Professional Training Programs
Advance your skills in scientific computing, AI development, and research software with our comprehensive training programs. Serving researchers and developers worldwide.
Bootcamp
Intensive, immersive programs designed for rapid skill development. 5-day comprehensive training from fundamentals to advanced practices.
Workshop
Specialized skill sessions focused on practical, hands-on learning experiences. Perfect for learning specific tools and technologies.
Course
Structured learning programs covering specific technologies like Python, Julia, and data science. Best for thorough mastery of domains.
Custom
Tailored training solutions designed specifically for your team's needs and organizational requirements.
AI-Enhanced Scientific Programming Bootcamp
Comprehensive 5-day bootcamp combining Python programming with AI tools and techniques for scientific research, including AI-assisted development and modern research workflows.
High Performance Research Computing Bootcamp
Advanced 5-day bootcamp focusing on HPC fundamentals, parallel computing, containerization, and high-performance languages like Julia for computationally intensive research.
Research Software Engineering Bootcamp
Comprehensive 5-day intensive training covering all aspects of research software development from fundamentals to advanced practices, including FAIR principles, reproducibility, and collaboration.
Scientific Python Bootcamp
Intensive 5-day Python immersion from basics to advanced techniques, covering scientific libraries, data analysis, visualization, and best practices for research computing.
AI Assisted Scientific Programming
Leverage AI tools and copilots for scientific programming, automated code generation, debugging, and research acceleration.
API Design and Development
Learn to design, build, and document RESTful APIs for research software, enabling data sharing and integration with modern web services.
Containers and Orchestration
Master containerization with Docker, Kubernetes, and modern DevOps practices for reproducible research environments and scalable deployments.
Introduction to Software Development and Collaboration
Essential tools and practices: Git version control, GitHub collaboration, Linux terminal, and team development workflows.
Introduction to Version Control using Git and Collaboration on GitHub
Master version control fundamentals with Git and learn effective collaboration workflows using GitHub. Perfect for researchers and developers starting their journey in collaborative software development.
Python Programming - Advanced
Master advanced Python techniques including design patterns, metaprogramming, performance optimization, profiling, packaging, documentation, and deploying production-ready scientific software.
Python Programming - Beginner
Learn Python fundamentals including syntax, data types, control structures, functions, and basic file I/O for scientific applications.
Python Programming - Intermediate
Master scientific Python libraries including NumPy, pandas, matplotlib, object-oriented programming, and testing for data analysis and research workflows.
Python Programming for MATLAB Developers
Transition from MATLAB to Python smoothly with this targeted course covering NumPy, matplotlib, and scientific Python workflows tailored for MATLAB users.
Reproducible Research Practices
Comprehensive training on reproducible research practices following community best practices. Learn version control, testing, continuous integration, reproducible environments, and open research principles.
Software Management and Data Management
Master project management, version control, data lifecycle, FAIR principles, and software sustainability practices.
Introduction to High Performance Computing
Get started with HPC fundamentals, parallel computing concepts, cluster computing, and leveraging supercomputing resources for research.
Introduction to Julia Programming
Learn Julia programming language designed for high-performance scientific computing, combining the ease of Python with the speed of C.
Introduction to Numerical Methods with Python
Explore numerical methods for solving mathematical problems in scientific research using Python, NumPy, and SciPy libraries.
Open Science, FAIR Software and Data
Learn the principles and practices of Open Science, FAIR data management, and FAIR software development to make your research more reproducible, transparent, and impactful.
Scientific Visualization
Master data visualization techniques for scientific research, from basic plots to advanced interactive visualizations using Python, matplotlib, and modern visualization libraries.
Ready to Elevate Your Team's Skills?
Get in touch to discuss custom training solutions, group bookings, or to learn more about our programs.
Expert Instructors
Learn from experienced research software engineers
Customizable
Tailored to your domain and requirements
Group Discounts
Special pricing for institutional bookings