Python Real World Data Science Mega Project: Car Buyer App

Practise Exclusive Data Science Skills in a Most Practical End to End Project engaging Scrapy and Pandas, from scratch!!

What you'll learn

Learn how to apply Data Science for real world problem solving, a MUST_KNOW for all developers

Create the backend of a universal Car-Advisor Application, that recommends best deals in car ads

Go through an entire development process of a Data Science Mega Project, from problem definition to final product

Merge Web Scraping+Data Analysis using SCRAPY+PANDAS super-combo to solve a real-world problem

Requirements

Familiarity with programming concepts (variables, loops, libraries, functions, methods etc.)

Familiarity with web concepts: HTML, CSS, Javascript (no requirement of coding ability)

Motivation and Endurance to take on a real world data science app creation challange,

Description

Allow me to be forthright on this: We all are inclined to pick that long and broad course.  I call them 'little by little, everything to the middle' courses. Those courses are indeed good and have their place in the portfolio. However, in our limited time they do not get finished and sometimes they are too broad to guide you to create something real and useful. And that is a fact backed by statistics of almost any online learning platform.Here is my recomendation for you today: Why not to learn once for yourself, and not for a future hope or prospect? Why not to let data science do something for you right away, right now? Stop a moment please and do think about this!Welcome to 'Python Real World Data Science Mega Project: Car Buyer App'This course is, where your data science knowledge will evolve into a practical programming skill that creates solutions for real-world. You will create an application, that will recommend your next car, saving you time and effort while contributing to your personal finances. That is the most practical result you can get from a course.This will be achieved utilizing a comprehensive approach, so we will go through each and every step of problem solving in data science. From exploring the real world to definition of the problem that will ultimately end up in a strategy to solve it. We will carefully craft the implementation with many real life scenarios and examples and when we come up with a solution, we still will not stop.We will look for ways to exploit our results for other useful products. In the meantime, we will continue to revise our strategy and implementation to perfect our results. Throughout the course you will experience, how 'being able to extract the data you want from web, analyzing it the way you want, and the synergy you can create by these two steps' is an invaluable capability for a data scientist. We will use SCRAPY (framework) to extract data from popular car sites around the world and develop our data science application mainly using PANDAS (library). This course is within the framework of a series to master web-scraping and Scrapy from basic skills to advanced concepts, from deep insights on the tools to the most practical real-life data science example utilizing web scraping on this platform, a depth and perspective unique to this course series that collectively have gathered more than 10000 students in months.Let me tell you forthright: The approach depicted, implemented and taught here is unique to this course. In other words, you can not compare this course with others, because the focus, the implementation and the end results will be different.  Here, you will learn while you create a high-value backend application that you can practically use and benefit.  So it is not only about learning how a tool works but also how it is applied in data science context in real-life.Finally, a good course is the one that will make you capable and motivated to go further in that field, it will increase your self-confidence to tackle the real-world issues. This uniquely structured and implemented project-based-course exactly aims and does that.  Join and create a complete end to end data science project, and all of this with no risk, thanks to Udemy's guarantee policy. Be sure to watch the course video on this very landing page. See you in the lectures!Very Respectfully, Tarkan Aguner

Overview

Section 1: Introduction

Lecture 1 Intro-01: Points to Ponder

Lecture 2 Intro-02: Notes for your Consideration

Lecture 3 Intro-03: Roadmap

Section 2: ___000 THE STRATEGY

Lecture 4 0-01: Exploration of the Real-World

Lecture 5 0-02: The Plan

Lecture 6 0-03: Wrap it Up

Section 3: ___001 SCRAPE THE FIRST WEBSITE

Lecture 7 1-01: Start up the Spider

Lecture 8 1-02: Exploring the Website

Lecture 9 1-03: Spider First Attempts

Lecture 10 1-04: Spider Successful Run

Lecture 11 1-05: Spider Response Validation

Lecture 12 1-06: Spider Parse Function I

Lecture 13 1-07: Spider Parse Function II

Lecture 14 1-08: Spider Parse Function III

Lecture 15 1-09: Spider Parse Function IV

Lecture 16 1-10: Spider flip_pages Function I

Lecture 17 1-11: Spider flip_pages Function II

Lecture 18 1-12: Spider flip_pages Function III

Lecture 19 1-13: Wrap it Up

Lecture 20 1-14: Assignments 1-2

Lecture 21 1-15: Solutions 1-2

Lecture 22 1-16: Discussion on ROBOTSTXT_OBEY

Section 4: ___002 SCRAPE THE SECOND WEBSITE

Lecture 23 2-01: First Thoughts

Lecture 24 2-02: Solving the Problem

Lecture 25 2-03: Spider StartUp

Lecture 26 2-04: Locating Data

Lecture 27 2-05: Parse Function I

Lecture 28 2-06: Parse Function II

Lecture 29 2-07: start_requests Function

Lecture 30 2-08: flip_pages Function I

Lecture 31 2-09: flip_pages Function II

Lecture 32 2-10: Error Analysis

Section 5: ___003 SCRAPE THE THIRD WEBSITE

Lecture 33 3-01: Site Investigation I

Lecture 34 3-02: Site Investigation II

Lecture 35 3-03: Spider Fired

Lecture 36 3-04: Parse Function

Lecture 37 3-05: flip_pages Function

Lecture 38 3-06: FormRequest Spider Example

Lecture 39 3-07: Assignments

Lecture 40 3-08: Solutions 1-2

Lecture 41 3-09: Solution 3

Lecture 42 3-10: RECAP

Section 6: ___004 FINDING MY DREAM CAR

Lecture 43 4-01: Where are We?

Lecture 44 4-02: Installation of the Dataset

Lecture 45 4-03: Creation of the Carpools I

Lecture 46 4-04: Creation of the Carpools II

Lecture 47 4-05: Application of the Methodology (and the Results!)

Lecture 48 4-06: RECAP

Section 7: ___005 THE ADD-ONs

Lecture 49 5-01: Refinements of the Methodology

Lecture 50 5-02: How to run this??

Lecture 51 Wrap it Up

Lecture 52 Bonus Video

Programmers who want to turn their Data Science knowledge into a developer's skill to solve real world problems,Developers at any level who would make use of a data science project of practical use: Python car-advisor,Programmers, who have taken their first programming course with success and would like to proceed to next level in Data Science,Data Science practitioners and enthusiasts, who want to tackle a real world challange of practial use