Beginning Data Science with Python

資料科學是一個跨學科領域,結合統計分析、程式設計和領域知識,以提取有價值的洞察並做出數據驅動的決策。由於其簡單性、多功能性和豐富的庫生態系統,Python已成為最受歡迎的資料科學程式設計語言之一。無論您是一個完全的初學者還是一個有經驗的程式設計師,想要深入探索資料科學領域,學習Python都是必不可少的第一步。

在這課程中,我們將使用Python探索資料科學的基礎知識。我們將涵蓋資料操作、探索性資料分析、資料可視化和機器學習等關鍵概念。通過實際例子和實踐練習,您將建立Python程式設計的扎實基礎,並學習如何應用於現實世界的資料問題上。在閱讀完本指南後,您將具備開展資料科學之旅所需的知識和技能,並能夠運用Python進行數據分析和預測建模。現在,讓我們踏上這個令人興奮的冒險,開始我們的Python資料科學之旅吧!

You'll Learn

模组一  

Intalling Python

  • Python on Windows
  • Python on Mac OS

Working with variables and data

  • Naming and using variables
  • Numbers, strings and boolean
  • Stripping whitespaces
  • Concatenating strings
  • Stripping whitespaces
  • Tabs and newlines
  • Integers and floats
  • Writing comments
  • Strings manipulation

Working with Lists and Tuples

  • Accessing Elements in a List
  • Working with Elements (appending, adding, sorting, deleting )
  • For Loop
  • Looping through an entire list
  • Slicing and looping through a slice
  • Copying a list
  • Organizing a list
  • List comprehension
  • Vertical summation
  • Defining a tuple
  • Tuples and Lists conversion
  • Looping through a Tuple

If and Conditional Statements

  • Various conditional tests ( equality and inequality checking )
  • Conditional testing on a list
  • Boolean Expressions
  • if-else , if-elif-else
  • Using if statement with multiple lists
  • Nesting Blocks
  • While Loop using a list
  • While Loop using a flag
  • Flow control with break statement
  • Flow control with continue statement

Dictionaries

  • Accessing values in a Dictionary
  • Adding new key-value pairs
  • Looping through all key-value pairs
  • Looping through all values in a dictionary

Getting user Input

  • Using input() function
  • Handling numberical input

Functions

  • Defining a function
  • Arguments and parameters
  • Working with positional arguments
  • Working with keyword arguments
  • Setting arguments' default values
  • Returning result from a function

Working with Modules

  • Storing functions in a module file
  • Importing an entire module
  • Importing individual functions

Using Python's standard modules

  • Math module
  • Datetime module
  • Random module
  • OS module

Working with files

  • Reading data from a txt or csv files
  • Merging and working data from a file
  • Writing to a file

Errors handling

  • Handling error using Exception
  • The try-except blocks
  • The else block
  • Displaying errors messages


課程班別
 
PYD4083 - 廣東話 22 Aug enrol
 
PYD4082 - 廣東話 28 Aug enrol
 
PYD4093 - 廣東話 04 Sep enrol
 
PYD4091 - 廣東話 20 Sep enrol
 
PYD4101 - 廣東話 05 Oct enrol
相關課程
  Beginning Data Science with Python
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  Python for Data Analysis
  Stock Trading Analysis with Python
  Python Programming x ChatGPT/GPT

模组二  

Data Preparation and loading

  • Data loading using Pandas
  • Working with problematic data
  • Dealing with big datasets

Data Processing with Pandas

  • Introduction to Data Structures
  • Series / DataFrame / Index Objects
  • Viewing and selecting data
  • Statistical and histogramming operations
  • String methods
  • Concatenating / joining / appending data
  • Arithmetic methods
  • Operations between DataFrame and Series
  • Function application and mapping
  • Sorting and Ranking
  • Doing common Excel tasks in Pandas
  • Doing Pivot Table in Pandas

Data Processing with Numpy

  • Array Creation - N-dimensions
  • Printing Arrays
  • Numpy DataTypes and conversion
  • numpy.ndarray methods
  • Basic arrays elementwise operations
  • Matrix product using dot function
  • Universal functions
  • Indexing, slicing and iterating
  • Shape manipulation
  • Copies and views
  • Data Processing Using Arrays

Data Visualization

  • pyPlot Basics
  • Knowing different chart elements
  • Charting with Pandas
  • Plotting a single interactive chart
  • Saving your charts
  • Subplots
  • Plotting multiple charts

Machine Learning

  • Supervised and unsupervised Learning
  • Training set and testing set
  • Dimensionality reduction
  • The PCA Decomposition
  • K-Nearest Neighbours Classifier
  • Linear Regression
  • Polynominal interpolation and curve fitting
  • Support Vector Machine