Rating 4.71 out of 5 (20 ratings in Udemy)
What you'll learn- Great for Quant Developers & software engineers.
- Gain confidence in Polymorphism, OOP, Metaclasses & special topics
- Designed based on real-world industry projects (Google, McKinsey, JP Morgan).
- You will never need to google-search again to find answers on confusing Python topics.
- The subtitles are manually created so they are fully accurate. They are not auto-generated.
Description
What is the course about:
Assume that a …
Rating 4.71 out of 5 (20 ratings in Udemy)
What you'll learn- Great for Quant Developers & software engineers.
- Gain confidence in Polymorphism, OOP, Metaclasses & special topics
- Designed based on real-world industry projects (Google, McKinsey, JP Morgan).
- You will never need to google-search again to find answers on confusing Python topics.
- The subtitles are manually created so they are fully accurate. They are not auto-generated.
Description
What is the course about:
Assume that a company hires you to develop a Machine Learning / Economics/ Data Science model on Python - or assume that the company gives you code and expects you to read and understand it quickly. This course gives you all the skills you need to clarify those complex topics that always pop up.
Who:
Dr Gian is a Research Fellow at Imperial College London ; I have been leading academia-industry projects related to energy investments using mathematical optimisation, machine learning and data science.
Doctor of Philosophy (PhD) in Analytics & Mathematical Optimization applied to Energy Investments, from Imperial College London.
Master of Engineering (M. Eng.) degree in Power System Analysis (Electricity) and Economics from National Technical University of Athens.
Special Acknowledgements:
To Himalaya Bir Shrestha, energy system analyst, who has been contributing to the development of Python scripts for this course as well as on Medium.
Important:
No pre-requisites and no experience required.
Every detail is explained, so that you won't have to search online, or guess. In the end you will feel confident in your knowledge and skills.
We start from scratch, so that you do not need to have done any preparatory work in advance at all. Just follow what is shown on screen, because we go slowly and understand everything in detail.
