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IBM

Analyzing Data with Python

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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 Data Sets

  • The Problem
  • Understanding the Data
  • Python Packages for Data Science
  • Importing and Exporting Data in Python
  • Getting Started Analyzing Data in Python
  • Accessing Databases with Python
  • Module Summary
  • Practice Quiz: Importing Data sets
  • Hands-on Lab: Importing Data sets
  • Graded Quiz: Importing Data sets

Module 2 – Data Wrangling

  • Pre-processing Data in Python
  • Dealing with Missing Values in Python
  • Data Formatting in Python
  • Data Normalization in Python
  • Binning in Python
  • Turning Categorical Variables into Quantitative Variables in Python
  • Hands-on Lab: Data Wrangling - Used Cars Pricing
  • Hands-on Lab: Data Wrangling - Laptop Pricing
  • Module Summary
  • Practice Quiz: Data Wrangling
  • Graded Quiz: Data Wrangling

Module 3 - Exploratory Data Analysis

  • Exploratory Data Analysis
  • Descriptive Statistics
  • GroupBy in Python
  • Correlation
  • Correlation - Statistics
  • Hands-on Lab: Exploratory Data Analysis - Laptop Pricing
  • Hands-on Lab: Exploratory Data Analysis - Used Car Pricing
  • Module Summary
  • Practice Quiz: Exploratory Data Analysis
  • Graded Quiz: Exploratory Data Analysis

Module 4 – Model Development

  • Model Development
  • Linear Regression and Multiple Linear Regression
  • Model Evaluation using Visualization
  • Polynomial Regression and Pipelines
  • Measures for In-Sample Evaluation
  • Prediction and Decision Making
  • Practice Quiz: Model Development
  • Hands-on Lab: Model Development - Used Car Pricing
  • Hands-on Lab: Model Development - Laptop Pricing
  • Module Summary
  • Graded Quiz: Model Development

Module 5 - Model Evaluation

  • Model Evaluation and Refinement
  • Overfitting, Underfitting, and Model Selection
  • Ridge Regression Introduction
  • Ridge Regression
  • Grid Search
  • Practice Quiz: Model Evaluation and Refinement
  • Hands-on Lab: Model Evaluation and Refinement - Used Cars Pricing
  • Hands-on Lab: Model Evaluation and Refinement - Laptop Pricing
  • Module Summary
  • Graded Quiz: Model Evaluation and Refinement

Module 6 - Final Assignment

  • Project Scenario
  • Hands-on Lab for Final Project - Data Analytics for House Pricing Data Set
  • Peer Review
  • Cheat Sheet: Data Analysis for Python
  • Final Exam Instructions
  • Final Exam
  • Course Rating and Feedback
  • Course Rating
  • Badge
  • Claim your badge here
  • Acknowledgments
  • Congrats and Next Steps
  • Thanks from the Course Team

Taught by

Joseph Santarcangelo

Reviews

3.2 rating, based on 4 Class Central reviews

4.6 rating at edX based on 101 ratings

Start your review of Analyzing Data with Python

  • The list of topics is very intiguing and also ambitious. However the course is quite short - about 6 hours should be enough to complete it. In consequence, the course does not offer deep knowledge. You should rather consider it as a presentation of some concepts, which need to be studied further somewhere else. However it serves as a nice introduction to data exploration, cleaning and analysis.

    As edX edition of the course did not offer access to Graded Review Questions, I've moved to CognitiveClass platform (by IBM) where the course is currently available for free including certificates, without any limitations, in the exactly same formula as edX edition.
  • Good concise content for using Python and its libraries to perform basic data analysis and machine learning.
    You can do the same course and learning path by IBM at https://cognitiveclass.ai/courses/data-analysis-python for free including the IBM certificate.
  • Jon Ingram
    This isn't a great interactive introduction to analysing data with Python. It is a decent lecture, I suppose, but the 'lab's are not interactive to any great extent, and the videos don't motivate you to actually go out and explore the dataset yourself.

    Thank you to the previous reviewer for mentioning that the full course (including the graded quizzes) is available for free on the CognitiveAI website (not one I've heard of before). It's just about bearable at a price of $0 -- I certainly wouldn't pay the $39 edX are asking for!
  • Anonymous
    This series of courses does not have engaging lectures, and the labs have many simple errors. Often, the labs use Python syntax that was not explained in the course lectures. The labs are mainly code that is already written, so I didn't feel I had enough chance to practice writing the code myself.

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