CCNA 200-301 Pearson uCertify Network Simulator
Cisco 200-301-SIMULATOR.AB1
CCNA 200-301 Pearson uCertify Network Simulator
ISBN: 978-1-61691-837-8Cisco 200-301-SIMULATOR.AB1
SQL for Data Scientists
(SQL-DS.AE1) / ISBN : 978-1-64459-365-3
This course includes
Lessons
TestPrep
Hands-On Labs
AI Tutor (Add-on)
7
Review
About This Course
Get a hands-on experience in SQL with uCertify’s course SQL for Data Scientists, which is designed to be a learning resource for anyone who wants to become (or who already is) a data analyst or data scientist. It teaches the ability to pull data from databases to build their own datasets without having to rely on others in the organization to query the source system and transform it into flat files (or spreadsheets) for them.
Skills You’ll Get
Get the support you need. Enroll in our Instructor-Led Course.
Interactive Lessons
15+ Interactive Lessons | 155+ Exercises | 99+ Flashcards | 99+ Glossary of terms
Gamified TestPrep
57+ Pre Assessment Questions | 57+ Post Assessment Questions |
Hands-On Labs
33+ LiveLab | 33+ Video tutorials | 47+ Minutes
1
Introduction
- Who This Course Is For?
- Why You Should Learn SQL if You Want to Be a Data Scientist?
- Conventions
2
Data Sources
- Data Sources
- Tools for Connecting to Data Sources and Editing SQL
- Relational Databases
- Dimensional Data Warehouses
- Asking Questions About the Data Source
- Introduction to the Farmer's Market Database
- A Note on Machine Learning Dataset Terminology
- Exercises
3
The SELECT Statement
- The SELECT Statement
- The Fundamental Syntax Structure of a SELECT Query
- Selecting Columns and Limiting the Number of Rows Returned
- The ORDER BY Clause: Sorting Results
- Introduction to Simple Inline Calculations
- More Inline Calculation Examples: Rounding
- More Inline Calculation Examples: Concatenating Strings
- Evaluating Query Output
- SELECT Statement Summary
- Exercises Using the Included Database
4
The WHERE Clause
- The WHERE Clause
- Filtering SELECT Statement Results
- Filtering on Multiple Conditions
- Multi-Column Conditional Filtering
- More Ways to Filter
- Filtering Using Subqueries
- Exercises Using the Included Database
5
CASE Statements
- CASE Statement Syntax
- Creating Binary Flags Using CASE
- Grouping or Binning Continuous Values Using CASE
- Categorical Encoding Using CASE
- CASE Statement Summary
- Exercises Using the Included Database
6
SQL JOINs
- Database Relationships and SQL JOINs
- A Common Pitfall when Filtering Joined Data
- JOINs with More than Two Tables
- Exercises Using the Included Database
7
Aggregating Results for Analysis
- GROUP BY Syntax
- Displaying Group Summaries
- Performing Calculations Inside Aggregate Functions
- MIN and MAX
- COUNT and COUNT DISTINCT
- Average
- Filtering with HAVING
- CASE Statements Inside Aggregate Functions
- Exercises Using the Included Database
8
Window Functions and Subqueries
- ROW NUMBER
- RANK and DENSE RANK
- NTILE
- Aggregate Window Functions
- LAG and LEAD
- Exercises Using the Included Database
9
Date and Time Functions
- Setting datetime Field Values
- EXTRACT and DATE_PART
- DATE_ADD and DATE_SUB
- DATEDIFF
- TIMESTAMPDIFF
- Date Functions in Aggregate Summaries and Window Functions
- Exercises
10
Exploratory Data Analysis with SQL
- Demonstrating Exploratory Data Analysis with SQL
- Exploring the Products Table
- Exploring Possible Column Values
- Exploring Changes Over Time
- Exploring Multiple Tables Simultaneously
- Exploring Inventory vs. Sales
- Exercises
11
Building SQL Datasets for Analytical Reporting
- Thinking Through Analytical Dataset Requirements
- Using Custom Analytical Datasets in SQL: CTEs and Views
- Taking SQL Reporting Further
- Exercises
12
More Advanced Query Structures
- UNIONs
- Self-Join to Determine To-Date Maximum
- Counting New vs. Returning Customers by Week
- Summary
- Exercises
13
Creating Machine Learning Datasets Using SQL
- Datasets for Time Series Models
- Datasets for Binary Classification
- Taking Things to the Next Level
- Exercises
14
Analytical Dataset Development Examples
- What Factors Correlate with Fresh Produce Sales?
- How Do Sales Vary by Customer Zip Code, Market Distance, and Demographic Data?
- How Does Product Price Distribution Affect Market Sales?
15
Storing and Modifying Data
- Storing SQL Datasets as Tables and Views
- Adding a Timestamp Column
- Inserting Rows and Updating Values in Database Tables
- Using SQL Inside Scripts
- In Closing
- Exercises
3
The SELECT Statement
- Retrieving Data from Employee Department
- Listing Materials
- Analysing Total amount Paid By Customers'
- Concatenating the First and Last Names
4
The WHERE Clause
- Getting Details of Employees Residing in the US
- Retrieving details of Sellers Whose Name Starts with Kick
- Checking the Functionality of TRIM() Function
- Retrieving Data of Employees Lived in the US and Canada
- Analyzing the Man Power in a Company
5
CASE Statements
- Grading Employees Punctuality
- Checking the Availability of Items Used in Production
6
SQL JOINs
- Getting Detailed View for Analyzing Population
- Updating Post Office Databases
- Getting Employees History
7
Aggregating Results for Analysis
- Using the GROUP BY Keyword
- Getting the Sum of Number of Items
- Adding Unit Price
- Retrieving the Minimum and Maximum Price of the Commodity
- Retrieving Unique Places
- Analyzing the Items on the Basis of Price Category
8
Window Functions and Subqueries
- Finding the Most Populated Territory
- Analyzing the Demography of Most Populated Territory
- Retrieving Pay Frequency
- Correcting the Entries of Database
10
Exploratory Data Analysis with SQL
- Analyzing Country Codes
11
Building SQL Datasets for Analytical Reporting
- Creating a Personalized Alias of a Query
- Creating a View
12
More Advanced Query Structures
- Analyzing Gender Ratio Inside a Company
- Finding Overlap Records
13
Creating Machine Learning Datasets Using SQL
- Retrieving Full Names
14
Analytical Dataset Development Examples
- Finding Last Names
15
Storing and Modifying Data
- Using the DROP Command
- Updating a Record
