AdvancedEngineering trackAE-CP-39

District Cooling Demand Forecasting

Internship role: Energy Analytics Intern. Forecast next-day cooling load for a district-cooling plant and optimise thermal-storage charging; measured by peak-demand and cost reduction.

10 Guided Steps120h Internship TierSubmit: GitHub repo or evidence pack + live demo / report + README + milestone logbookVerified CertificateAI Rubric Graded

Program Overview

Internship role: Energy Analytics Intern. Forecast next-day cooling load for a district-cooling plant and optimise thermal-storage charging; measured by peak-demand and cost reduction.

What you submit

GitHub repo or evidence pack + live demo / report + README + milestone logbook

Stack: Python, weather and load data, XGBoost, Grafana

How it is graded

Signals: Milestone gates met; measurable result reported; documentation; deployment or evidence reachable; reflective log

Functionality & requirements30
Technical quality & architecture25
Documentation15
Deployment & evidence15
Innovation10
Presentation5

Pass 60% · Merit 75% · Distinction 90%

Learning Outcomes

120-hour United Arab Emirates programme. Empower and Tabreed run the world's largest district-cooling networks in the UAE.

Target Audience

Engineering Students

Diploma, B.Tech, B.E., BCA, MCA, or M.Tech students seeking practical experience.

Aspiring Developers

Developers who want to build proof-of-work capstone projects for tech resumes.

Job Seekers

Graduates looking for AI-evaluated code review & verified industry credentials.