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Data Analysis and Interpretation Capstone

Approx. 8 hours to complete

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Course Summary

This course focuses on the practical application of data analysis techniques using real-world data sets. Students will learn to use data to solve problems and make informed decisions.

Key Learning Points

Gain practical skills in data analysis
Learn to work with real-world data sets
Develop the ability to make data-driven decisions

Learning Outcomes

Gain proficiency in data analysis techniques
Learn to work with real-world data sets
Develop the ability to make data-driven decisions

Prerequisites or good to have knowledge before taking this course

Basic understanding of statistics and data analysis
Familiarity with programming concepts

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced
Project-based

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Applied Data Science with Python
Data Analysis and Presentation Skills: the PwC Approach

Related Education Paths

Related Books

Description

The Capstone project will allow you to continue to apply and refine the data analytic techniques learned from the previous courses in the Specialization to address an important issue in society. You will use real world data to complete a project with our industry and academic partners. For example, you can work with our industry partner, DRIVENDATA, to help them solve some of the world's biggest social challenges! DRIVENDATA at www.drivendata.org, is committed to bringing cutting-edge practices in data science and crowdsourcing to some of the world's biggest social challenges and the organizations taking them on.

Or, you can work with our other industry partner, The Connection (www.theconnectioninc.org) to help them better understand recidivism risk for people on parole seeking substance use treatment. For more than 40 years, The Connection has been one of Connecticut’s leading private, nonprofit human service and community development agencies. Each month, thousands of people are assisted by The Connection’s diverse behavioral health, family support and community justice programs. The Connection’s Institute for Innovative Practice was created in 2010 to bridge the gap between researchers and practitioners in the behavioral health and criminal justice fields with the goal of developing maximally effective, evidence-based treatment programs. A major component of the Capstone project is for you to be able to choose the information from your analyses that best conveys results and implications, and to tell a compelling story with this information. By the end of the course, you will have a professional quality report of your findings that can be shown to colleagues and potential employers to demonstrate the skills you learned by completing the Specialization.

Outline

Module 1. Identify Your Data and Research Question
Introduction to the Capstone Course
Overview of Each Module and Assignments
Your Capstone Project
Writing Your Report: Title and Introduction
Writing Your Report: What to Avoid
Read Me First
Industry Partner: DRIVENDATA
Industry Partner: The Connection
About the Assignments
Data Sets and Codebooks
Creating a Final Report
SAS and python code for sample final report
SAS Data Sets
Sample Final Report Data Set

Module 2. Data Management
Writing Your Report: Methods

Module 3. Exploratory Data Analysis
Writing Your Report: Results

Complete Your Final Report
Writing Your Report: Conclusions and Limitations
Final Assignment Grading Rubric

Summary of User Reviews

The Data Analysis Capstone course on Coursera has received positive reviews from many users. Learners have praised the course for its in-depth coverage of data analysis concepts and real-world projects that allow them to hone their skills. The course has a high overall rating and is well-regarded by many students.

Key Aspect Users Liked About This Course

The practical projects are a key aspect of the course that many users appreciate. They provide a hands-on learning experience that allows students to apply the concepts they learn in class to real-world scenarios.

Pros from User Reviews

The course covers a wide range of data analysis topics in depth.
The instructors are knowledgeable and engaging.
The course projects are well-designed and provide practical experience.
The course is self-paced, which allows learners to work at their own pace.
The course is affordable and accessible to learners from all backgrounds.

Cons from User Reviews

Some users have reported technical issues with the platform.
The course can be challenging for learners who are new to data analysis.
The workload can be heavy at times.
The course could benefit from more interactive elements.
Some users have reported that the course content is outdated.

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