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
43,683 already enrolled
Included with
263 reviews
263 reviews
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
- Database Design
- Performance Metric
- Analytical Skills
- Statistical Analysis
- SQL
- Data Presentation
- Exploratory Data Analysis
- Data Analysis
- Peer Review
- Text Mining
- Data Science
- Data Import/Export
- Target Audience
- Data Modeling
- Business Analytics
- Data Storytelling
- Descriptive Analytics
- Business Metrics
- Presentations
- Descriptive Statistics
Details to know
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Build your subject-matter expertise
- 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 videos•Total 48 minutes
- Course Introduction and Welcome•3 minutes
- Milestone 1 Introduction•1 minute
- The Proposal Process•4 minutes
- Import of Elon Musk Data•5 minutes
- Initial Feature Exploration / Hypotheses•8 minutes
- Entity Relationship Diagram (ERD) for Analysis•3 minutes
- Data Models, Part 1: Thinking About Your Data•6 minutes
- Data Models, Part 2: The Evolution of Data Models•4 minutes
- Data Models, Part 3: Relational vs. Transactional Models•6 minutes
- SQL in Notebooks•4 minutes
- Import Data•3 minutes
- Introduction of Data of Unknown Quality•2 minutes
4 readings•Total 70 minutes
- A Note from UC Davis•10 minutes
- Choose Your Client/Dataset•30 minutes
- Connecting to Mode Analytics•20 minutes
- Welcome to Peer Review Assignments!•10 minutes
1 peer review•Total 420 minutes
- Milestone 1: Project Proposal and Data Selection/Preparation•420 minutes
2 discussion prompts•Total 20 minutes
- Your Learning Goals•10 minutes
- Questions For Your Peers•10 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 videos•Total 39 minutes
- Milestone 2 Introduction•1 minute
- Importance of Understanding Your Data•2 minutes
- Foundational Stats in SQL/Sheets•9 minutes
- Pandas Teach on Stats•6 minutes
- Visualization with raw graphics.io•6 minutes
- Impact of Findings on Hypotheses•6 minutes
- Statistics Refresher (Optional)•9 minutes
1 reading•Total 20 minutes
- Additional Resources•20 minutes
1 peer review•Total 420 minutes
- Milestone 2: Descriptive Stats•420 minutes
1 discussion prompt•Total 10 minutes
- Questions For Your Peers•10 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
5 videos•Total 28 minutes
- Milestone 3 Introduction•1 minute
- TF-IDF for Word Frequency / Theme Analysis•8 minutes
- Text Analysis of Elon Musk Tweets•6 minutes
- Create a New Metric•6 minutes
- Analyze Results•7 minutes
1 peer review•Total 420 minutes
- Milestone 3: Beyond Descriptive Stats•420 minutes
1 discussion prompt•Total 10 minutes
- Questions For Your Peers•10 minutes
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 videos•Total 61 minutes
- Milestone 4 Introduction•2 minutes
- Sample Output / Presentation•7 minutes
- Module Introduction•1 minute
- Working with Text Strings•7 minutes
- Working with Date and Time Strings•5 minutes
- Date and Time Strings Examples•5 minutes
- Case Statements•7 minutes
- Views•7 minutes
- Data Governance and Profiling•6 minutes
- Using SQL for Data Science, Part 1•6 minutes
- Using SQL for Data Science, Part 2•6 minutes
- Course Summary•1 minute
7 readings•Total 105 minutes
- Resources on the Who, What, Why, and How•20 minutes
- Resources on Audience•30 minutes
- Dashboard and Storytelling with Data•10 minutes
- Finding the Story•10 minutes
- Prioritizing, Optimizing and Designing the Data Story•10 minutes
- Tell the Story of Your Data•10 minutes
- Additional SQL Resources to Explore•15 minutes
1 peer review•Total 420 minutes
- Milestone 4: Presenting Your Findings (Storytelling)•420 minutes
2 discussion prompts•Total 20 minutes
- Questions For Your Peers•10 minutes
- Reflections•10 minutes
Earn a career certificate
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University of California, Davis
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University of California, Davis
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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 Jul 12, 2025
It is good course for people seeking a career in Dat Science
Reviewed on Nov 24, 2021
This guided project was a nice end to the SQL Basics specialization.
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