David Loughlan: How to get hired in analytics

Masterclass

David Loughlan: How to get hired in analytics

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David Loughlan, the founder of Data Idols, gives invaluable tips on how to get hired in analytics. There is an article to accompany this video here. 

1. David Sumpter: Using large language models for scouting
Professor David Sumpter 1. Using large language models for scouting
2. David Sumpter: Modelling player movements
Professor David Sumpter 2. Modelling player movements
3. David Sumpter: Predicting transfer values between leagues
Professor David Sumpter 3. Predicting transfer values between leagues
4. Jernej Flisar: Using data in set piece analysis
Jernej Flisar 4. Using data in set piece analysis
5. Ágúst Pálmason Morthens: Manager recruitment
Ágúst Pálmason Morthens 5. Manager recruitment
6. David Sumpter: Build your own language agent
Professor David Sumpter 6. Build your own language agent
7. Dominic Jordan: Data skills for the modern game
Dominic Jordan 7. Data skills for the modern game
8. Nicole Kozlova: Setting up your environment
Nicole Kozlova 8. Setting up your environment
9. David Sumpter & Dimitris Markou: AI Automated Opposition Analysis
Professor David Sumpter & Dimitris Markou 9. AI Automated Opposition Analysis
10. David Sumpter & Ida Höglund Persson: Quantifying your game model
David Sumpter & Ida Höglund Persson 10. Quantifying your game model
11. Nicole Kozlova: Data from a player’s perspective
Nicole Kozlova 11. Data from a player's perspective
12. Dominic Jordan: How to make your CV stand out
Dominic Jordan 12. How to make your CV stand out
13. Ana Beatriz Macedo: Data basics
Ana Beatriz Macedo 13. Data basics
14. Lars Ekman: Software engineering for language models
Lars Ekman 14. Software engineering for language models
15. Luis Mosquera Toscano: Power BI in football
Luis Mosquera Toscano 15. Power BI in football
16. Vosse de Boode: Building trust in analytics in the age of AI
Vosse de Boode 16. Building trust in analytics in the age of AI
17. Paul Power: Modelling sports as graph neural networks
Paul Power 17. Modelling sports as graph neural networks
18. Pegah Rahimian: How deep learning understands style, space and decision-making
Pegah Rahimian 18. How deep learning understands style, space and decision-making
20. Dave Carolan: Physical Data Masterclass
Dave Carolan 20. Physical Data Masterclass
21. Luis Mosquera Toscano & David Sumpter: Python pitfalls and how to avoid them
Luis Mosquera Toscano & David Sumpter 21. Python pitfalls and how to avoid them
22. Dimitris Markou: Adding context to measuring player performance
Dimitris Markou 22. Adding context to measuring player performance
23. Folkert Boer: How Feyenoord’s football department works as one
Folkert Boer 23. How Feyenoord's football department works as one

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