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'IT Support for Research' Workshop: Basic Python (Evening class)

Workshop/ Training/ Webinar

20220301-event_Basic-Python-evening

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 are interested in advanced machine learning. Students have basic programming concepts are welcome to join.



'IT Support for Research' Workshop: Basic Python 

(Evening class)

Date: 8 Mar (Tue), 15 Mar (Tue), 22 Mar (Tue), 29 Mar (Tue), 12 Apr (Tue)

Time: 18:00 – 20:30

Target Audience: RPg, TPg and Ug students

Pre-requisite: Basic programming concepts

Medium of Instruction: English

Course Outline:

Lesson 1

  1. Introduction to Jupyter IDE
  2. Introduction to Python
    1. Expressions
    2. Data types
    3. Arithmetic operations
    4. Control flows


Lesson 2

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

 

Lesson 3

  1. Python libraries for numerical computations and data analysis
    1. NumPy
      1. Indexing
      2. Arithmetic operations
      3. Concatenations
      4. Aggregations
      5. Sorting

 

Lesson 4

  1. Python libraries for numerical computations and data analysis
    1. Pandas
      1. Operations on data columns
      2. Handling missing values
      3. Pivot tables
      4. Working with text and time series
      5. File management
  2. Database management with Python
    1. MySQL
      1. Construct database and table/collection
      2. Query data from table/collection
      3. Insert, update and delete records/documents


Lesson 5

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

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