If you would like more information on payment options, please contact Jennifer Coppock at jscoppock@bauer.uh.edu

Business Analytics Bootcamp

August 19 - December 10, 2019

How much would your company benefit from having a cadre of problem solvers?

We have the only program developed and taught by a seasoned professional using 37 years of experience in solving very complex business problems.

Our Data Analytics Boot Camp trains bright people to become corporate problem solvers using data and analytics. Problems can run the gamut from pricing, to supply chain, to forecasting demand, to optimizing production. Problem solvers generate enormous value returns for their organizations by making them better, faster, and cheaper over time.

There is very high demand for Data Scientists, in fact it is one of the leading professions in the market at the moment. Harvard Business Review called it "The Sexiest Job of the 21st Century." According to Glassdoor, the average base pay for Data Scientists is $120,931. There is a reason Data Scientists are in such high demand. Employers all over the world are looking to make their firms more data-driven, more disciplined, and with a far better decision-making capability.

Graduates of the Bauer Data Analytics Bootcamp will leave ready to pursue employment as a Data Scientist. In just 16 weeks we will provide you with the skills and understanding for a career in Big Data.

COURSE DESCRIPTION
This boot camp is a concentrated program designed to prepare students for the extraordinary demand for corporate problem-solvers. Graduates will leave with the ability to use data, mathematics, and technology in concert to solve complex business challenges.

SKILLS INVENTORY COVERAGE

Analytical problem solving
Creating a comprehensive diagram of an enterprise
Data-driven strategy
Using statistics for business insight
Forecasting
Advisory on complex business operations, such as supply chain
Simulation and business modeling

Blockchain
Automation
Managing large data sets
Visualization/UI
Internet of Things (IoT)
Systems thinking
Factory thinking
Technical computing

PREREQUISITES & REQUIREMENTS
Students should be highly motivated with a basic understanding of business concepts, spreadsheet calculations, rudimentary office application skills, and math. Students are required to bring and use a current generation laptop computer.

COURSE FORMAT
In-class lectures are conducted in the evenings on Tuesday and Thursday from 6-8 p.m., followed by a Saturday morning lecture/lab from 9 a.m.-12 p.m. (this class is not presently offered online). Each week is a new unit.

DATE	UNIT	OUTCOMES
Week of August 19	Unit 1: Welcome to Business Analytics	Understand the scope of business problem solving Realize the range of topics in The Art of the Possible Overturn common myths
Week of August 26	Unit 2: The Analytics Process	Know the process for putting together effective solutions Create a correct hypothesis
Week of September 2	Unit 3: Dealing with Data	How to collect, manage, clean, and use data effectively
Week of September 9	Unit 4: Systems Thinking	Understand how to apply Systems Thinking, the underlying principle behind all modeling
Week of September 16	Unit 5: The Art of the Possible	Grounding in all of the common (and uncommon) methods that we have at our disposal to apply to highly complex problems
Week of September 23	Unit 6: Visualization	The skills to visualize the behavior of complex systems; how to make patterns self-revealing
Week of September 30	Unit 7: Tools of the Trade	A comprehensive grasp of the technology of problem-solving
Week of October 7	Unit 8: Case Study Walk-Throughs	Understand the problem-solving process through the lens of a handful of actual case studies from a variety of industries
Week of October 14	Unit 9: Simulation	How to create faithful replicas of complex businesses or subsystems to generate keen insight about their behavior
Week of October 21	Unit 10: Digital Twins and Automation	Automation of organizations through the development of Digital Twins
Week of October 28	Unit 11: Optimization	How to find the optimal performance for a system using mathematical methods
Week of November 4	Unit 12: Machine Learning	Using Machine Learning for classification and prediction
Week of November 11	Unit 13: Testing and Validation	How to ensure that analytical systems we build are both accurate and valid
Week of November 18	Unit 14: Analytics and the Enterprise	Tips for success when working within a large organization in an analytics role
Week of December 3	Unit 15: End of Course Project Reviews and Critiques	Review student course projects; presentations
Week of December 10	Unit 16: Advanced Topics	Going beyond the conventional: methods and technologies that are likely to shape future problem-solving

COURSE COST
$10,500

INSTRUCTOR
George E. Danner is the instructor for the course. He is currently President of Business Laboratory, an award-winning consultancy providing analytical problem-solving for organizations around the world. George has 35 years of experience in advising companies on their most challenging problems, and in building teams to do the same.

George has a BS in Mechanical Engineering from Texas A&M University and an MS in Management from The Sloan School at MIT.

TEXTBOOKS
Both textbooks were written by the course instructor, and are available for purchase online:

Profit from Science by George Danner
The Executive’s How-To Guide to Automation by George Danner

COURSE PROJECT
Students will be assigned a course project at the beginning of the course for completion by week 15. The project will resemble a real world application of business problem-solving.

Executive Education: Knowledge for the Real World

Business Analytics Bootcamp

August 19 - December 10, 2019

Main Navigation