Course
Data Science
Continuing Education

Data Analysis with Python

15 Hours

Estimated learning time

Self-Paced

Progress at your own speed

Popular course

A popular course among students

About the Course

Description

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models.

Topics covered include:

  • collecting and importing data
  • cleaning, preparing & formatting data
  • data frame manipulation
  • summarizing data
  • building machine learning regression models
  • model refinement
  • creating data pipelines

You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them.

In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions.

If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge.

This Course is part of a program

You can only buy it along with program.

Sections

Schedule

Asynchronous

Delivery method

Online

Deliverables

  • 0 Credits

    Academic Excellence

    Earn necessary number of credit hours for completing this content

  • Hone Important Skills

    Total Upgrade

    Such as Python Programming, Machine Learning, Data Analysis, Regression, Exploratory Data Analysis, Modeling, Computer Programming, Data Visualization, Linearity, Probability & Statistics, General Statistics, Machine Learning Algorithms, Plot (Graphics), Analysis