionality reduction
  • Predictive modeling techniques
    • regression
    • decision trees
    • support vector machines
    • k-nearest neighbors
    • artificial neural networks
  • Clustering
    • hierarchical clustering
    • k-means
  • Ensemble Methods
    • Random forest
    • Adaboost
    • Gradient boost

 

Students will be able to:

  • Understand the business prediction and model selection process
  • Discuss their theoretical appreciation for a variety of data mining methods
  • Apply practical knowledge of the uses and limitations of data-mining
  • Make and assess predictions using a software package
  • Compare and select the best model using a variety of metrics

 


 

BAIS:4150 - Business Analytics and Information Systems Capstone:

The purpose of this course is to allow students to gain exposure to practical, real-world applications of the concepts they have encountered throughout the BAIS curriculum. Students will gain relevant analytics project experience work in in teams with a partner institution to explore a topic (data analysis, process improvement, etc.) of business interest of that partner institution. Depending upon the data security policies among partner institutions as well as federal and state privacy regulations, students could potentially be required to perform work on-site at the partner institution. Regardless, significant time outside of class will be required to complete the deliverables of the project AND deliver value to project sponsors.

 

Students will learn:

  • Project management skills for data analytics projects
  • To clarify problems and document accurate problem statements
  • How to provide weekly progress reports and status updates
  • Working within a professional team, including how to give constructive feedback to team members.

 

Students will be able to:

  • Apply concepts from all Tippie College of Business core courses to help organizations understand their problems and potential impact of solutions.
  • Organize, manage, and execute analytics projects to help organizations solve problems
  • Apply concepts from all BAIS courses to help solve those problems
  • Run status meetings with their project sponsor
  • Implement a software solution to analyze data from the project sponsor
  • Summarize and present process, findings, and recommendation to project sponsor

List of skills and activities in BAIS elective courses.


 

BAIS:3800 - Optimization and Simulation Modeling:  (offerings planned fall & spring semesters)

In Optimization and Simulation Modeling, students learn the art and science involved with translating a business problem stated in layperson’s terms into a mathematical model that can provide actionable insight for the decision-maker. Students learn to assess the business problem, acquire the appropriate data, and formulate a mathematical model that captures the essential elements of the decision-making problem. Using spreadsheet software, students will learn how to employ data to guide business decisions in areas such as operations, accounting, finance, marketing, economics, and human resources.

Students will:

  • Understand what factors make a decision difficult and identify the appropriate modeling technique (optimization or simulation)
  • Formulate optimization models by identifying the business objective and constraints and stating these in terms of decision variables
  • Understand the difference between linear and nonlinear optimization models and the implication of this difference
  • Model logical conditions using binary decision variables
  • Use data to model uncertainty via probability distributions
  • Construct Monte Carlo simulation models to quantify risk

 


 

BAIS:4280 - Cyber Security: (offerings planned spring semesters)

This elective course...

 


 

BAIS:3025 - Business Process Automation: (offerings planned fall semesters)

This elective course...

 


 

BAIS:3140 - Information Visualization: (offerings planned fall spring semesters)

This elective course...

 


 

BAIS:3100 - Accounting Information Systems: (offerings planned fall & spring semesters)

This elective course...

 


 

BAIS:4220 - Advanced Database and Big Data: (offerings planned spring semesters)

This elective course...

 


 

BAIS:3300 - Digital Project Management: (offerings planned spring semesters)

In this course, students will focus on collecting user requirements, planning and designing systems solutions, and managing software projects using AGILE. Students will work through each phase of the Software Design Life Cycle in a multi-developer environment while applying Agile concepts to keep their project on track.

Students will learn:

  • Project discovery, prioritization, and initiation
  • Planning:
    • Identifying personas and user classes
    • Requirements gathering through user stories
  • Analysis:
    • Use case diagrams
    • Use case elaboration
    • Activity diagrams
  • Design:
    • UI/UX
    • Site map
    • Screen sketches & wireframes
    • Storyboards
    • Class diagrams
    • Architecture
  • Implementation:
    • Git & Github (individual and multi-developer)
    • HTML5
    • CSS3
    • Bootstrap
  • Python and Flask to create a database-driven web application
  • SQLAlchemy ORM for database record SCRUD
    • Search record(s)
    • Create record(s)
    • style="font-size:1.75rem">Read record(s)
    • style="font-size:1.75rem">Update record(s)
    • Delete record(s)
  • API and JSON data
  • Testing
  • Deploy to Microsoft Azure cloud using CI/CD

 

Students will be able to:

  • Give a solid understanding of the issues involved in planning and designing an information system that successfully supports a business operation.
  • Acquire hands-on experience in designing an information system using today's software tools and Agile development principles.
  • Navigate the issues involved in a multi-developer environment.
  • Prepare a software project proposal and deliver a professional presentation of their final product.
  • Utilize Microsoft Azure cloud environment for web applications.

 


 

BAIS:3400 - Cloud Computing: (offerings planned fall semesters)

In this Icourse, students will learn the fundamental skills necessary for utilizing compute, storage, and database resources in the cloud. After this course, students will be prepared to sit for the Amazon Web Services, Cloud Practitioner certification exam.

Students will learn:

  • Internet literacy:
    • IPv4 and IPv6
    • DNS
    • Firewalls & ports
    • Linux operating system
  • Cloud literacy:
    • Pay-as-you-go
    • Shared responsibility model
    • Infrastructure as a Service (IaaS)
    • Platform as a Service (PaaS)
    • Software as a Service (SaaS)
    • Scaling
    • Data durability
    • Data reliability
  • Amazon Web Services (AWS)
  • AWS Compute:
    • Elastic Compute Cloud (EC2) compute
    • Lightsail
    • Lambda
    • Elastic Beanstalk
  • AWS Storage:
    • Simple Storage Solution (S3)
    • EC2 instance storage
    • Elastic Block Storage (EBS)
    • Elastic File Storage (EFS)
    • Glacier
  • AWS Database:
    • Amazon SQL & NoSQL options
    • AWS Network:
    • Virtual Private Clouds (VPC) & subnets
    • Virtual Private Networks (VPNs)
    • Gateways
  • AWS Security:
    • Network Access Control Lists (NACLs)
    • Bastion hosts
  • Wireless Local Networks
    • Wireless standards
    • Wireless configuration
    • Security
    • Performance

Students will be able to:

  • Identify and configure appropriate Internet protocols, applications, and technology for end-to-end network connectivity to the cloud.
  • Define basic principles, protocols, and technology used in cloud computing. 
  • Understand current cloud computing service models as well as issues with using cloud computing in modern enterprise networks.
  • Identify appropriate uses for cloud computing, cloud storage, and cloud databases. Demonstrate the ability to configure these resources using Amazon Web Services.
  • Understand the characteristics, utilization, and proper configuration of wireless networks for local communications.
  • Demonstrate the ability to build a small website, drive traffic to the site, and analyze their visitors' behavior.
  • Pass the Amazon Web Services, Cloud Practitioner certification exam.  https://aws.amazon.com/certification/certified-cloud-practitioner/

 

 

List of BAIS elective courses offered in other departments.


 

CS:1210 - Computer Science I:Fundamentals:

This elective course...

 


 

ECON:3355 - Economic and Business Forecasting:

This elective course...

 


 

MKTG:3102 - Marketing Analytics:

This elective course...