Software Design for Data Science
What you'll learn
- Use this discount code at checkout: 6D66AEF5E0D52DCB0DF3
- Learn how to structure the code for writing Data Science applications
- Learn the fundamental software design principles for Data Science
- Learn how to use custom Annotations, and which ones to use
- Build your own Annotations and place them exactly at the best places in the code
- Develop your own logger and configure it in the optimal way
- There are no prerequisites because we build all the necessary knowledge slowly! Jump straight in!
What is the course about:
This online course teaches you how to actually write code for developing Data Science Software.
The principles of software design depend on the program we have in mind. If we aim for Data Science applications then the Software Design must apply a different set of principles than if we aim for developing software for web applications.
Software Design for Data Science needs to be able to handle the data structures encountered in Data Science.
This course goes through the most important and fundamental practices of Software Design used in practice and explains them using intuitive examples, to ensure you truly comprehend the material.
Senior scientists part of high-tech projects at the intersection of Academia & Industry.
Doctor of Philosophy (Ph.D.) in Analytics & Mathematical Optimization applied to Energy Investments, and Masters of Engineering (M. Eng.) in Power Systems and Economics.
Prerequisites: The course Data Science Code that appears all the time at Workplace.
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 explain everything in detail.
Who this course is for:
- Investment Bankers
- Academics, PhD Students, MSc Students, Undergrads
- Postgraduate and PhD students.
- Data Scientists
- Energy professionals (investment planning, power system analysis)
- Software Engineers
- Finance professionals
Senior Research Scientists in Data Science, Mathematical Optimization and Quantitative Finance at the intersection of Academia and Industry (quantitative and analytical / consulting), involving application, teaching and research publications.
Hold a Doctor of Philosophy (Ph. D.) in Mathematical Optimization and Data Science, as well as Software Development applications for Quantitative Energy.