Python Real World Data Science Mega Project- Car Buyer App

Python Real World Data Science Mega Project: Car Buyer App, available at $174.99, has an average rating of 4.35, with 53 lectures, based on 20 reviews, and has 270 subscribers.

You will learn about 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 This course is ideal for individuals who are Programmers who want to turn their Data Science knowledge into a developers skill to solve real world problems or Developers at any level who would make use of a data science project of practical use: Python car-advisor or Programmers, who have taken their first programming course with success and would like to proceed to next level in Data Science or Data Science practitioners and enthusiasts, who want to tackle a real world challange of practial use It is particularly useful for Programmers who want to turn their Data Science knowledge into a developers skill to solve real world problems or Developers at any level who would make use of a data science project of practical use: Python car-advisor or Programmers, who have taken their first programming course with success and would like to proceed to next level in Data Science or Data Science practitioners and enthusiasts, who want to tackle a real world challange of practial use.

Enroll now: Python Real World Data Science Mega Project: Car Buyer App

Summary

Title: Python Real World Data Science Mega Project: Car Buyer App

Price: $174.99

Average Rating: 4.35

Number of Lectures: 53

Number of Published Lectures: 52

Number of Curriculum Items: 53

Number of Published Curriculum Objects: 52

Original Price: $174.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

Programmers who want to turn their Data Science knowledge into a developers 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

Target Audiences

Programmers who want to turn their Data Science knowledge into a developers 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

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

Course Curriculum

Chapter 1: Introduction

Lecture 1: Intro-01: Points to Ponder

Lecture 2: Intro-02: Notes for your Consideration

Lecture 3: Intro-03: Roadmap

Chapter 2: ___000 THE STRATEGY

Lecture 1: 0-01: Exploration of the Real-World

Lecture 2: 0-02: The Plan

Lecture 3: 0-03: Wrap it Up

Chapter 3: ___001 SCRAPE THE FIRST WEBSITE

Lecture 1: 1-01: Start up the Spider

Lecture 2: 1-02: Exploring the Website

Lecture 3: 1-03: Spider First Attempts

Lecture 4: 1-04: Spider Successful Run

Lecture 5: 1-05: Spider Response Validation

Lecture 6: 1-06: Spider Parse Function I

Lecture 7: 1-07: Spider Parse Function II

Lecture 8: 1-08: Spider Parse Function III

Lecture 9: 1-09: Spider Parse Function IV

Lecture 10: 1-10: Spider flip_pages Function I

Lecture 11: 1-11: Spider flip_pages Function II

Lecture 12: 1-12: Spider flip_pages Function III

Lecture 13: 1-13: Wrap it Up

Lecture 14: 1-14: Assignments 1-2

Lecture 15: 1-15: Solutions 1-2

Lecture 16: 1-16: Discussion on ROBOTSTXT_OBEY

Chapter 4: ___002 SCRAPE THE SECOND WEBSITE

Lecture 1: 2-01: First Thoughts

Lecture 2: 2-02: Solving the Problem

Lecture 3: 2-03: Spider StartUp

Lecture 4: 2-04: Locating Data

Lecture 5: 2-05: Parse Function I

Lecture 6: 2-06: Parse Function II

Lecture 7: 2-07: start_requests Function

Lecture 8: 2-08: flip_pages Function I

Lecture 9: 2-09: flip_pages Function II

Lecture 10: 2-10: Error Analysis

Chapter 5: ___003 SCRAPE THE THIRD WEBSITE

Lecture 1: 3-01: Site Investigation I

Lecture 2: 3-02: Site Investigation II

Lecture 3: 3-03: Spider Fired

Lecture 4: 3-04: Parse Function

Lecture 5: 3-05: flip_pages Function

Lecture 6: 3-06: FormRequest Spider Example

Lecture 7: 3-07: Assignments

Lecture 8: 3-08: Solutions 1-2

Lecture 9: 3-09: Solution 3

Lecture 10: 3-10: RECAP

Chapter 6: ___004 FINDING MY DREAM CAR

Lecture 1: 4-01: Where are We?

Lecture 2: 4-02: Installation of the Dataset

Lecture 3: 4-03: Creation of the Carpools I

Lecture 4: 4-04: Creation of the Carpools II

Lecture 5: 4-05: Application of the Methodology (and the Results!)

Lecture 6: 4-06: RECAP

Chapter 7: ___005 THE ADD-ONs

Lecture 1: 5-01: Refinements of the Methodology

Lecture 2: 5-02: How to run this??

Lecture 3: Wrap it Up

Lecture 4: Bonus Video

Instructors

Abdulkadir Guner
Educator / Programmer / Engineer

Rating Distribution

1 stars: 0 votes

2 stars: 0 votes

3 stars: 1 votes

4 stars: 7 votes

5 stars: 12 votes

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