Digital Transformation Technical Leaders Program

Empowering Scientists and Engineers to Lead the Digital Future

A customizable program designed to deliver business impact: newly skilled technical teams, the latest scientific computing technologies and techniques, a new generation of workflows.

Driving a Digital Future

The Digital Transformation Technical Leaders Program is a multi-month effort designed to develop scientists and engineers into digital scientists and engineers who will become the technical leaders of tomorrow. Through a combination of training and apprenticeship, real problems from the workplace are taken on. Real-time application of techniques ensures that relevant knowledge is gained throughout the program.

The program empowers scientists and engineers to use complex digital tools to solve tough technical problems, often creating entirely new workflows that can transform the way they work and accelerate science innovation.


Accelerating Skills Development

Everyone is fighting for the same digital talent. You can't hire them, and most companies don't have the resources or capabilities to create them. Enthought does. Enthought trains nearly 1,000 scientists and engineers every year, empowering them with the skills needed to accelerate their work leveraging state-of-the-art scientific computing.

A Program for Developing Technical Leaders

Duration + Location

Learning Activity


Onsite or Virtual

(2 weeks)

Introductory Courses In Scientific Python Gain foundational skills


(5 weeks)

Capstone Project Bridging the introductory courses and the apprenticeship, these science-based projects test trainees' ability to apply their python skills in a realistic environment. Regular instructor engagement ensures successful project completion.


(3-5 weeks)

Apprenticeship Prep 1. People Selection

2. Project Selection

3. Data Preparation

Onsite or Virtual

(3 weeks)

Apprenticeship on Projects Full-time intensive project


Daily mentoring/support


(3+ months)

Project Work + Individual Mentoring Ongoing mentorship supports the smooth transition of the apprenticeship project into the participants' real-work environment

Training Resources

New Application Transforms Chip Communication Subsystem Testing

Freescale Semiconductor needed to transform their testing processes. Freescale’s High Speed Signal Integrity (HSSI) group is responsible for testing the electrical characteristics of the communications…

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Active Learning Improves Polymer Formulation Scale-Up Efficiency

A Specialty Chemical Company Wanted to Remove the Bottleneck from their Polymer Scale-Up Process Many of the high tech products we interact with on a…

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10X Efficiency Gain and Improved Classification Using Deep Learning

Use AI techniques to efficiently extract mineralogy and grain size statistics from thin sections Thin sections provide the closest examination of in situ rock properties,…

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Accelerating Consumer Products Reformulation with Machine Learning

Consumer products need to be reformulated continually in order to adapt to new market forces, government regulations, and supply chain limitations. In some markets, sustainability…

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The Journey to Digital-centric Chemicals and Materials Laboratories

Digital technologies and the innovation they enable are steadily transforming chemicals and materials labs.  This webinar proposes five ‘levels’ of lab digital capability, providing managers…

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3 ways to identify digital transformation opportunities in your R&D lab

Is your R&D lab digitally mature? Do you use data and code to create value at every step of your R&D program? This webinar will…

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Integrating Weather and Renewable Energy Sources Data for 2.5 Million Viewers

Educating and developing a culture of responsible energy consumption The EnergizAIR project is presented both to show the innovative technology and methodology to solve the…

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Manual Processes for CSEM Replaced by Computational Tools and Strategies

Shell needed a way to effectively visualize a new scientific measurement Controlled-Source Electromagnetic sounding (CSEM) is a new tool for marine oil exploration. Sensitive electric…

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Predicting Pore Pressure From Very Limited Data Sets

ConocoPhilips wanted to make pore pressure predictions with limited data sets Logs from two wells and a limited set of 2D and 3D seismic were…

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AI/Machine Learning Techniques Quantify AVA Seismic Analysis Uncertainty

Help ConocoPhillips apply advanced AI techniques to Amplitude Versus Angle (AVA), seismic analysis Amplitude Versus Angle (AVA), seismic analysis is a well-established oil exploration tool….

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Steven Kern

Consulting Manager

Andrew Summers

Consulting Manager

Wahiba Taouali

Consulting Manager

Nicola De Mitri

Senior Scientific Software Developer