I have completed Data Scientist in Python full track from Dataquest with 28 real world projects.This repository contains all projects,datsets used in course and notes.Step_1 to Step_8 is order of course track completeion.

I worked on Jupyter Notebooks and Notepad app for course notes on Windows laptop.
You can install Jupyter Notebook from here
Notepad app already avialable in Windows ,or you can use any app for making notes.

Repo have separate folder for projects where i have saved projects according to course and step track.

Project_1: Profitable app profilles for the APP and Google play markets
Project_2: Learn and install jupyter notebook
Project_3: Exploring hacker news posts

Total Projects:3

Project_4: Exploring ebay car sales data
Project_5: Visualizing earnings based on college majors
Project_6: Visualizing geder gap in college degrees
Project_7: Clean and analyze employee exit survey
Project_8: Analyze highschool data
Project_9: Star wars survey

Total Projects: 6

Step_3 have no projects.

Project_10: Analyze facebook data using SQL
Project_11: Answering business questions using SQL
Project_12: API and web scraping with reddit API
Project_13: API and web scraping with reddit API
Project_14: Popular data science questions

Total Projects: 5

Project_15: Investigating Fandago movie ratings
Project_16: Finding best market to advertise in
Project_17: Mobile app for lottery addiction
Project_18: Building spam filter with naive bays
Project_19:

Total Projects: 5

Project_20: Predicting car prices
Project_21: Predicting house sale prices
Project_22: Predicting bike rentals
Project_23:

Total projects: 4

Project_24: Digits classification
Project_25: Credit modeling
Project_26: Getting started with titanic survival prediction

Total projects: 3

Project_27: Spark installation and jupyter notebook integration

Total projects: 1

This folder contains datasets used in courses for data analysis practice. Datasets used in step_1
Datasets used in step_2
Datasets in step_3
Step_3 have no data sets to download.
Datasets used in step_4
Datasets used in step_5
Datasets used in step_6
Datasets used in step_7
Datasets used in step_8

Notes of all courses are avialbale either in text or jupyter notebook format.
Takeaway files are in pdf format which are very short and concise notes.

This course is more than enough for absolute beginners and good for intermediate Data Analytics practitioner.

If have any issue in understanding notes or struggling to grasp any topic , i am ready to offer help.