What you'll learn

Aspiring Data Engineers & Architects, DBA, Solutions Architect, Technical Managers, Managers, Developers, Data Scientist, Big Data
End-to-end Python for Data Engineering
SQL Programming Basic to Advanced
Essentials for Data Engineering, ML Engineering & AI Engineering

Course content

2 sections • 54 lectures • 13h 18m total length

SQL Introduction30:35
Client & Server Setup12:17
Database Objects Theory28:12
HANDS-ON : Database Objects29:19
HANDS-ON : CRUD Operations21:17
SELECT Operators24:41
CASE & COALESCE Functions13:18
Various DATE Functions5:45
CTAS (Create Table As) Cast, Concat Operations14:10
SQL DML - Update Delete Truncate12:30
HAVING Clause7:42
SQL Joins19:27
Union, Intersect Functions & Views17:34
Materialized View - The View that gets Stored8:18
Common Table Expressions (CTE)10:48
Analytics using WINDOW Functions22:40
MERGE (Conditional Update and Insert) Function & Summary10:52

Python Intro - Architecture, PyCharm, Virtual Env39:32
PyCharm & CLI Walkthrough8:51
Compiled vs Interpreted7:41
Everything is Python is Object12:38
Data Type - String10:20
Data Type - Number4:02
Data Type - List11:35
Data Type - Tuple6:16
Set Dict Type Conversion16:03
Memory Allocation & Operators10:27
Set up Python interpreter in PyCharm11:22
Print & Input Functions16:03
IF Statement14:36
For & While loops15:57
Functions Intro9:53
Function Scoping15:19
Functions RETURN7:53
Function Arguments9:37
Modify Arguments9:06
Positional & Keyword Arguments9:42
args & kwargs16:38
Class Object Self32:48
Class-Instance Variables, __init__17:00
HANDS-ON : Class Object 114:48
HANDS-ON : Class Object 213:47
Inheritance7:50
Python Memory Management8:05
Modules & Packages33:26
HANDS-ON EXERCISE1:31
Module Pre-compilation3:27
Namespace & __name__9:55
Error Handling in Python14:00
File Handling17:09
CSV & JSON module13:37
Python Multi-threading concept17:37
HANDS-ON : Multi-threading22:01
Debugging & Profiling18:26

Requirements

No Prerequisites. Whoever is interested to become Data Engineer, ML Engineer, AI Engineer, Data Architect or AI Architect can take this course

Description

Which are the top programming languages that comes to your mind when you think of Data, AI/ML. I think you know the answer.

Python - Python has come a long way from being a backbencher in the programming world to a topper in today's emerging Data and AI world. Python has lion's share of footprint in Data Engineering and AI/ML. Any AI or ML library that you can think of is from Python. Same is the case with Data Engineering also. Python has taken so much of centerstage that PySpark is the top focus for Spark workloads, so much so that Spark community is trying to make Spark run faster on PySpark than Scala.
SQL - SQL is the language that deals with everything that is data. Spark, which is the numero uno distributed data processing framework, uses SQL construct for batch and stream processing.

In this course, I will teach Python and SQL that is needed for you to be ready for Data and AI/ML workloads.

You will get to from Python basics like data types, functions to advanced topics like Memory Management, Multi-threading, Object Oriented Programming (as much needed for Data Engineering and AI/ML).

In SQL you will get to know CASE, COALESCE, CTE (Common Table Expression), MERGE, WINDOW functions etc. These are very essential to work on Data Engineering (Spark - both Batch & Streaming).

I will be adding Python NumPy and Pandas in future.

Who this course is for:

Aspiring Data Engineers & Architects, DBA, Solutions Architect, Technical Managers, Managers, Developers, Data Scientist, Big Data

What you'll learn

Explore related topics

Course content

SQL for Data Engineering17 lectures • 4hr 49min

Python for Data Engineering, AI & ML37 lectures • 8hr 29min

Requirements

Description

Who this course is for: