• views: 146
• date: 4 October 2023
• posted by: mitsumi

What you'll learn
The course describes the essential Python code that has appeared in Data Science projects that the Instructor has participated during his career
The Instructor is the CEO of MATHOPTIM and has a PhD in Data Science and has participated in 100+ data science projects.
In the end you will have understood the essential code that has appeared in all the real-world Data Science projects in which the Instructor has participated
This is an invitation-only course.
Requirements
There are no prerequisites because every line is explained in detail
Description
SUMMARY:The course describes essential Python code that has appeared in the Data Science projects that the Instructor has participated in, during his career.There are no prerequisites because every line of code is explained in the videos.The course includes 13 hours & 29 minutes of video.A total of 177 lectures.Each lecture includes a video, which is 1-15 minutes long, and a Python file (.ipynb) that you can download. That is, you can download 177 Python files in total.All 177 videos and 177 files are regularly updated to the most recent version of Python. This takes place typically 3-4 times every 12 months at no extra cost to you.These updates continue for life. This online course has no subscriptions. With a single payment, you get lifetime access to all its existing videos/files and to all updates that the code/videos will receive.You gain direct access to the Instructor. You can send your questions via email at no extra cost. This service has no expiration date.You can watch all 177 videos here and on Udemy.You will get a Certificate from Udemy upon completion.THE INSTRUCTOR:I have a PhD in Data Science / Optimization and years of Research experience.You can find me here, on Udemy, but you can also find me and my colleagues (all of us very experienced instructors) which is a platform dedicated to mathematical optimization.
Who this course is for
Data Scientists
Software Engineers
Professionals in Finance
Economists

Download link

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