SQL for Data Science Capstone Project

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SQL for Data Science Capstone Project

This course is part of Learn SQL Basics for Data Science Specialization

Instructor: Don Noxon

42,791 already enrolled

Included with

4 modules

Gain insight into a topic and learn the fundamentals.

259 reviews

Intermediate level

Some related experience required

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

259 reviews

Intermediate level

Some related experience required

4 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Develop a project proposal and select your data
Perform descriptive statistics as part of your exploratory analysis
Develop metrics and perform advanced techniques in SQL
Present your findings and make recommendations

Skills you'll gain

Category: Statistical Analysis
Category: Descriptive Statistics
Category: Data Presentation
Category: Proposal Writing
Category: SQL
Category: Exploratory Data Analysis
Category: Peer Review
Category: Data Modeling
Category: Target Audience
Category: Analytical Skills
Category: Presentations
Category: Data Manipulation
Category: Data Science
Category: Business Analytics
Category: Data Analysis
Category: Data Storytelling

Details to know

Shareable certificate

Add to your LinkedIn profile

Taught in English

Build your subject-matter expertise

This course is part of the Learn SQL Basics for Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

Data science is a dynamic and growing career field that demands knowledge and skills-based in SQL to be successful. This course is designed to provide you with a solid foundation in applying SQL skills to analyze data and solve real business problems.

Whether you have successfully completed the other courses in the Learn SQL Basics for Data Science Specialization or are taking just this course, this project is your chance to apply the knowledge and skills you have acquired to practice important SQL querying and solve problems with data. You will participate in your own personal or professional journey to create a portfolio-worthy piece from start to finish. You will choose a dataset and develop a project proposal. You will explore your data and perform some initial statistics you have learned through this specialization. You will uncover analytics for qualitative data and consider new metrics that make sense from the patterns that surface in your analysis. You will put all of your work together in the form of a presentation where you will tell the story of your findings. Along the way, you will receive feedback through the peer-review process. This community of fellow learners will provide additional input to help you refine your approach to data analysis with SQL and present your findings to clients and management.

In this first milestone, you will select your client and import your dataset. You will begin to explore your data to understand it and make assumptions about your data. You will draft a project proposal to act as a guide as you explore your data and prove or disprove your hypotheses.

What's included

12 videos4 readings1 peer review2 discussion prompts

12 videosTotal 48 minutes

Course Introduction and Welcome3 minutes
Milestone 1 Introduction1 minute
The Proposal Process4 minutes
Import of Elon Musk Data5 minutes
Initial Feature Exploration / Hypotheses8 minutes
Entity Relationship Diagram (ERD) for Analysis3 minutes
Data Models, Part 1: Thinking About Your Data6 minutes
Data Models, Part 2: The Evolution of Data Models4 minutes
Data Models, Part 3: Relational vs. Transactional Models6 minutes
SQL in Notebooks4 minutes
Import Data3 minutes
Introduction of Data of Unknown Quality2 minutes

4 readingsTotal 70 minutes

A Note from UC Davis10 minutes
Choose Your Client/Dataset30 minutes
Connecting to Mode Analytics20 minutes
Welcome to Peer Review Assignments!10 minutes

1 peer reviewTotal 420 minutes

Milestone 1: Project Proposal and Data Selection/Preparation420 minutes

2 discussion promptsTotal 20 minutes

Your Learning Goals10 minutes
Questions For Your Peers10 minutes

In this milestone, you will start to execute your project proposal. You will start looking at your data and perform initial statistic models to explore your data and determine what you have available to you.

What's included

7 videos1 reading1 peer review1 discussion prompt

7 videosTotal 39 minutes

Milestone 2 Introduction1 minute
Importance of Understanding Your Data2 minutes
Foundational Stats in SQL/Sheets9 minutes
Pandas Teach on Stats6 minutes
Visualization with raw graphics.io6 minutes
Impact of Findings on Hypotheses6 minutes
Statistics Refresher (Optional)9 minutes

1 readingTotal 20 minutes

Additional Resources20 minutes

1 peer reviewTotal 420 minutes

Milestone 2: Descriptive Stats420 minutes

1 discussion promptTotal 10 minutes

Questions For Your Peers10 minutes

In this milestone, you will go beyond the descriptive statistics you completed in the last milestone. This milestone is really about diving deeper to analyze your data, beyond descriptive stats. Maybe you need to analyze qualitative data or textual data to get a full picture.

What's included

5 videos1 peer review1 discussion prompt

In this milestone, you will present your findings. You will identify your audience and create a presentation tailored to them. You will be able to tell the story of analyses and make recommendations.

What's included

12 videos7 readings1 peer review2 discussion prompts

12 videosTotal 61 minutes

Milestone 4 Introduction2 minutes
Sample Output / Presentation7 minutes
Module Introduction1 minute
Working with Text Strings7 minutes
Working with Date and Time Strings5 minutes
Date and Time Strings Examples5 minutes
Case Statements7 minutes
Views7 minutes
Data Governance and Profiling6 minutes
Using SQL for Data Science, Part 16 minutes
Using SQL for Data Science, Part 26 minutes
Course Summary1 minute

7 readingsTotal 105 minutes

Resources on the Who, What, Why, and How20 minutes
Resources on Audience30 minutes
Dashboard and Storytelling with Data10 minutes
Finding the Story10 minutes
Prioritizing, Optimizing and Designing the Data Story10 minutes
Tell the Story of Your Data10 minutes
Additional SQL Resources to Explore15 minutes

1 peer reviewTotal 420 minutes

Milestone 4: Presenting Your Findings (Storytelling)420 minutes

2 discussion promptsTotal 20 minutes

Questions For Your Peers10 minutes
Reflections10 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Instructor ratings

(56 ratings)

Don Noxon

University of California, Davis

1 Course42,791 learners

Offered by

University of California, Davis

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5 stars
63.84%
4 stars
14.23%
3 stars
7.69%
2 stars
5.76%
1 star
8.46%

Showing 3 of 259

Reviewed on Jan 16, 2023

The course is supposed to evaluate SQL skills but unwillingly the learners have to use a lot of their Python skills. That would be my only complain.

Reviewed on Nov 24, 2021

This guided project was a nice end to the SQL Basics specialization.

Reviewed on Jul 25, 2022

Great Course. I explored the ability to make a data science project from start to end

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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