English | Size: 5.62 GB
Genre: eLearning
In this track, you’ll discover how to build an effective data architecture, streamline data processing, and maintain large-scale data systems. In addition to working with Python, you’ll also grow your language skills as you work with Shell, SQL, and Scala, to create data engineering pipelines, automate common file system tasks, and build a high-performance database.
Through hands-on exercises, you’ll add cloud and big data tools such as AWS Boto, PySpark, Spark SQL, and MongoDB, to your data engineering toolkit to help you create and query databases, wrangle data, and configure schedules to run your pipelines. By the end of this track, you’ll have mastered the critical database, scripting, and process skills you need to progress your career.
Please note this track assumes a fundamental knowledge of Python and SQL.
Content List:
01 Data_Engineering_For_Everyone
02 Introduction To Data Engineering
03 Stremlined_Data_Ingestion_With_Pandas
04 Writing_Efficient_Python_Code
05 Writing_Functions_With_Python
06 Unit_Testing
07 Data_Processing_In_Shell
08 Introduction_to_Bash_Scripting
09 Object_Oriented_Programming_With_Python
10 Introduction_To_AirFlow_In_Python
11 Building_Data_Engineering_Pipelines_In_Python
12 Introduction_To_AWS_Boto_In_Python
13 Introduction_To_Relational_Databases_In_SQL
14 Database_Design
15 Introduction_To_Scala
16 BigData_Fundamentals_With_PySpark
17 Cleaning_Data_With_Pyspark
18 Introduction_To_Spark_Sql_In_Python
19 Cleaning_Data_In_Sql_Server_Database
20 Transactions_and_Error_Handling_In_Sql_Server
21_Building_and_Optimizing_Triggers_In_Sql_Server
22 Improving_Query_Performance_In_Sql_Server
23 Introduction_To_MongoDB_In_Python
EXCLUDED COURSES AS IT IS FULLY ONLINE COMPILER BASED (AND NO MATERIALS PROVIDED):
24_Introduction_To_Shell
25_Introduction_To_PySpark
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