1.1. Part 1: Essential Python for Energy Analysis
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1.1. Part 1: Essential Python for Energy Analysis
This is part 1. The course teaches the Python programming you need for energy data analysis, progressing from essential data manipulation techniques to advanced concepts like multi-level dataframes, custom functions, and package management. Prerequisites: None. Level: Beginner. Video Duration of parts 1 and 2: 17 hours. Price: Free with your subscription. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.1. Part 2: Essential Python for Energy Analysis
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1.1. Part 2: Essential Python for Energy Analysis
This is part 2. The course teaches the Python programming you need for energy data analysis, progressing from essential data manipulation techniques to advanced concepts like multi-level dataframes, custom functions, and package management. Prerequisites: None. Level: Beginner. Video Duration of parts 1 and 2: 17 hours. Price: Free with your subscription. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.2. Electricity Demand: Power versus Energy
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1.2. Electricity Demand: Power versus Energy
The course teaches the distinction between power (W) and energy (Wh) in electricity systems. Also, it teaches data visualization techniques to correctly represent the electricity demand using line plots and scatter plots. Prerequisites: None. Level: Beginner. Video Duration: 25 minutes. Price: Free with your subscription. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.3. Connecting Offshore Wind Farms to Onshore
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1.3. Connecting Offshore Wind Farms to Onshore
The course teaches offshore wind farm development, including HVDC and HVAC offshore-to-onshore transmission lines, different wind turbine technologies. You will also develop a relevant Python model. Prerequisites: None. Level: Intermediate. Video Duration: 68 minutes. Price: Free with your subscription. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.4. Drafting Electricity Grid Schematics
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1.4. Drafting Electricity Grid Schematics
The course teaches how to design a basic electricity grid schematic i.e. the substation, loads & transmission lines, in Matlab & Python. You will learn about redundancy, N-X criteria, and meshed / radial grid architectures. Prerequisites: None. Level: Beginner. Video Duration: 67 minutes. Price: Free with your subscription. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.5. Energy Storage Data Analytics
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1.5. Energy Storage Data Analytics
The course teaches the technical details of energy storage systems, and how to conduct calculations and data manipulation on energy storage datasets, in Python. Prerequisites: None. Level: Beginner. Video Duration: 47 minutes. Price: Free with your subscription. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.6. Power-Station Data Analytics
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1.6. Power-Station Data Analytics
The course teaches data analysis for thermal, wind, and hydro power stations, including analysing electricity generation datasets, calculating electricity generation patterns, and handling installed generation capacity data in Python / Excel. Prerequisites: None. Level: Beginner. Video Duration: 110 minutes. Price: Included. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.7. Geopolitical Mapping of Military Alliances
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1.7. Geopolitical Mapping of Military Alliances
The course teaches how to visualise military alliances and territorial changes with Python. Learn to create visualizations of alliances like NATO, CSTO, and SCO and territorial shifts over time. This is a course on military geopolitics. Prerequisites: None. Level: Intermediate. Video Duration: 180 minutes. Price: Included. Support: Ask any questions here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.8.Comparing Datasets with Python & Excel
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1.8.Comparing Datasets with Python & Excel
The course teaches how to compare datasets using Excel and Python. Prerequisites: None. Level: Beginner. Video Duration: 33 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.9.Preparing Excel Data for Pivot-Table Analysis
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1.9.Preparing Excel Data for Pivot-Table Analysis
The course teaches how to change the format of an Excel file so that the data it contains becomes readable by pivot tables. This data transformation is implemented in Python. Prerequisites: None. Level: Beginner. Video Duration: 26 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.10.Mapping Energy Infrastructure with Python
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1.10.Mapping Energy Infrastructure with Python
The course teaches how to illustrate natural gas pipelines and electricity interconnectors on geographical maps using Python. Learn geospatial techniques from creating basic maps to advanced tasks. Prerequisites: None. Level: Beginner. Video Duration: 4 hours, 37 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.11. Net Electricity Demand & Wind Share
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1.11. Net Electricity Demand & Wind Share
The course teaches how to calculate the net electricity demand and express the output of wind units as a percentage. Prerequisites: None. Level: Beginner. Video Duration: 24 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.12. Levelised-Cost-of-Energy (LCOE) - in Python
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1.12. Levelised-Cost-of-Energy (LCOE) - in Python
The course teaches what the Levelized Cost of Energy (LCOE) is and how it is used through practical examples in Python. Prerequisites: None. Level: Beginner. Video Duration: 1 hour, 17 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.13. Reducing the dimension of Electricity Data
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1.13. Reducing the dimension of Electricity Data
Using Python and Excel, you will reduce the size of a large dataset with minimal information loss. You will learn the structure of big datasets for electricity demand and then step-by-step implement the big data methodology. Prerequisites: None. Level: Beginner. Video Duration: 2 hours, 29 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.14. Upsampling Daily to Hourly Electricity Data
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1.14. Upsampling Daily to Hourly Electricity Data
The course teaches how, from a dataset that has 365 values for electricity demand or generation, we can generate an equivalent dataset that has 8760 values, one value for each hour of the year, in Python. Prerequisites: None. Level: Intermediate. Video Duration: 46 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.15. Calculating Zone-Level Electricity Demand
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1.15. Calculating Zone-Level Electricity Demand
The course teaches how electricity grids are split into zones and how, using Python, to calculate the electricity demand for each of them. Prerequisites: None. Level: Beginner. Video Duration: 28 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.16.Modelling Flat and Peaky Load Profiles
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1.16.Modelling Flat and Peaky Load Profiles
The course teaches how to generate electricity load profiles that are peaky or flat. This is done using Excel and Python. Visualizations are created to explain the difference. Prerequisites: None. Level: Beginner. Video Duration: 31 minutes. Price: Free with your subscription. Access: After 45 days of membership and immediate access to annual subscribers. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.17.Big Data for Power Grid Reinforcements
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1.17.Big Data for Power Grid Reinforcements
The course teaches how data science is used in the datasets of energy companies with information about grid reinforcements. From a large dataset of candidate reinforcements, learn to narrow down to few alternatives. Prerequisites: None. Level: Beginner. Video Duration: 1 hour and 57 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.18. Comparing Countries’ Generation Capacity
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1.18. Comparing Countries’ Generation Capacity
The course teaches how to compare the installed electricity generation capacity of various technologies (e.g., Photovoltaics, wind farms, etc.) of countries (e.g., the U.K., etc.), across years (2010, ..., 2020, etc.). Prerequisites: None. Level: Beginner. Video Duration: 34 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.19.Comparing Electricity Access across Countries
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1.19.Comparing Electricity Access across Countries
The course teaches how to analyze data related to electricity access. You will also learn how to develop visual representations for electricity access across countries and years. Prerequisites: None. Level: Beginner. Video Duration: 31 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.20.Comparing CO₂-Emissions Intensity
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1.20.Comparing CO₂-Emissions Intensity
The course teaches how to use data science to plot the trend of the emissions intensity through time and for different countries. You will also learn how to interpret the results and draw conclusions about sustainability. Prerequisites: None. Level: Beginner. Video Duration: 46 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.21.Comparing Countries’ Population in Python
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1.21.Comparing Countries’ Population in Python
The course teaches how to compare countries' populations across different years, using official WorldBank data, in Python. Prerequisites: None. Level: Beginner. Video Duration: 10 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.22.Comparing the Electricity-Generation Mix
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1.22.Comparing the Electricity-Generation Mix
The course teaches how to use data analysis and the Geopandas package in Python for visualizing the electricity generation mix of different countries. Prerequisites: None. Level: Beginner. Video Duration: 12 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.23.Calculating the Installed Generation Capacity
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1.23.Calculating the Installed Generation Capacity
The course teaches how to calculate the installed generation capacity of power stations, in Python. Prerequisites: None. Level: Beginner. Video Duration: 16 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.24. Comparing Countries’ Electricity Consumption
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1.24. Comparing Countries’ Electricity Consumption
The course teaches how to build a Python model for visualising the electricity demand (consumption) of different countries across different years. We will use official data from WorldBank. Prerequisites: None. Level: Beginner. Video Duration: 30 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.25. Total and Residual Load-Duration Curves
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1.25. Total and Residual Load-Duration Curves
The course teaches how to develop and interpret the load duration curve using Python. The duration curve for the total and residual load will be defined and calculated as well. Prerequisites: None. Level: Beginner. Video Duration: 27 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.26. Baseload-and Intermediate-Load Levels
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1.26. Baseload-and Intermediate-Load Levels
The course teaches how to decompose load duration curves into base load, intermediate load, and peak load parts. This decomposition is essential for identifying the appropriate mix of base-load plants and flexible sources in the electricity grid. Prerequisites: None. Level: Beginner. Video Duration: 30 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.27. Hourly Electricity Demand at Busbar Level
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1.27. Hourly Electricity Demand at Busbar Level
The course teaches how to calculate the hourly electricity demand of a bus using Python. Prerequisites: None. Level: Beginner. Video Duration: 10 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.28. Hourly Electricity Demand for All Grid Buses
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1.28. Hourly Electricity Demand for All Grid Buses
The course teaches how to calculate the hourly electricity demand of every bus and then of all buses of the power system. Prerequisites: None. Level: Beginner. Video Duration: 14 minutes. Price: Free with your subscription. Access: After 45 days of membership or immediately to annual subscribers. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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1.29. Rolling Averages of Electricity Demand
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1.29. Rolling Averages of Electricity Demand
The course teaches how to calculate the rolling average (the moving average) for electricity demand. This technique allows for identifying trends. It is implemented in Python. Prerequisites: None. Level: Beginner. Video Duration: 50 minutes. Price: Free with your subscription. Support: Ask anything here on Skool. Instructor: Dr. Giannelos, PhD Imperial College London.
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