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Tutorials

Linkedin – JavaScript Scope

Baturi 16 September 2025 0 0

Free Download Linkedin – jаvascript Scope
Updated: 4/29/2024
Duration: 43m | Video: 1280x720 30fps | Audio: AAC, 48 kHz, 2ch | Size: 73.8 MB
Genre: eLearning | Language: English
jаvascript scope determines how variables can be accessed throughout your code. There are two scopes: global and local. Global variables are accessible from anywhere; local variables are accessible only from within the function or block the variables are declared. Scope can be confusing, especially when factors such as hoisting and closures enter the mix. This course provides a thorough introduction to the scope options for jаvascript variables, alongside challenges that help you practice what you've learned. LinkedIn Learning instructor Emmanuel Henri helps you properly scope your variables, mitigate the effects of hoisting, and declare local variables inside non-function code such as if statements using block scope.

Tutorials

Introduction to Spark SQL and DataFrames

Baturi 16 September 2025 0 0

Free Download Introduction to Spark SQL and DataFrames
Updated: April 1, 2024
Duration: 1h 54m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 250 MB
Level: Intermediate | Genre: eLearning | Language: English
Explore DataFrames, a widely used data structure in Apache Spark. DataFrames allow Spark developers to perform common data operations, such as filtering and aggregation, as well as advanced data analysis on large collections of distributed data. With the addition of Spark SQL, developers have access to an even more popular and powerful query language than the built-in DataFrames API. In this course, instructor Dan Sullivan shows how to perform basic operations—loading, filtering, and aggregating data in DataFrames—with the API and SQL, as well as more advanced techniques that are easily performed in SQL. In this section of the course, Dan explains how to join data, eliminate duplicates, and deal with null or NA values. The lessons conclude with three in-depth examples of using DataFrames for data science: exploratory data analysis, time series analysis, and machine learning.