YoVDO

Analyzing Data with Python

Offered By: IBM via edX

Tags

Data Analysis Courses Programming Languages Courses Python Courses

Course Description

Overview

Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!

LEARN TO ANALYZE DATA WITH PYTHON

Learn how to analyze data using Python in this introductory course. You will go from understanding the basics of Python to exploring many different types of data through lecture, hands-on labs, and assignments. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more!


Syllabus

Module 1 - Importing Datasets

  • Learning Objectives
  • Understanding the Domain
  • Understanding the Dataset
  • Python package for data science
  • Importing and Exporting Data in Python
  • Basic Insights from Datasets

Module 2 - Cleaning and Preparing the Data

  • Identify and Handle Missing Values
  • Data Formatting
  • Data Normalization Sets
  • Binning
  • Indicator variables

Module 3 - Summarizing the Data Frame

  • Descriptive Statistics
  • Basic of Grouping
  • ANOVA
  • Correlation
  • More on Correlation

Module 4 - Model Development

  • Simple and Multiple Linear Regression
  • Model EvaluationUsingVisualization
  • Polynomial Regression and Pipelines
  • R-squared and MSE for In-Sample Evaluation
  • Prediction and Decision Making

Module 5 - Model Evaluation

  • Model Evaluation
  • Over-fitting, Under-fitting and Model Selection
  • Ridge Regression
  • Grid Search
  • Model Refinement

Taught by

Joseph Santarcangelo

Tags

Related Courses

Social Network Analysis
University of Michigan via Coursera
Intro to Algorithms
Udacity
Data Analysis
Johns Hopkins University via Coursera
Computing for Data Analysis
Johns Hopkins University via Coursera
Health in Numbers: Quantitative Methods in Clinical & Public Health Research
Harvard University via edX