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Anlayizing Data with Python

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BeginnerCourse

Learn data analysis with Python in this beginner-friendly course, where you'll master essential skills like data visualization, utilizing tools such as Numpy and Pandas. Discover how to analyze datasets effectively and create insightful visualizations to convey your findings clearly. Dive into basic machine learning concepts to enhance your analytical capabilities. Elevate your Python proficiency by applying it practically in real-world data scenarios.

Language

  • English

Topic

  • Data Analysis

Skills You Will Learn

  • Data Analysis, Data Visualization, Numpy, Pandas, Machine Learning

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 5 weeks

Platform

  • edX

Last Update

  • January 10, 2025
About this Course

Learn to Analyze Data with Python

In this introductory course, learn how to analyze data using Python. You'll 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!

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!


Course 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

Instructors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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Rav Ahuja

Global Program Director, IBM Skills Network

Rav Ahuja is a Global Program Director at IBM. He leads growth strategy, curriculum creation, and partner programs for the IBM Skills Network. Rav co-founded Cognitive Class, an IBM led initiative to democratize skills for in demand technologies. He is based out of the IBM Canada Lab in Toronto and specializes in instructional solutions for AI, Data, Software Engineering and Cloud. Rav presents at events worldwide and has authored numerous papers, articles, books and courses on subjects in managing and analyzing data. Rav holds B. Eng. from McGill University and MBA from University of Western Ontario.

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Lakshmi Holla

Team Lead

I am Lakshmi, Team Lead for mentoring services at Skillup. I oversee a team of teaching assistants who provide comprehensive support, testing, and maintenance for learners pursuing Data Science, Data Engineering, and Professional Certificates on platforms like Coursera and edX.

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