Data Analysis and Visualization with Python

Boosting your data science career with a crash course on data visualization in Python.

3 Units
Buy $14.99

Boosting Your Data Science Career

This class is a comprehensive introduction to data visualization with Python. It introduces how to work with different data structures in Python and covers the most popular data analytics and visualization modules, including numpy, scipy, pandas, matplotlib, and seaborn. We use Ipython notebook to demonstrate the results of codes and change codes interactively throughout the class.

  • PROJECT ORIENTED

    We don’t just teach the syntax/grammar of Python like all the other free resources on the Internet. Students will learn how to solve a real data science problem using Python skills.

  • ACCELERATED ADMISSIONS

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  • ENGAGING COMMUNITY

    An active community of 2000+ working data scientists, like-minded peers, and data experts across various fields

Course curriculum

Unit1
Introduction to Numpy & Scipy
26 Sessions | 3 hours

  • NumPy Overview

  • Ndarray

  • Creating Array

  • Exercise 1

  • Spawning Arrays

  • Subscripting & Slicing

  • Shape

  • Exercise 3

  • Operations

  • Broadcasting

  • Logical Operators

  • Aggregating Boolean Arrays

  • Fancy Indexing

  • Exercise 4

  • Tensor

  • Vectorizing Function in NumPy

  • Matrix & Linear Algebra

  • Exercise 5

  • Random Sampling

  • Birthday Problems

  • SciPy Overview

  • Statistical Functions

  • Hypothesis Test

  • One Sample T-test

  • Two Sample T-test

  • ANOVA
Unit2
Data Manipulations with Pandas
18 Sessions | 2 hours

  • Overview

  • Series

  • Data Frame

  • Exercise 1

  • I/O tools

  • Exercise 2

  • Data Manipulation

  • Exercise 3

  • Sort & Merge

  • Exercise 4

  • Selection & Filter

  • Removing Data

  • Handling Missing Data

  • Exercise 5

  • Handling Missing Data - Dropna

  • Handling Missing Data - Fillna

  • Handling Missing Data- Interpolate

  • Grouping & Aggregating
Unit3
Data Visualization in the NumPy Stack
14 Sessions | 2 hours

  • Overview

  • Exercise 1

  • Histogram

  • Exercise 2

  • Scatter Plot

  • Exercise 3

  • Bar Plot

  • Data Manipulation

  • Exercise 4

  • Box Plot

  • Exercise 5

  • Seaborn

  • Exercise 6

  • Plotly

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