Data Science With Python

Python Data Science Course in Singapore

Python for Data Science Training Course

Course Start Date

Duration

02 days

Timing

9:30 am – 5:30 pm

Venue

#26-08A, International Plaza, 079903 (Near Tanjong Pagar MRT Station)

Target Student:

This course is designed for students who wish to expand their ability to extract knowledge from business data. The target student for this course understands the principles and benefits of data science and has used basic data-driven tools like Microsoft® Excel® and Structured Query Language (SQL) queries, but wants to take the next steps into more advanced applications of data science.

You will learn?

  • Set up a Python data science environment.
  • Manage and analyze data with NumPy arrays.
  • Manipulate and modify data with NumPy arrays.
  • Manage and analyze data with pandas DataFrames.
  • Manipulate, modify, and visualize data with pandas DataFrames.
  • Visualize data with Matplotlib and Seaborn.

Course prerequisites: 

Basic Python knowledge is not compulsory but recommended before joining this course. If you are new to programming, you may consider our Basic Python Programming Course first to have better training result. 

Python for Data Science Course Outline:

Lesson 1: Setting Up a Python Data Science Environment

  • Topic A: Select Python Data Science Tools
  • Topic B: Install Python Using Anaconda
  • Topic C: Set Up an Environment Using Jupyter Notebook

Lesson 2: Managing and Analyzing Data with NumPy

  • Topic A: Create NumPy Arrays
  • Topic B: Load and Save NumPy Data
  • Topic C: Analyze Data in NumPy Arrays

Lesson 3: Transforming Data with NumPy

  • Topic A: Manipulate Data in NumPy Arrays
  • Topic B: Modify Data in NumPy Arrays

Lesson 4: Managing and Analyzing Data with pandas

  • Topic A: Create Series and DataFrames
  • Topic B: Load and Save pandas Data
  • Topic C: Analyze Data in DataFrames
  • Topic D: Slice and Filter Data in DataFrames

Lesson 5: Transforming and Visualizing Data with pandas

  • Topic A: Manipulate Data in DataFrames
  • Topic B: Modify Data in DataFrames
  • Topic C: Plot DataFrame Data

Lesson 6: Visualizing Data with Matplotlib and Seaborn

  • Topic A: Create and Save Simple Line Plots
  • Topic B: Create Subplots
  • Topic C: Create Common Types of Plots
  • Topic D: Format Plots
  • Topic E: Streamline Plotting with Seaborn

Appendix A: Scraping Web Data Using Beautiful Soup

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