Big Data with Apache Spark 3 and Python: From Zero to Expert

سرفصل های دوره

Complete bootcamp to learn PySpark, Databricks, Spark Machine Learning, Advanced Analytics, Koalas and Spark Streaming

1. Spark Fundamentals

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

2.1 Big Data with Apache Spark 3 and Python From Zero to Expert.pdf

2.2 Entrega.rar

2. Course material.html

3. Spark Fundamentals

4. Apache Spark execution

5. Apache Spark ecosystem and documentation

6. PySpark operation, cluster administration and architecture

2. Installing Apache Spark locally

1. Download Spark, Java and Anaconda

2. Setting environment variables

3. Running Spark in Prompt and Jupyter Notebook

4. Fixing common problems.html

3. Basic Features and RDDs

1.1 PySpark RDDs.pdf

1. PySpark Cheat Sheet.html

2. RDD Fundamentals

3. Initialize PySpark with SparkSession and the SparkContext

4. Transformations in RDDs like map, filter, flatMap and distinct

5. Transformations in RDDs like reduceByKey, groupByKey or sortByKey

6. RDD actions such as count, first, collect or take

4. Spark DataFrames and Apache Spark SQL

1.1 PySpark Sql Basics Cheat Sheet.pdf

1. PySpark Cheatsheet SQL.html

2. Fundamentals and advantages of DataFrames

3. Characteristics of DataFrames and data sources

4. Creating DataFrames in PySpark

5. Operations with PySpark DataFrames

6. Different types of joins in DataFrames

7. SQL queries in PySpark

8. Advanced features for loading and exporting data in PySpark

5. Advanced features in Apache Spark

1. Funciones avanzadas y optimizacion del rendimiento

2. BroadCast Join and caching

3. User Defined Functions (UDF) and advanced SQL functions

4. Handling and imputation of missing values

5. Partitioning and catalog of APIs

6. Practical Exercise Advanced Analytics with Apache Spark.html

6. Advanced Analytics with Apache Spark

1. Introduction to advanced analytics with Spark

2. Data loading and data schema modification

3. Inspect data in PySpark

4. Column transformation in PySpark

5. Advanced missing data imputation in PySpark

6. Data selection with PySpark and PySpark SQL

7. Data visualization and graph generation in PySpark

8. Persist data with PySpark

7. Kolas The Apache Spark Pandas API

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. Importing and exporting data with Koalas

8. Hands-on exercise with Koalas.html

8. Machine Learning with Apache Spark

1. Fundamentals of Machine Learning with Spark

2. Spark Machine Learning Components

3. Stages of developing a Machine Learning model

4. Import data and exploratory data analysis (EDA)

5. Data preprocessing with PySpark

6. Training the machine learning model in PySpark

7. Evaluation of the Machine Learning model

9. Spark Streaming

1. Practical example of counting words with Spark Streaming

2. Spark Streaming Configurations Output Modes and Operation Types

3. Time Window Operations in Spark Streaming

4. Spark Streaming Capabilities

5. Use case Real-time bank fraud detection (Part I)

6. Use case Real-time bank fraud detection (Part II)

7. Spark Streaming Exercise.html

10. Introduction to Databricks

1. Introduction to Databricks

2. Databricks Terminology and Databricks Community

3. Delta Lake

4. Create a free Databricks account

11. Apache Spark on Databricks

1. Introduction to the Databricks environment

2. Getting started with Databricks

3. Creating and saving DataFrames in Databricks

4. Data transformation and visualization in Databricks

5. Use case Population data analytics

12. Machine Learning in Databricks

1. Import and exploratory analysis of the 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

13. Additional material

1.1 PySpark_Cheat_Sheet_Python.pdf

1. Additional Resources Complete Guide to Spark.html

139,000 تومان

خرید اشتراک افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: Udemy-Training