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Limited time offer icon TOPTALENT LEARNING CREDITS YEAR END SALE!!

Using Data Science Tools in Python

Enroll yourself in the Using Data Science Tools in Python course and lab to gain hands-on expertise on using Python for data science. Python’s robust libraries have given data scientists the ability to load, analyze, shape, clean, and visualize data in easy use, yet powerful, ways. The course and lab provide the skills you need to successfully use these key libraries to extract useful insights from data, and as a result, provide great value to the business.
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Test Prep
60+ Pre Assessment Questions | 60+ Post Assessment Questions |
Features
33+ LiveLab | 4+ Video tutorials | 13+ Minutes

Why choose TOPTALENT?

Outline

Lessons 1:
Introduction

  • Course Description
  • How To Use This Course
  • Course-Specific Technical Requirements

Lessons 2:
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
  • Summary

Lessons 3:
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
  • Summary

Lessons 4:
Transforming Data with NumPy

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

Lessons 5:
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
  • Summary

Lessons 6:
Transforming and Visualizing Data with pandas

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

Lessons 7:
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
  • Summary

Appendix A: Scraping Web Data Using Beautiful Soup

  • Topic A: Scrape Web Pages