UdemySoftware DevelopmentPaid courseAll LevelsCertificate

Software Design Principles for Energy Software Development (Udemy.com)

From Prototype to Production: Software Engineering for Energy Applications

4.8

144 reviews

Created by: Algorithmic Economist, PhD

Last updated September 2026

What you will learn

Master the Divide and Conquer principle through a complete smart energy system implementation
Apply all 5 SOLID principles to build flexible, maintainable energy software architectures
Optimize Cohesion across 7 different types (functional, layer, communication, sequential, procedural, temporal, utility)
Minimize Coupling using 5 key strategies (content, stamp, routine, type use, import coupling)
Design reusable components that can be shared across multiple energy projects
Refactor existing energy system code to follow professional design patterns
Evaluate software quality using industry-standard metrics and best practices
Build a complete energy application architecture from requirements to implementation

How it compares

Against the other 518 rated Udemy courses in Software Development on CourseDuck:

Rating4.8 out of 5higher than 93% of them
Reviews144#390 of 519 by number of reviews
Length4.7 hoursshorter than 65% of them
Last updatedSeptember 2026more recently than 93% of them

Course Description

WHO I AM: I hold a PhD from Imperial College London. My expertise is in power system economics, energy finance and energy markets, using machine learning, data science and optimisation.

BONUS: After you enrol, visit the very last lecture for a special gift.

What You'll Learn:

How to apply the Divide and Conquer principle to break down complex models into manageable components
How to implement SOLID principles (Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, Dependency Inversion) in software engineering projects for energy
How to optimize Cohesion and Coupling for building maintainable and scalable energy software solutions
How to design reusable code components that reduce development time and costs
How to apply these principles to real-world smart energy system applications

Perfect For:

Energy software developers and engineers
Data scientists transitioning to software engineering roles, with a focus on energy/economics
Energy system architects and technical leads
Full-stack developers in the energy/utility sector
Technical consultants in energy digitalization
Graduate students in energy informatics or computer science
Energy professionals learning to build production-ready code

Why This Course Matters:

The energy transition demands software that can handle massive data flows, integrate renewable sources, manage smart grids, and optimize energy trading - all while remaining maintainable and scalable. Poor software design costs the energy sector billions in technical debt and failed digital transformation projects. Companies desperately need developers who understand both energy systems AND professional software architecture. Whether you're building energy management platforms, trading algorithms, or grid optimization tools, these design principles are the difference between prototype code and production systems. Master the skills that transform you from a coder to a software architect, opening doors to senior engineering roles paying $180,000-300,000+ in the booming energy tech sector.

All Levels

Time: 4.7h

Udemy Discount

The discount is applied through our link. Open the course from here and Udemy's current promotional price is applied at checkout on most courses, no code to type.

Get the Udemy discount

Some courses are excluded from Udemy's promotions. If the price does not drop, clear your browser cookies and use the button again.

Instructor Details

Algorithmic Economist, PhD

4.8 Rating
144 Reviews

I hold a PhD from Imperial College London, where my research focused on power-system investment planning, energy economics and optimisation under uncertainty.

I teach practical quantitative methods at the intersection of energy markets, economics, finance and data, including machine learning and mathematical optimisation.

I have co-authored peer-reviewed papers and industry reports and worked on applied research and consultancy projects covering electricity networks, renewables, energy storage, hydrogen and energy markets.