C A R E E R T R A C K

Data Engineer with Python

PROVIDED COURSE COUNT: 23 (2 Courses Are Fully Online Compiler Based + Not Provided Any Course Materials)

About

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

Size: 5.61 GB

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https://www.datacamp.com/tracks/data-engineer-with-python.