English | Size: 571.89 MB
Genre: eLearning
Learn the 1% of Python and Data Science that is used 99% of the time at Workplace! Save time & increase productivity!
What you’ll learn
Very Experienced PhD level Instructor
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In practice, 1% of Python is used 99% of the time. This course focuses on this 1%
Great for Quants/ Economists, Data Scientists/ Software Engineers: the skills shown here, come up all the time
This is your Help Resource when you are under heavy pressure! You open this course and search for a keyword/command you want. And you will watch the video
You will not need to google-search to find answers all the time. Just have this course open in one tab of your browser so that any time you search in it!
What is the course about:Save your time and learn only what you will need 99.9% of the time in real life.The idea is that this course can be your encyclopedia. When you don’t remember how something is done in Python, you just come to this course and search for the keyword and immediately watch the video and remind yourself. Python and Data Science are infinite … you can keep learning and learning forever. But why waste time? In the end, in real life, you will need to perform, as quickly as possible. And this comes down to knowing the skills, the techniques, taught in this course! Details:We are senior Research Scientists & have been part of high-tech projects at the intersection of Academia & Industry, prior to, during & after the Ph.D. Doctor of Philosophy (Ph.D.) in Analytics & Mathematical Optimization applied to Energy Investments, and Masters of Engineering (M. Eng.) in Power Systems and Economics.Important: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.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.
Who this course is for
Entrepreneurs
Economists
Quants
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
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