Oct 2 (edited) • 💻 Technical Skills
What you get as a Subscriber
A beginner-friendly training program without prerequisites, for a career in the energy sector.
Regardless of your location, age, sex, education level, work experience.
The energy sector has always been resilient against any economic crisis, but recently it has been growing so rapidly that the demand for skilled professionals is higher than the supply.
Subscribers get:
- Access to 110 beginner-friendly online courses on Energy Economics/Finance all developed by Dr Giannelos. The courses are designed to save you massive amounts of time as you will learn exactly what is used in practice and how it is used. Each course includes code (Data Science, Machine Learning and Optimisation) and theory, all explained as simple as possible. Find them all in the 'Classroom'. Or, scroll down in this message to view the recommended curriculum for beginners. No prior experience in coding or energy / economics / finance needed
- Access to Dr Giannelos for any questions you may have, every day. Ask for a personalized program. Or request help on the code or on the video you are watching. Or ask about your career
- Access to Dr Giannelos for guidance on your curriculum, every day. Specifically, there is no need to learn all 110 online courses. Rather, you will start with a personalized curriculum, depending on your career goals, existing skills, time availability, special circumstances. The program will be flexible so that it can be modified along the way.
- Access to energy-related articles from the Financial Times, Wall Street Journal, the Economist, etc, without you having to subscribe to these publications, which would cost you hundreds of dollars per month! Your Skool subscription covers everything! Dr Giannelos reads the articles for you, and brings you the key points along with his commentary and extra details you need to know, all written in simple beginner-friendly language, without intimidating jargon!. All analyses can be found in Classroom --> section 6.2
- Access to energy-related research publications and books, without you having to purchase them or subscribe. Dr Giannelos brings you the key points along with his commentary and extra details, all written in simple beginner-friendly language. This will offer you unprecedented insights that will help you stand out. Find all analyses in Classroom --> sections 6.1, 6.4
- Access to job opportunities and career guides. Find them all in Classroom --> section 6.3
- Get a certificate of completion for every course you complete
- Get feedback on your CV
- Join a Real-World Project, a simulation of real-world energy consultancy
- Join beginner-friendly interactive classes offered by Dr Giannelos
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ARE YOU NEW TO ENERGY ECONOMICS? START WITH THE FOLLOWING 35 COURSES
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1) Hourly Electricity Demand at Busbar Level. Go to Classroom --> 1.27
2) Hourly Electricity Demand for All Grid Buses. Go to Classroom --> 1.28
3) Drivers for Electricity-Grid Reinforcement: Go to Classroom --> 5.2
4) Per Unit System for Power-System Analysis. Go to Classroom --> 4.1.
5) Comparing Countries’ Population in Python: Go to Classroom --> 1.21
6) Comparing the Electricity-Generation Mix. Go to Classroom --> 1.22
7) Calculating the Installed Generation Capacity. Go to Classroom--> 1.23
8) Aggregating & Summarising Electricity Data. Go to Classroom --> 1.30
9) The Global Installed Capacity of Renewables. Go to Classroom --> 1.34
10) Day -Ahead & Balancing Market in Python. Go to Classroom --> 5.17
11) Retail Electricity Market in Python. Go to Classroom --> 5.18
12) Oil Forward Contracts in Python. Go to Classroom --> 5.19
13) Oil Option Contracts in Python. Go to Classroom --> 5.20
14) Financial Discounting in Energy. Go to Classroom --> 5.3
15) Wholesale Electricity Price in Python. Go to Classroom --> 5.6
16) Capitalisation Factor for Energy Investments. Go to Classroom --> 5.7
17) Locational Marginal Electricity Price Model. Go to Classroom --> 4.27
18) Electricity Demand: Power versus Energy. Go to Classroom --> 1.2
19) Levelised-Cost-of-Energy (LCOE) - in Python. Go to Classroom --> 1.12
20) Univariate Deep Learning for CO₂Forecast. Go to Classroom --> 2.4
21) Object-Oriented Programming for Energy. Go to Classroom --> ID: 3.1
22) Spot-Market Strategy for Power Stations. Go to Classroom --> 4.31
23) Optimal Siting of Onshore Wind Farms. Go to Classroom --> 4.8
24) Energy Storage Allocation at minimum cost. Go to Classroom --> 4.12
25) Economic Dispatch for Grid with Renewables. Go to Classroom --> 4.14
26) Economic Dispatch with Wind & Storage. Go to Classroom --> 4.16
27) Optimisation: Natural Gas & Electricity Grids. Go to Classroom --> 4.24
28) Economic Dispatch with Hydro Generation. Go to Classroom --> 4.19
29) Energy Storage Data Analytics. Go to Classroom --> 1.5.
30) Power-Station Data Analytics. Go to Classroom --> 1.6.
31) Electricity Demand: Power versus Energy. Go to Classroom --> 1.2.
32) Connecting Offshore Wind Farms to Onshore. Go to Classroom --> 1.3.
33) Profit Maximisation in Energy+Reserve Markets. Go to Classroom --> 4.18
34) Software Design for Energy Modelling. Go to Classroom --> 3.4.
35) DC-Power-Flow Modelling. Go to Classroom --> 4.7.
A total of 110 courses are available in the Classroom!
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- PhD in Energy, Imperial College London
- 40+ research publications, over 1100 citations. View profile
- Author on Substack. View profile
- Energy Data Science consultant at www.energydatascientist.com
- Connect on LinkedIn
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What you get as a Subscriber
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A beginner-friendly training program for a career in the energy sector. Regardless of your location, age, sex, education/experience level
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