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Webinar for Researchers: Basic Python

Workshop/ Training/ Webinar

20210518-event-python-webinar

Summary

This workshop, consists of five online sessions, aims at helping participants to build a solid foundation in Python programming. Application of Python’s libraries in data manipulation and data acquisition, storage and visualization will be covered. This workshop is also a good preparation for participants who interest in advance machine learning.

 

Date: 18 May (Tue), 20 May (Thu), 25 May (Tue), 27 May (Thu), 1 Jun (Tue)

Time: 14:30 – 17:00

Pre-requisite: Basic programming concepts

Target Audience: Rpg, Tpg, Ug Students

Medium of Instruction: English

Course Outline:

(18 May) Lesson 1

  1. Introduction to Jupyter IDE
    • Magic commands
    • Useful shortcuts
  2. Introduction to Python
    • Expressions
    • Data types
    • Arithmetic operations
    • Control flows

 

(20 May) Lesson 2

  1. More about Python
    • Functions
    • String operations
    • Containers (list, tuple, set, dictionary)
    • Introduction to encoding
    • Manipulating dates and times (the datetime module)

 

(25 May) Lesson 3

  1. Python libraries for numerical computations and data analysis
    • NumPy
      • Indexing
      • Arithmetic operations
      • Concatenations
      • Aggregations
      • Sorting
    • Pandas
      • Operations on data columns
      • Handling missing values
      • Pivot tables
      • Working with text and time series
      • File management

 

(27 May) Lesson 4

  1. More about Python string: Regular Expression
    • Metacharacter
    • Quantifier
    • Group
  2. Web scraping
  3. Database management with Python
    • MySQL, MongoDB
      • Construct database and table/collection
      • Query data from table/collection
      • Insert, update and delete records/documents

 

(1 June) Lesson 5

  1. Visualization with Python libraries
    • Matplotlib
      • Formatting axes, titles, labels, annotations and color bar
      • Plotting line, bar, scatter, histogram, boxplot, 3d plot
    • A higher-level approach: Seaborn
      • Plotting heatmap, violin plot, join plot

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