Carl H. Lindner College of BusinessCarl H. Lindner College of BusinessUniversity of Cincinnati

Carl H. Lindner College of Business
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Data and Analytics Professional Development Courses

These courses are open to the public.  If you are an individual or business professional looking for analytics training, the Center for Business Analytics offers corporate training on a variety of business and data analytics topics. These short courses address some of the key skills required to increase data management skills and effectiveness and are taught by experts from the University of Cincinnati and from leading business analytics companies.

Download our Professional Development Flyer.

We also offer these and other customized courses at your location.  For more information on any of these on-site course options, contact Glenn Wegryn, Executive Director of the Center for Business Analytics at wegryngn@ucmail.uc.edu or 513-556-7146.

2017 PROFESSIONAL DEVELOPMENT CLASSES (open to all)

Introduction to Programming with PythonSept 14 & 15
Tableau TrainingSept 21 & 22
Introduction to 'R'Oct 5 & 6
Text Mining with "R"Oct 19 & 20
Tableau TrainingNov 2 & 3
Analytics In ExcelDec 14 & 15

INTRODUCTION TO PROGRAMMING WITH PYTHON                                Sept 14 & 15                      

Python is one of the most powerful and widely used programming languages available.  Its easily understood syntax makes it a popular choice for new coders, while its library or open source modules for everything from web development to data analysis make it the tool of choice for many fields.  This course will focus on the foundations of Python programming, helping both new and experience programmers master basics through hands on exercises and real world data sets.   

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Course Location:
U-Square. Room 359
225 Calhoun Street
Cincinnati. OH 45219

DETAILS AND REGISTRATION

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TABLEAU TRAINING                                                                Sept 21 & 22, Nov 2 & 3

Course Description: This two-day workshop on Tableau will cover beginner, intermediate and advanced topics in Tableau. This course will be taught by Jeffrey Shaffer, a Tableau Zen Master.

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 352 or 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

DETAILS AND REGISTRATION

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INTRODUCTION TO "R"                                                                Oct 5 & 6

Course Description: R is one of the fastest growing programming languages and tool of choice for analysts and data scientists.  In part, R owes its popularity to its open source distribution and massive user community.  In this course, we will help both new and existing R users master the basics of R.   There will be an emphasis on using hands on exercises and real world datasets.

Upon successfully completing this course, students will:

  • Be up and running with R
  • Understand the different types of data R can work with
  • Understand the different structures in which R holds data
  • Be able Import data into R
  • Perform basic data wrangling activities with R
  • Compute basic descriptive statistics with R
  • Visualize their data with base R and ggplot graphics

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 352 or 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

DETAILS AND REGISTRATION

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TEXT MINING WITH "R"                                                                                Oct 19 & 20         

This short course is as an introduction to text mining with the R programming language. Much of the data proliferating today is unstructured and text-heavy and many analysts are not trained in analyzing unstructured text data. A few of the covered areas includes structuring text data, word frequency analysis, sentiment analysis, word relationships, topic modeling analysis and more. includes hands on practice with data sets.

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Course Location:
U-Square. Room 359
225 Calhoun Street
Cincinnati. OH 45219

DETAILS AND REGISTRATION

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ANALYTICS IN EXCEL                                                                Dec 14 & 15           

Course Description: This course will introduce intermediate-to-advanced tools in Excel for analytics. We will cover data visualization topics that move beyond the basic charting tools in Excel. Descriptive analytics methods for analyzing data and generating meaningful insights will be covered using PivotTables, PivotCharts and other Excel tools. We will use Excel for predictive analytics by utilizing Excel’s regression tools and other forecasting capabilities. What-if analysis and other prescriptive analytics tools in Excel will also be introduced. We will cover special Excel functions such as VLOOKUP, MATCH and Data Tables to help you unleash the power of Excel as an analytics tool. This is the perfect class for the Excel user who is ready to take the next step of improving their analytics capabilities in a familiar software environment. 

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

DETAILS AND REGISTRATION

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OTHER CLASSES - NOT CURRENTLY SCHEDULED

INTRODUCTION TO BIG DATA AND FUNDAMENTALS OF HADOOP                                

This two-day introductory course in Big Data and Hadoop explores drivers behind Big Data and uses cases to illustrate the power of new technologies to harness Big Data and generate meaningful insights. This is an introductory course in Big Data and Hadoop, but it will go beyond basics to introduce some technical components. It is appropriate for those that just want to learn more about Hadoop and Big Data and those that are looking to begin on a path to becoming a Hadoop developer.

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Course Location:
U-Square. Room 359
225 Calhoun Street
Cincinnati. OH 45219

DETAILS AND REGISTRATION  

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APPLIED ANALYTICS WITH "R"                                                              

This is the third course in the "R" series and will build on the material from "Intermediate "R".  Attendance at the introductory or intermediate course is not required for those with significant practical experience in a professional setting but it is strongly encouraged that attendees have significant experience with the topics covered in those courses. This course will cover the application of several descriptive, predictive and prescriptive analytic techniques.  The emphasis will be on the general purpose of these techniques along with integration and application in R rather than on the theoretical nature.  This allows this course to be more accessible to a wider audience looking to inject R for analytic purposes across organizational processes. There will be an emphasis on using hands on exercises and real world datasets.

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Course Location:
U-Square. Room 359
225 Calhoun Street
Cincinnati. OH 45219

DETAILS FOR APPLIED ANALYTICS WITH "R" _______________________________________________________

 

USING DATA VISUALIZATION TO TRANSFORM DATA INTO INSIGHTS

Course Description: Data by itself is meaningless. Data visualization encompasses a set of techniques and principles that can be used to transform data at its most basic form into charts and tables that can be analyzed and presented to generate insights and spur action. This two-day workshop will teach participants how to use data visualization to both analyze complex data setsay 4 & 5 to generate insights and to present analytical output as meaningful information. The course will cover data visualization best practices, design principles for creating effective data visualization, and leading software demonstrations (advanced Excel features, Tableau, etc.) to show participants how to effectively display and analyze complex data sets. We will introduce interactive data visualization tools to create data dashboards that can be used to monitor the status of your organization and to create exceptional opportunities for generating competitive advantage. This course is suitable for all levels of participants interested in learning more effective data visualization techniques.

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

DETAILS FOR USING DATA VISUALIZATION TO TRANSFORM DATA

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INTERMEDIATE "R'                                                                      Feb 23 & 24

This is the second course in the "R" series and will build on the material from "Introduction to "R".  Attendance at the introductory course is not required for those with significant practical experience in a professional setting.  This course will cover the application of R for the entire data science workflow – data acquisition, wrangling, visualization, analytic modeling, and communication.  There will be an emphasis on using hands on exercises and real world datasets.

Upon successfully completing this course, students will:

  • Be able to work in a fully reproducible literate statistical environment
  • Have mastered the data wrangling process to include handling text data and scraping structured and unstructured online data
  • Understand how to minimize code duplication by applying control statements, the apply family of functions, along with developing their own functions
  • Be fluent with exploratory data analyses
  • Understand the analytic modeling process
  • Be able to communicate their analysis through a variety of mediums

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 352 or 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

DETAILS FOR INTERMEDIATE "R"

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INTRODUCTION TO DATA MANAGEMENT                                     

This is the first course in the Data Management Series.   

Course Description: Data is the foundation from which business analytics, data visualization, and business intelligence originates.  This course focuses on learning the steps to get data into a well-designed database and teaches participants how to use Structure Query Language (SQL) to interact with data. The course will start with topics related to database design and data rules to provide participants with a sound knowledge of databases and relational data design.  The course will focus on learning Structure Query Language (SQL) to interact with the data. This course will allow all levels, from novice to experienced users, the chance to learn advanced skills, syntax, and techniques to perform analytics and data mining on datasets.  The class will finish with the coverage of practical examples to solve common business problems, efficient database structure design, and solutions on how to create interactions between analytical tools and a database. This class will leverage an individual’s strengths in business, information technology and analytics, and is meant for those wanting to learn more about databases and programming in SQL.

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

Details for Introduction to Data Management

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ADVANCED DATA MANAGEMENT                                            

This is the second course in the Data Management Series. 

Course Description: Advanced Data Management is a continuation of the topics discussed in the Introduction Data Management course.  This course focuses on learning dimensional modeling and data warehousing techniques along with teaching participants advance SQL code.

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

Details for Advanced Data Management

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DATA MINING                                                                        

Material will be accessible to novice practitioners, but some experience with common predictive models and one or more analytics software packages will be helpful.

Course Description:  Most organizations do not suffer from a lack of data, but from a lack of actionable insights based on that data. Powerful techniques now exist to take messy data sets and generate surprising insights. Textbooks and websites tout the power of data mining, but few sources actually discuss the difficulties and challenges that must be overcome with real world data. This two-day workshop will focus on the challenges of building predictive models in the real world and techniques experienced practitioners apply when developing their models.

Attendees will learn through interactive discussion, case studies and hands on assignments.  R will be used in the classroom, but instructors will take questions regarding other packages.                                              

Course Fee: $695 includes breakfasts, lunches, refreshments and free parking for both days.

Location:  U-Square Room 359                         
                 225 Calhoun Street
                 Cincinnati, Ohio 45219

Details For Data Mining

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Prescriptive Analytics: Building and Solving Optimization Problems

Prescriptive Analytics involves the use of models that prescribe a course of action. This course will teach participants how to go from a problem statement to an optimization model and how to solve the model using open-source and commercially available software. Applications in finance, operations, supply chain, marketing and more will be covered.

 

Introduction to Big Data and Hadoop

Course Description: The production of data is expanding at an astounding pace. The recent explosion of individual data through social media, digitization of every aspect of life and wide-ranging ecosystem of everyday physical objects connected to the Internet has resulted in unprecedented amounts of data for organizations to collect and analyze. This two-day workshop explores the drivers behind Big Data and uses cases across a wide variety of industries to illustrate the power of new technologies to harness Big Data and generate meaningful insights. Participants will be introduced to Hadoop, the focal point of the Big Data movement, which is a popular software framework that allows distributed processing of very large data sets, both structured and unstructured. Participants will learn how the Hadoop core works – HDFS and Map Reduce; participants will be introduced to several ecosystem components like Pig, Hive, HBase and Mahout. This is an introductory course in Big Data and Hadoop, but it will go beyond the basic ideas to introduce some technical components. It is appropriate for those that just want to learn more about Hadoop and Big Data and those that are looking to begin on a path to becoming a Hadoop developer.

 

From Mess to Model

Course Description: Real life is messy. All of us have encountered the feeling of “Where do I begin?” when facing a difficult problem or decision. This course will instruct attendees on how to take complex problems and transform them into structured models where advanced analytics methods can be applied to generate solutions. The course will introduce influence diagrams and decision trees for defining the problem and structuring a model. The course will discuss rapid prototyping of models to generate potential approaches. Proper modeling form and enhanced spreadsheet models will be emphasized. Prescriptive analytics methods such as optimization and simulation will also be discussed to solve the generated models.

 

Fundamentals of Web Analytics

Course Description: With over 500 websites created and 2 million Google searches made every minute of every day, there is no shortage of data online.  Understanding how to use all this data to uncover meaningful insights is a challenge faced by many digital marketers and analysts today.  In this 2 day course, we will review the basic principles of analysis particularly in the digital space.  We will discuss web analytics architecture, implementation and overall strategy with the goal of not only providing the best practices and examples of how web analytics can be done right but to empower attendees to be more data-driven with business decisions, particularly in the digital space.

 

For questions and further course information please contact:

Larry Porter
porterlc@ucmail.uc.edu
513-556-4742