Course Summary
This course covers SQL and data science concepts through a capstone project, providing hands-on experience with real-world datasets and preparing students for data-related job positions.Key Learning Points
- Learn SQL and data science concepts through a hands-on capstone project
- Work with real-world datasets to gain practical experience
- Prepare for data-related job positions
Job Positions & Salaries of people who have taken this course might have
- USA: $62,453
- India: ₹5,55,290
- Spain: €25,000
- USA: $62,453
- India: ₹5,55,290
- Spain: €25,000
- USA: $113,309
- India: ₹10,19,079
- Spain: €52,000
- USA: $62,453
- India: ₹5,55,290
- Spain: €25,000
- USA: $113,309
- India: ₹10,19,079
- Spain: €52,000
- USA: $76,821
- India: ₹6,84,247
- Spain: €29,000
Related Topics for further study
Learning Outcomes
- Gain a solid understanding of SQL and data science concepts
- Develop practical skills through working with real-world datasets
- Prepare for data-related job positions
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of SQL
- Familiarity with data science concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Project-based
Similar Courses
- Applied Data Science Capstone
- Data Science Methodology
Related Education Paths
Notable People in This Field
- Co-founder of Coursera
- Data Scientist and Founder of Fast Forward Labs
Related Books
Description
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.
Knowledge
- ​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
- P​resent your findings and make recommendations
Outline
- Getting Started and Milestone 1: Project Proposal and Data Selection/Preparation
- Course Introduction and Welcome
- Milestone 1 Introduction
- The Proposal Process
- Import of Elon Musk Data
- Initial Feature Exploration / Hypotheses
- Entity Relationship Diagram (ERD) for Analysis
- Data Models, Part 1: Thinking About Your Data
- Data Models, Part 2: The Evolution of Data Models
- Data Models, Part 3: Relational vs. Transactional Models
- SQL in Notebooks
- Import Data
- Introduction of Data of Unknown Quality
- A Note from UC Davis
- Choose Your Client/Dataset
- Connecting to Mode Analytics
- Welcome to Peer Review Assignments!
- Milestone 2: Descriptive Stats & Understanding Your Data
- Milestone 2 Introduction
- Importance of Understanding Your Data
- Foundational Stats in SQL/Sheets
- Pandas Teach on Stats
- Visualization with raw graphics.io
- Impact of Findings on Hypotheses
- Statistics Refresher (Optional)
- Additional Resources
- Milestone 3: Beyond Descriptive Stats (Dive Deeper/Go Broader)
- Milestone 3 Introduction
- TF-IDF for Word Frequency / Theme Analysis
- Text Analysis of Elon Musk Tweets
- Create a New Metric
- Analyze Results
- Milestone 4: Presenting Your Findings (Storytelling)
- Milestone 4 Introduction
- Sample Output / Presentation
- Module Introduction
- Working with Text Strings
- Working with Date and Time Strings
- Date and Time Strings Examples
- Case Statements
- Views
- Data Governance and Profiling
- Using SQL for Data Science, Part 1
- Using SQL for Data Science, Part 2
- Course Summary
- Resources on the Who, What, Why, and How
- Resources on Audience
- Dashboard and Storytelling with Data
- Finding the Story
- Prioritizing, Optimizing and Designing the Data Story
- Tell the Story of Your Data
- Additional SQL Resources to Explore
Summary of User Reviews
SQL Data Science Capstone on Coursera is a highly rated course that teaches SQL for data science. Users praised the practical approach of the course and how it helps them to apply their knowledge in real-world scenarios.Key Aspect Users Liked About This Course
Practical approachPros from User Reviews
- Hands-on learning experience
- Real-world projects and datasets
- Great instructors and peer community
- Good pace for beginners and intermediate learners
- Helpful feedback on assignments
Cons from User Reviews
- Some technical issues with the platform
- Limited coverage of advanced SQL topics
- Not enough focus on data visualization
- Some assignments could be more challenging
- Some users found the course too basic
Don Noxon
3.9 Raiting
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