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SQL for Data Science Capstone Project

Approx. 35 hours to complete

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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

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

Intermediate

Course 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.

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.

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
Present 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 approach

Pros 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

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