- Level Foundation
- المدة 7 ساعات hours
- الطبع بواسطة Rice University
-
Offered by
عن
The Business Statistics and Analysis Capstone is an opportunity to apply various skills developed across the four courses in the specialization to a real life data. The Capstone, in collaboration with an industry partner uses publicly available "Housing Data' to pose various questions typically a client would pose to a data analyst. Your job is to do the relevant statistical analysis and report your findings in response to the questions in a way that anyone can understand. Please remember that this is a Capstone, and has a degree of difficulty/ambiguity higher than the previous four courses. The aim being to mimic a real life application as close as possible.الوحدات
Lesson 1 - A Summary of the Four Courses in the Specialization
1
Videos
- A Summary of the Four Courses in the Specialization
2
Readings
- Lesson 1, Slides
- Pre-Course Survey
Lesson 2 - Introducing the Capstone
1
Videos
- Introducing the Capstone
1
Readings
- Lesson 2, Slides
Lesson 3 - A Conversation with Garfield Fisher, the industry partner for the Capstone
2
Videos
- A Conversation with Garfield Fisher, the industry partner for the Capstone
- Q&A with Garfield Fisher
Lesson 4 - Data for the Capstone Project
1
Videos
- Data for the Capstone Project
3
Readings
- The URL to download data for the Capstone Project
- List of variables to be used in Capstone
- Lesson 4, Slides
Lesson 5 - Merging and Cleaning Data for the Capstone
1
Videos
- Merging and Cleaning Data for the Capstone
1
Readings
- Lesson 5, Slides
Capstone: An Introduction: Quiz
1
Assignment
- Capstone Quiz 1: Data in Excel
Lesson 1 - Introducing Assignment 1: Differences in Market Value of Housing Units
1
Videos
- Introducing Assignment 1: Differences in Market Value of Housing Units
1
Readings
- Lesson 1, Slides
Lesson 2 - Introducing Assignment 2: Fair Market Rent of Housing Units
1
Videos
- Introducing Assignment 2: Fair Market Rent of Housing Units
1
Readings
- Lesson 2, Slides
Week 2 Assessments
2
Assignment
- Week 2 Assessment 1
- Week 2 Assessment 2
3
Readings
- Week 2 Assessment 1 Sample Solution
- Week 2 Assessment 2 Instructions
- Week 2 Assessment 2 Sample Solution
Lesson 1 - Introducing Assignment 3: A Model for Market Value of Housing Units
1
Videos
- Introducing Assignment 3: A Model for Market Value of Housing Units
1
Readings
- Lesson 1, Slides
Week 3 Assessments
1
Peer Review
- Week 3 Assessment
1
Readings
- Week 3 Assessment Sample Solution
Lesson 1 - Introducing Assignment 4: Building a Predictive Model for Market Value of Housing Units
1
Videos
- Introducing Assignment 4: Building a Predictive Model for Market Value of Housing Units
1
Readings
- Lesson 1, Slides
Week 4 Assessment
1
Peer Review
- Week 4 Assessment
2
Readings
- Week 4 Assessment Sample Solution
- Post-Course Survey
Auto Summary
Dive into the "Business Statistics and Analysis Capstone" to culminate your learning journey in Data Science & AI with a hands-on, real-world project. Guided by Coursera, this advanced course challenges you to apply statistical analysis skills to real-life data sets, specifically focusing on publicly available 'Housing Data.' Your task is to address complex questions that a client might pose to a data analyst, demonstrating your ability to conduct thorough statistical analyses and present understandable findings. This capstone project is designed to simulate real-world ambiguity and complexity, providing a robust learning experience that builds on the foundational knowledge from the previous four courses in the specialization. Over an estimated 420 hours, you will refine your expertise and showcase your capabilities in a professional context. The course offers flexible subscription options including Starter, Professional, and Paid plans, catering to various learning needs and budgets. Ideal for those at the foundation level, this capstone project is perfect for aspiring data analysts seeking to solidify their skills and gain practical experience in business statistics and analysis. Enroll now to elevate your data science proficiency and prepare for real-world challenges.

Sharad Borle