Data Analysis Real World Use-cases Hands on Python (數據分析真實世界用例-Python)

Digital Institute of Hong KongData Analysis Real World Use-cases Hands on Python (數據分析真實世界用例-Python)
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Data Analysis Real World Use-cases Hands on Python (數據分析真實世界用例-Python)

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Description

The course explains Projects on  real Data and real-world Problems.  It shows and explains the full real-world Data. Starting with importing messy data, cleaning data, merging and concatenating data, grouping and aggregating data, Exploratory Data Analysis through to preparing and processing data for Statistics, Machine Learning and Data Presentation.

Course Outline

Module/Subject(s) Description of the Module/Subject
Intro to this course & course Benefits

1. Intro to this course
2. Utilize QnA of the course ( Golden Oppurtunity ) !
3. How to follow this course-Must Watch
4. Installation of Anaconda Navigator
5. Quick Summary of Jupyter Notebook
Project 1-->> Uber New York Data Analysis

1. Datasets & Resources
2. Collect data for Analysis
3. Data preparation for Uber Data Analysis
4. Analysing Trips of Uber
5. Analysing Monthly rides
6. Analyzing Demand of Ubers
7. Performing Cross Analysis
8. Perform Spatial Analysis on Demand of Ubers
9. Analysing Uber Pickups in Each month
10. Analysing Rush in New york City
11. Perform In-Depth Analysis of Uber Base Number
Project 2-->>  Hotel Booking Data Analysis

1. Datasets & Resources
2. Preparing our Data for Analysis
3. Perform Spatial Analysis on Guests Home-Town
4. How does price of hotel vary across year?
5. Analyzing Preference of Guests
6. Analyzing relationship between special requests and cancellation.
7. Analyzing most busy month
8. Analyzing more about Customers
9. Analyze more about Data
Project 3-->> Covid-19 Data Analysis

1. Datasets & Resources
2. Prepare your Data for the Analysis
3. Analysing Total cases, Deaths, Recovered & active cases
4. Perform EDA on Data
5. Analysing those countries that gets badly affected by Corona
6. Perform In-depth Analysis on Data
7. Automate Your Analysis
Project 4-->>Finance Data Analysis

1. Datasets & Resources
2. Perform Descriptive Analysis on data
3. Understanding Data & data-preprocessing
4. Analyze Education Status of customers
5. Analyze Account holder distribution
6. Automate your Analysis
7. Analyze Customers Behavior on the basis of various attributes
8. Perform Hypothesis on Data
Project 5-->> Amazon Customers Data Analysis

1. Datasets & Resources
2. How to Read Data from SQLite Database.
3. Perform Sentiment Analysis on Data.
4. How Amazon recommend product
5. Analyzing Feedback given by customers
6. Prepare our data for Analysis
7. Analyzing behaviour of customers

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