Citizen Data Scientist Program
In partnership with Daytum
This program is designed for:
Fundamental courses: Managers, SMEs, and technical professionals with little or no programming experience.
Application courses: SMEs with programming experience in Python who are looking for more advanced application and workflows.
Course Details:
Machine Learning for Executives
4 hours
Designed for managers looking to understand the possibilities/limitations of Maching Learning
You will learn how Data Analytics & Machine Learning can solve problems and what to expect from a Citizen Data Scientist
Introduction to Python
3 days
Designed for SMEs with little programming experience and no experience in Python
You will learn how to use Python software with sufficient skill to benefit in your day-to-day work
Introduction to Energy Data Science
3 days + coaching on real problems
Designed for SMEs with programming experience in Python
You will learn software engineering skills and interactive dashboard building using PyData software stack (NumPy, SciPy, Pandas, etc.) on petroleum data sets
Introduction to Subsurface Machine Learning
2 days + coaching on real problems
Designed for SMEs with programming experience in Python
You will learn advanced geostatistics and machine learning models with subsurface workflows in Scikit-learn and TensorFlow on petroleum data sets
Turbo Charge Excel with Pandas
1 day + coaching on real problems
Designed for SMEs with programming experience in Python
You will learn common Pandas workflows as a powerful replacement for Excel
Automation and Reporting in Python
1 day + coaching on real problems
Designed for SMEs with programming experience in Python
You will learn how to automate common reporting workflows
Program Instructors
John T. Foster, Ph.D., P.E.
Assoc. Prof at UT Austin Pet & Geosystems Eng.
Expertise in Data Science, Python/ C++/ Fortran/Julia, High Performance Computing, Software Engineering, Anaconda
Unconventional Resources, Computational Modeling, Hydraulic Fracturing and Reservoir Geomechanics, Reservoir Simulation
Michael Pyrcz, Ph.D., P.Eng.
Assoc. Prof at UT Austin Pet & Geosystems Eng. and Jackson School of Geosciences
Expertise in Data Science, Machine Learning, Python/ C++/R/Fortran
Geostatistics, Conventional and Unconventional Resources, Statistical Modeling, Geologic Carbon Storage, Geological Modeling, Petrophysics and Pore Scale Processes, Mining/Agriculture/ Environmental Spatial Modeling
