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Autor Tópico: Applied Data Science using Python Programming  (Lida 134 vezes)

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Applied Data Science using Python Programming
« em: 21 de Maio de 2020, 08:06 »

Applied Data Science using Python Programming
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
Language: English | VTT | Size: 1.95 GB | Duration: 2.5 hours

What you'll learn
Python programming
Supervised Machine Learning
Unsupervised Machine Learning
Build and deploy machine learning web-app
Web-scraping
Building map-Descriptions and putting up online

Requirements
Basics of statistics
Description
If you are reading this description - chances are you already know the vast potential Python and Data-Science has to offer. I need not repeat the promises - you know it better. If you are still reading this description - then it also tells that you want to learn it. But probably, you are shy, apprehensive or too busy to pick up a new programming language.

I understand, programming languages and data-science can be intimidating for people who come from non-technical backgrounds. But the good part is you want to learn it and make your career future-proof. Probably, you are searching for the easy first step to find some confidence and motivation. This course attempts to do exactly that.

This is a super-basic course intended for people who know absolutely nothing about python or data-science.

My aim is to help you learn python programming while learning to employ data-science solutions to financial investment problems. At it's best, this course is probably your first-stepping stone into the world of python and data-science. If you are a seasoned python programmer or data-scientist - this course might serve as a refresher (at the most). Like I mentioned, the level of this course is super-basic. Also, this is an applied course and there is little theory in it. I hope to offer some insight into the theory from the quizzes. But I recommend you to read books on python, data-science and statistics for more in-depth learning. Also, I have restricted the use of jargons in this tutorial and made it as simple as possible.

Why financial investment problems?

Money is a basic need for everyone of us - and almost all of us hope to buy an apartment, trade in stocks, and curious what type of customers will buy our product if we open a startup. No matter whether you are in academia or in industry - money connects us all.

Since this course is intended for people of different disciplines, students and practitioners from Management to Medicine, Social Sciences to Humanities might be interested to learn Python programming and implement data-science solution to their workplace problems. I chose financial investment problems for demonstration purpose - with a hope that everyone will be able to find it as a common platform - no matter what is your academic or trade background.

Disclaimer: This course is not meant for financial education and neither encourages financial investments. Also, I am not an expert in finance - so I do not recommend students to blindly invest their money after following my tutorials. Although I tried to follow research papers and investment websites still I do not have domain knowledge so there are chances that I might have mistaken. Most of the data used here are toy-data (i.e. I just made them up).

Who this course is for:
Absolute beginners in Python Programming and Data-Science

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