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.
제공자:
Learn SQL Basics for Data Science 특화 과정캘리포니아 대학교 데이비스 캠퍼스이 강좌에 대하여
최근 조회 28,857회
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 4번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
중급 단계
완료하는 데 약 35시간 필요
영어
자막: 영어
배울 내용
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
귀하가 습득할 기술
Presentation SkillsData AnalysisSQLcreating metricsExploratory Data Analysis
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 4개 강좌 중 4번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
중급 단계
완료하는 데 약 35시간 필요
영어
자막: 영어
제공자:
캘리포니아 대학교 데이비스 캠퍼스
UC Davis, one of the nation’s top-ranked research universities, is a global leader in agriculture, veterinary medicine, sustainability, environmental and biological sciences, and technology. With four colleges and six professional schools, UC Davis and its students and alumni are known for their academic excellence, meaningful public service and profound international impact.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 9시간 필요
Getting Started and Milestone 1: Project Proposal and Data Selection/Preparation
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.
완료하는 데 9시간 필요
12개 동영상 (총 48분), 4 개의 읽기 자료, 1 개의 테스트
12개의 동영상
Milestone 1 Introduction1m
The Proposal Process3m
Import of Elon Musk Data5m
Initial Feature Exploration / Hypotheses8m
Entity Relationship Diagram (ERD) for Analysis2m
Data Models, Part 1: Thinking About Your Data5m
Data Models, Part 2: The Evolution of Data Models3m
Data Models, Part 3: Relational vs. Transactional Models5m
SQL in Notebooks3m
Import Data2m
Introduction of Data of Unknown Quality1m
4개의 읽기 자료
A Note from UC Davis10m
Choose Your Client/Dataset30m
Connecting to Mode Analytics20m
Welcome to Peer Review Assignments!10m
완료하는 데 8시간 필요
Milestone 2: Descriptive Stats & Understanding Your Data
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.
완료하는 데 8시간 필요
7개 동영상 (총 39분), 1 개의 읽기 자료, 1 개의 테스트
7개의 동영상
Importance of Understanding Your Data2m
Foundational Stats in SQL/Sheets9m
Pandas Teach on Stats5m
Visualization with raw graphics.io6m
Impact of Findings on Hypotheses5m
Statistics Refresher (Optional)8m
1개의 읽기 자료
Additional Resources20m
완료하는 데 8시간 필요
Milestone 3: Beyond Descriptive Stats (Dive Deeper/Go Broader)
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.
완료하는 데 8시간 필요
5개 동영상 (총 28분)
5개의 동영상
TF-IDF for Word Frequency / Theme Analysis7m
Text Analysis of Elon Musk Tweets5m
Create a New Metric5m
Analyze Results7m
완료하는 데 10시간 필요
Milestone 4: Presenting Your Findings (Storytelling)
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.
완료하는 데 10시간 필요
12개 동영상 (총 61분), 7 개의 읽기 자료, 1 개의 테스트
12개의 동영상
Sample Output / Presentation7m
Module Introduction1m
Working with Text Strings7m
Working with Date and Time Strings5m
Date and Time Strings Examples5m
Case Statements7m
Views6m
Data Governance and Profiling5m
Using SQL for Data Science, Part 15m
Using SQL for Data Science, Part 26m
Course Summary57
7개의 읽기 자료
Resources on the Who, What, Why, and How20m
Resources on Audience30m
Dashboard and Storytelling with Data10m
Finding the Story10m
Prioritizing, Optimizing and Designing the Data Story10m
Tell the Story of Your Data10m
Additional SQL Resources to Explore15m
Learn SQL Basics for Data Science 특화 과정 정보
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, and more. These topics will prepare you to apply SQL creatively to analyze and explore data; demonstrate efficiency in writing queries; create data analysis datasets; conduct feature engineering, use SQL with other data analysis and machine learning toolsets; and use SQL with unstructured data sets.
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