À propos de ce cours

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Dates limites flexibles
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Niveau intermédiaire

Some statistics is recommended and at least 2-years business experience.

Approx. 15 heures pour terminer
Anglais
Sous-titres : Anglais

Ce que vous allez apprendre

  • Validate and clean a dataset

  • Assess and create datasets to answer your questions

  • Solve problems using SQL

  • Build a simple testing framework to touch on AB Testing

Compétences que vous acquerrez

A/B TestingQuery StringData AnalysisPredictive AnalyticsSQL
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire

Some statistics is recommended and at least 2-years business experience.

Approx. 15 heures pour terminer
Anglais
Sous-titres : Anglais

Offert par

Logo Université de Californie à Davis

Université de Californie à Davis

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1

Semaine 1

5 heures pour terminer

Data of Unknown Quality

5 heures pour terminer
12 vidéos (Total 85 min), 3 lectures, 2 quiz
12 vidéos
Introduction of Data of Unknown Quality1 min
Introduction to the Course Dataset10 min
Error Codes (Solution)13 min
Flexible Data Formats6 min
Flexible Data Formats (Solution)5 min
Identifying Unreliable Data + Nulls3 min
Unreliable Data - Part 1 (Solution)4 min
Unreliable Data -Part 2 (Solution)7 min
Unreliable Data - Part 3 (Solution)8 min
Answering Ambiguous Questions3 min
Users Table (Solution)16 min
3 lectures
A Note From UC Davis10 min
Connecting to Mode Analytics20 min
Not Dumb Questions10 min
2 exercices pour s'entraîner
Are You Connected to Mode Analytics?5 min
Module 1 Quiz30 min
Semaine
2

Semaine 2

2 heures pour terminer

Creating Clean Datasets

2 heures pour terminer
10 vidéos (Total 53 min)
10 vidéos
Tools of the Trade: Coding Guide with Sublime Text (Optional)3 min
Data Types4 min
What is a Dependency?5 min
Create a View-Item Table2 min
Turn a Clean Query Into a Table (Activity/Solution)9 min
Hierarchy of Data2 min
Create User Info Table3 min
Create a User Snapshot Table (Activity/Solution)13 min
Partitions in Hive (Optional)5 min
4 exercices pour s'entraîner
Data Types (Quiz)10 min
Dependencies (Quiz)8 min
Turn a Clean Query Into a Table (Quiz)2 min
Module 2 Quiz30 min
Semaine
3

Semaine 3

3 heures pour terminer

SQL Problem Solving

3 heures pour terminer
11 vidéos (Total 64 min)
11 vidéos
Map Out Your Joins4 min
Test Queries vs Final Queries3 min
Example: Create an Aggregate Table with a Rolling Date Period2 min
Rolling Orders (Solution)10 min
Find Each User's Most Recently Viewed Page for an Email Campaign2 min
Review Windowing Functions3 min
Promo Email (Solution)11 min
Product Analysis4 min
Product Analysis (Solution)15 min
Coding with Style2 min
2 exercices pour s'entraîner
Reorder and Connect Tables10 min
Module 3 Quiz30 min
Semaine
4

Semaine 4

5 heures pour terminer

Case Study: AB Testing

5 heures pour terminer
10 vidéos (Total 72 min), 2 lectures, 2 quiz
10 vidéos
Statistics Refresher (Optional)8 min
Test Assignments8 min
Test Assignments (Solution)11 min
Create a New Metric5 min
Creating a New Metric (Solution)9 min
Analyze Results7 min
Analyzing Results (Solution)13 min
Peer Review Overview3 min
Course Summary1 min
2 lectures
Additional Thoughts for the Final Project5 min
Additional Practice and Reading (Optional)10 min
1 exercice pour s'entraîner
Prepared for the Final Project?10 min

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À propos du Spécialisation Learn SQL Basics for Data Science

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....
Learn SQL Basics for Data Science

Foire Aux Questions

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