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Data Engineering, PySpark, Data Analysis, Coding exercise, Data Analytics
Rating: 5
Hands-on course focusing on data engineering and analysis on Azure Databricks using Spark SQL
Rating: 4.95
Learn Big Data Analysis in PySpark using the Apache Spark's Powerful Features and Easy Commands of Python and SQL
Rating: 4.9
Preparation course for Databricks Data Engineer Associate certification exam
Rating: 4.73148
Data engineering and architecting pipelines using snowflake & AWS cloud
Rating: 4.71212
100% pass || 4 CCA175 Practice exams || Cluster Setup || Real Exam Like Questions || Spark 2.4 solutions using Python
Rating: 4.7
Big Data with Scala and Spark,PySpark and AWS,Data Scraping & Data Mining With Python, Mastering MongoDB for Beginners
Rating: 4.625
Real World Project on Formula1 Racing for Data Engineers using Azure Databricks, Delta Lake, Azure Data Factory [DP203]
Rating: 4.61293
Build Pyspark and Spark SQL Applications on AWS EMR, Orchestrate using Step Functions, Manage EMR using Boto3 and more
Rating: 4.60714
Build intelligent data pipelines with big data processing and machine learning technologies
Rating: 4.54545
Learn GCS for Data Lake, BigQuery for Data Warehouse, GCP Dataproc and Databricks for Big Data Pipelines
Rating: 4.53571
Learn how to use Spark with Python, including Spark Streaming, Machine Learning, Spark 2.0 DataFrames and more!
Rating: 4.53283
Learn how to use Python and PySpark 3.0.1 for Data Engineering / Analytics (Databricks) - Beginner to Ninja
Rating: 4.52
Implement PySpark Real Time Project. Learn Spark Coding Framework. Transform yourself into Experienced PySpark Developer
Rating: 4.51786
Building Data Processing Pipeline Using Apache NiFi, Apache Kafka, Apache Spark, Cassandra, MongoDB, Hive and Zeppelin
Rating: 4.5
PySpark tutorial with 20+ hands-on examples of analyzing large data sets on your desktop or on Hadoop with Python!
Rating: 4.49237
125+ Questions to for Azure data factory, Databricks spark pyspark, ADLS & many more. With Cheatsheet & Contnious update
Rating: 4.42262
Effectively apply Advanced Analytics to large datasets using the power of PySpark
Rating: 4.4
This Python for beginners course will help you to become Zero to Hero. Learn Python Programming in Easy Way.
Rating: 4.37793
Learn Apache Spark, fundamentals of Apache Spark with Python including AWS EC2, Data frames, Machine Learning, etc.
Rating: 4.35
A Step by Step Hands-on Guide to prepare for Databricks Certified Associate Developer for Apache Spark using Pyspark
Rating: 4.34783
Build Data Engineering Pipelines using Databricks core features such as Spark, Delta Lake, cloudFiles, etc.
Rating: 4.32937
Learn Python & Implement Data-Structures like a Professional from Absolute Beginner to building Advanced Python Programs
Rating: 4.3
Data warehousing & ETL on AWS Cloud
Rating: 4.27778
Use PySpark to productionize analytics over Big Data and easily crush messy data at scale
Rating: 4.25
Learn Python & Implement Data Structures with Python like a Professional from Absolute Beginner to building Advance Apps
Rating: 4.25
Big data Python Spark PySpark coding framework logging error handling unit testing PyCharm PostgreSQL Hive data pipeline
Rating: 4.25
PySpark - Databricks Certified Associate Developer for Apache Spark 3.0
Rating: 4.2
A beginners guide to learn Machine Learning (including Hands-on projects - From Basic to Advance Level)
Rating: 4.1573
Become zero to hero in Apache PySpark 3.0 programming in a fun and easy way. Fastest way to prepare for Databricks exam.
Rating: 4.15
Get well versed with Machine learning and AI by working on Hands-on Projects.
Rating: 4.09821
Diabetes Prediction using Machine Learning in Apache Spark
Rating: 4.05
End to end batch processing,data orchestration and real time streaming analytics on GCP
Rating: 4.03226
Add Spark Streaming to your Data Science and Machine Learning Python Projects
Rating: 4
Learn BigData and IoT with PySpark, Spark Streaming, Kafka, IoT Architecture, 40+ RDDs & Dataframes Functions- Hands-on
Rating: 3.95
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0
Rating: 3.3
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