System Advisor Model (SAM) for Renewable Energy Finance — PickAClass
⏱ 2h 48m 📚 28 lessons 🎧 Audio version

System Advisor Model (SAM) for Renewable Energy Finance

Learn how to use the System Advisor Model to assess the performance and financial viability of solar, wind, and other renewable energy projects.

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About this course

Are you involved in planning or evaluating renewable energy projects but need a reliable tool for financial forecasting? The System Advisor Model (SAM) is essential for turning technical data into viable business decisions. This course provides a practical, step-by-step introduction to using SAM for detailed performance modeling and economic analysis. You will gain the skills necessary to accurately forecast project returns, evaluate financing options, and understand the core metrics driving renewable energy investments. What you'll learn: * Understand the core components and input requirements for accurate technical and performance modeling in SAM. * Practice setting up detailed technical models for common renewable technologies like photovoltaics and wind. * Configure modern financial structures, including Power Purchase Agreements (PPAs) and various debt financing models. * Analyze key economic metrics such as Net Present Value (NPV), Internal Rate of Return (IRR), and Levelized Cost of Energy (LCOE). * Apply sensitivity analysis to evaluate project risk under changing market conditions or resource variability. The course begins with foundational concepts of renewable energy project economics and guides you through setting up, running, and interpreting project simulations within the SAM environment. We emphasize understanding the relationship between technical inputs and financial outputs. This course is designed for absolute beginners—project analysts, engineers, and finance professionals new to renewable energy modeling. No prior experience with the SAM software or advanced financial concepts is required. Start developing robust financial models for sustainable energy investments today.

What you'll get

  • 📜 Certificate of completion
    Add it to your LinkedIn profile
  • 💬 Personal AI tutor
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  • 🎧 Audio version included
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  • ♾️ Lifetime access
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  • 📱 Phone or computer
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  • 💸 14-day refund
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  • Short & focused
    2h 48m of practical content

Certificate of completion

Every course you complete on PickAClass issues a credential like this — original, with its own code, verifiable by URL, and detailed about what was actually demonstrated.

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Certificate of Mastery
This certifies that
Name Surname
has successfully demonstrated mastery of
System Advisor Model (SAM) for Renewable Energy Finance
Skills demonstrated
Behavioral pattern analysis
Foundational
1.2 hrs
Decision-architecture frameworks
Proficient
1.4 hrs
A/B test design
Proficient
1.7 hrs
Behavioral copywriting
Advanced
1.9 hrs
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PickAClass — Name Surname
System Advisor Model (SAM) for Renewable Energy Finance
Page 2 of 2
Performance detail
Coursework summary
Lessons completed 14 / 14
Practice questions 26 / 28
Assignments submitted 4 (avg 4.5 / 5)
Capstone project Reviewed — 4.6 / 5
Total practice 6.2 hrs
Performance benchmark
Cohort rank Top 12% of 1,625
Time to completion 11 days (median: 22)
Mastery score 91 / 100
Practice-question score 94%
Skill verification Verified Skill Path
Verify this credential
pickaclass.com/certificates/PCC-2026-X4F7-AP19
Issued under the academic standards of PickAClass. Skill levels reflect assessed performance against the course's competency rubric. This is an original credential of this platform.

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Frequently asked

What do I need to take this course? +

Just a phone or computer with internet. No installs, no special hardware.

How do I pay? +

By card via Stripe. We don’t store card details — Stripe handles them securely.

Can I get a refund? +

Yes — full refund within 14 days, no questions asked.

How long will I have access? +

Forever. Once you purchase, the course is yours to revisit anytime.

Will I get a certificate? +

Yes. On completion you'll receive a certificate you can add to your LinkedIn profile.

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