Python for Data Analysis

Python for data analysis

SkillsFuture Credit Approved Course


If you’re going to work with big data, you’ll probably be using R or Python. And if you’re using Python, you’ll be definitely using Pandas and NumPy, the third-party packages designed specifically for data analysis. This Python for Data Analysis course provides an opportunity to learn about them.

Course Outline:

  1. Python Data Analysis Libraries
    • Data Analysis Components
    • Data Analysis Steps
    • Python Data Analysis Libraries
  2. Overview of Numpy
    • What is Numpy?
    • 1D and 2D Array
    • Array Arithmetics
    • Special Functions
    • Math Functions
    • Selecting and Slicing Array Elements
    • Filtering Array Elements
    • Transforming Array
    • Statistics
  3. Data Analysis with Pandas
    • Series
    • Data Frame
    • Selecting/Slicing Data
    • Import/Export Data – CSV, Excel, Internet
    • Filtering Data
    • Missing Data
    • Removing Duplicated Data
    • Joining Data from Different Sources
    • Transforming Data
    • Aggregating Data
    • Pandas Statistics
  4. Data Visualization with Matplotlib & Seaborn
    • Overview of Matplotlib & Seaborn
    • Plot Types
    • Plot Attributes
    • Object Oriented Plots
    • Time Series Plot
  5. Intro to Machine Learning with Scikit-Learn
    • Overview of Scikit-Learn
    • Supervised and Unsupervised Learning
    • Classification
    • Regression
    • Clustering
    • PCA

Students looking to learn Python 3 may want to look at our Python 3 Programming course