Databricks and PySpark for Big Data: From Zero to Expert

سرفصل های دوره

Complete course to learn Databricks, including PySpark, Dataframes, Machine Learning, Advanced Analytics and Streaming

1. Introduction to Apache Spark and Big Data

1. How to get the most out of this course.html

2. Spark Fundamentals

3. How Apache Spark works

4. Apache Spark ecosystem and official documentation

5. PySpark cluster management and architecture

2. Spark Architecture Concepts

1. Spark Optimization Techniques

2. Lazy Evaluation

3. Wide and Narrow Transformations

4. Parquet file in Spark

5. Parallelism and Partitions

6. Shuffling

7. Caching and Storage Levels

3. Databricks Fundamentals

1. Introduction to Databricks

2. Databricks Terminology and Databricks Community

3. Create a free Databricks account

4. Introduction to the Databricks environment

5. First steps with Databricks

4. Databricks Platform

1. Importing notebooks, language configuration and markdown

2. Databricks File Dystem (DBFS)

3. Create, manipulate and visualize tables

4. Databricks widgets

5. ETL, Dataframes and data visualization in Databricks

1. Creating and saving DataFrames in Databricks

2. Transformation and visualization of data in Databricks

3. Population Data Analytics Lab

6. Spark DataFrame API

1. Spark SQL and SQL Dataframe API

2. Temporary Views vs Global Temporary Views

3. Spark Dataframes

4. Spark SQL and SQL Dataframe API Lab

7. Spark Column Expresions

1. Introduction to Spark Column Expresions

2. Column Expressions, operators and methods

3. DataFrame Transformation Methods

4. Subset Rows in Dataframe

8. Dataframe Agregations

1. Spark Aggregation Methods

2. Grouped data methods

3. Aggregate Functions and Math Functions

4. Functions and built-in functions review

5. Dataframe NaN functions and dataframe join

9. Machine Learning con Databricks y Apache Spark

1. Import and exploratory analysis of data

2. Variable preprocessing with PySpark and Databricks

3. Definition of the Machine Learning model and development of the Pipeline

4. Model evaluation with PySpark and Databricks

5. Hyperparameter tuning and registration in MLFlow

6. Predictions with new data and visualization of the results

10. Databricks Koalas The Pandas API for Apache Spark

1. Spark Koalas Fundamentals

2. Feature Engineering with Koalas

3. Creating DataFrames with Koalas

4. Data Manipulation and DataFrames with Koalas

5. Working with missing data in Koalas

6. Data visualization and graph generation with Koalas

7. Import and export data with Koalas

11. Spark Streaming at Databricks

1. Example of Streaming word count with Spark Streaming

2. Spark Streaming Configurations Output Modes and Operation Types

3. Spark Streaming Capabilities

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تولید کننده: Udemy-Training