Python Online Training

Official Learning Partner

Course Highlights

What is Python?

Python is a easier, useful platform used for Big Data Analytics, Software Development, Cloud Scripting, Data Science, Machine Learning, Automations and almost everything with Data !

Who can join this Python Training Course?

Anyone who wants to get into Data Platform, Data Analytics, Data Engineering and Data Science can find this course very very useful. This course includes Basic to Advanced Data Analytics concepts including Data Ingestions, ETL, Data Cleansing, Big Data Loads, Pandas Dataframes, SQL Server TSQL Integrations, Power BI Desktop Integrations, Power BI Cloud Concepts with Python Analytics.

Trainer: Mr. Guna Shekeran

Training Modes:

LIVE Online Self Paced Videos

Training Highlights:

Python Fundamentals
Python Jupyter Notebooks
Python Data Types, Classes

Python Iterators, Lists
Python Functions, JSON
Python for Big Data Analytics

Python Data Frames, Pandas
Python with SQL Server
Python with TSQL Queries

Python with SQL Aggregations
Python with Power BI
Python with Cloud Service

Python Training
Course Contents:

Brochure Download Register Now

Module 1 : Python [Applicable for Python Plans A, B, C]

Part 1: Python Fundamentals

Ch 1: Data Analytics Intro & Python

Data and Databases : Introductions
Data Analytics Job Role
Python : Introduction & Advantages
Python : Career Options, Scope
Python for Big Data Analytics
Why Python? Usage Options
Python Installation : Multi OS
Anaconda Software Installation
Jupyter Interface for Python
Python Activities with Jupyter
Notebooks : Python Web Interface
Notebooks and Cells: Introduction

Ch 2: Basic Operations with Python

Python Interface : Creating Notebook
Adding Cells, Saving Notebook
Executing Basic Cells; Result Window
Single Line & Multi Line Comments
Save, Open / Clone Notebooks
Indentation Options with Python
Python : Internal Architecture
Code Editor, Source Files
Compiler, Byte Code, Virtual Machine
Program Execution : Py, PYC and PVM
Python Libraries / Modules
Compiler Versus Interpreter

Ch 3: Data Types & Variables

Integer / Int Data Types
Float & String Data Types
Boolean Data Types, Binary Types
Sequence Types: List, Tuple
Range, Complex & memoryview
Retrieving Data Type: type()
Python Variables: Naming
Camel / Pascal / Snake Case
Multi Assignments & Casting
Multi Word Variables, PRINT
Multiple Variables and Vales
Unpack Collection, Outputs

Ch 4: Python Operators, Conditions

Python Operators : Arithmetic
Assignment, Compare Operators
Logical, Identity Operators
Member & Bitwise Operators
Operator Precedence Options
Python Operator Expressions
Python If … Else Statement
Short Hand If Statement, Use
OR, AND and NOT Statements
Pass Statement with Python
ELIF and ELSE IF Statements
Ternary Operators in Python

Ch 5: Python Loops, Iterations

Python Loop & Realtime Use
Python While Loop Statement
Break and Continue Statement
Using Print with While()
Iterations & Conditions
Exit Conditions : Cautions
Python For Loop Statement
Break, Continue & Range
Python Iterators : Creation
__iter__() and __next__()
Iterator vs Iterable
iter() and Looping Options

Ch 6: Python Collections

Python Collections (Arrays)
Python Collection Data Types
List, Tuple, Set, Dictionary
List Items, Ordered & Length
list() Constructor, print()
Python Tuples, Tuple Items
tuple() Constructor, Usage
Python Sets : Syntax Rules
Duplicates, Types, Ordered
Python Dictionaries: Usage
Changeable, Ordered Data
Dictionary Construct, type()

Part 2: Python For Data Analytics – 1

Ch 7: Python Functions

Python Functions : Realtime Use
Function : Creation, Execution Call
Function Parameters, Arguments
Arguments Number, Arg keyword
Arbitrary Keyword & **kwargss
Default & List Value Parameters
Python Lambda Functions
Using Lamdba Options in Python
Anonymous Functions in Python
Arguments, Expressions
Recursive Functions, Usage
Return & Print with Lamdba

Ch 8: Python Classes & Arrays

Python Classes & Objects
Python Classes : Usage
__init__() Function
__str__() Function
Self Parameters & Usage
Object Properties Options
Python Inheritance & Classes
Adding Parent & Child Classes
Add __init__() Function
Using super() Function
Add Properties, Methods
Polymorphism in Python

Ch 9: Python Modules

Python Modules : Creation
Import Python Modules
Using Variables in Modules
Naming, Renaming Module
Built In Modules & dir
Using Modules, Properties
datetime module in Python
Date Objections, strftime Method
import datetime, datetime.now()
Using Python Constructors
Conditional Columns, Expressions
Disable / Enable Data Loads

Ch 10: Python JSON & RegEx

Python JSON Concepts, Usage
Python Dictionary & import json
Convert from Python to JSON
Python Objects into JSON strings
Result Formatting & Ordering
json.dumps, print options
Python Regular Expressions
RegEx Module in Python
RegEx Functions : findall
search() Function & split
span() function & Usage
Using RegEx with JSON

Ch 11: Python User Inputs & TRY

Python Try Except
Python Exception Handling
NameError Resolution
Python Finally Block, Usage
Raise an exception method
TypeError, Scripting in Python
Python User Inputs
Python String Formatting
Multiple Values & String
Python Index Numbers
Named Indexes, Usage
input() & raw_input()

Ch 12: Python File Handling

File Handling
r, a, w, x modes
t, b Operations
File Activities
Read Only Parts
Loop, Close Files
Python File Write
Appending, Overwriting
Create a New File
import os, path.exists
f.open, f.write
f.read, f.close

Part 3: Python For Data Analytics – 2

Ch 13: Data Analytics – Pandas

Python Modules & Pandas
Why Use Pandas?
Pandas Codebase & Usage
Installation of Pandas
import & pandas.DataFrame
Checking Pandas Version
Pandas Series
one-dimensional array
Labels : Creation, Use
series(), print()
Pandas DataFrames
Dataframes & Series

Ch 14: Data Analytics – DataFrames

Pandas DataFrames in Python
DataFrame() & Realtime Usage
Indexes & Named Options
Locate Row and Load Rows
Row Index & Index Lists
Load Files Into a DataFrame
Pandas Read CSV
pd.read_csv() Function
pd.options.display.max_rows
df.to_string() Function
Dictionary as JSON
tail() & null() Function

Ch 15: Data Analytics – Pandas

Pandas – Cleaning Data
Removing Rows, Data Cleansing
Replace, Transform Columns
Data Discovery & Column Fill
Identify & Remove Duplicates
dropna(), fillna() Functions
Pandas – Data Correlations
Data Relations and Validations
Good & Bad Correlation
Perfect Correlation Scenarios
Python Data Plotting Options
matlib Module & Plotting

Ch 16: SQL Server with Python – 1

Installing SQL Server DB Engine
Install Machine Learning Services
SQL Server Management Studio
Install Azure Data Studio Tool
sp_execute_external_script
Input Data & Result Sets
DDL & DML with Python
SQL_out, SQL_in with Python
Variables & Parameters in Python
Python Version, Package List
Script Parameters & Usage
WITH RESULT SETS Options

Ch 17: SQL Server with Python – 2

Using pandas.Series with SQL Server
Indexing Methods and Realtime Use
Convert series to data frame
DataFrames with SQL Server
Output values into data.frame
Output Datasets and Usage
pymssql package in SQL Server
pip list & Package Manager
Python runtime, Py Package Index
pymssql.connect & Usage
Query Execution & Result
Cursor Variables & Usage

Ch 18: Power BI with Python

Installing Power BI Desktop
Using Python Script Visual
PyScript Options & Tuning
Settings, Labelling Options
Running and Testing Scripts
Data Validations in Power BI
Power BI Cloud : ipynb Scripts
Python in Desktop Vs Cloud
Interactive Reports with Python
Power Query Options (M Lang)
Data Formatting with Python
Integrate SQL, Power BI, Python

Module 2 : SQL Server Basics, Queries, Stored Procedures and Database Development

Ch 1: SQL SERVER INTRODUCTION

Data, Databases and RDBMS Software
Database Types : OLTP, DWH, OLAP
Microsoft SQL Server Advantages, Use
Versions and Editions of SQL Server
SQL : Purpose, Real-time Usage Options
SQL Versus Microsoft T-SQL [MSSQL]
Microsoft SQL Server – Career Options
SQL Server Components and Usage
Database Engine Component and OLTP
BI Components, Data Science Components
ETL, MSBI and Power BI Components
Course Plan, Concepts, Resume, Project
24 x 7 Online Lab for Remote DB Access
Software Installation Pre-Requisites

Ch 2: SQL SERVER INSTALLATIONS

System Configuration Checker Tool
Versions and Editions of SQL Server
SQL Server and SSMS Installation Plan
SQL Server Pre-requisites : S/W, H/W
SQL Server 2016 / 2017 Installation
SQL Server 2019 Installation
Instance Name and Server Features
Instances : Types and Properties
Default Instance, Named Instances
Port Numbers, Instance Differences
Service and Service Account Use
Authentication Modes and Logins
Windows Logins and SQL Logins
FileStream and Collation Properties
DBEngine and Replication Components

Ch 3: SSMS Tool, SQL BASICS – 1

SQL Server Management Studio
Local and Remote Connections
System Databases: Master and Model
MSDB, TempDB, Resource Databases
Creating Databases : Files [MDF, LDF]
Creating Tables in User Interface
Data Insertion & Storage. Limitations
SQL : Purpose and Real-time Usage
SQL Versus T-SQL : Basic Differences
DDL, DML, SELECT, DCL and TCL
Creating Tables using SQL Scripts
Data Storage, Inserts – Basic Level
Table Data Verifications with Select
SELECT Statement for Table Retrieval

Ch 4: SQL BASICS – 2

Creating Databases & Tables in SSMS
Single Row Inserts, Multi Row Inserts
Rules for Data Insertion Statements
SELECT Statement @ Data Retrieval
SELECT with WHERE Conditions
Batch Concept and Go Statement
AND and OR Operators Usage
IN Operator and NOT IN Operator
Between, Not Between Operators
LIKE and NOT LIKE Operators
UPDATE Statement & Conditions
DELETE & TRUNCATE Statements
Logged and Non-Logged Operations
ADD, ALTER and DROP Columns
ALTER & DROP Table Statements

Ch 5: SQL Basics – 3, T-SQL INTRO

Database Objects : Tables and Schemas
Schemas : Group Tables in Database
Schemas : Security Management Object
Creating Schemas & Batch Concept
Using Schemas for Table Creation
Data Storage in Tables with Schemas
Data Retreival and Usage with Schemas
Table Migrations across Schemas
Import and Export Wizard in SSMS
Data Imports with Excel File Data
Performing Bulk Operations in SSMS
Temporary Tables : Real-time Use
Local and Global Temporary Tables
# and ## Prefix, Scope of Usage
Session Level, Connection Level Use

Ch 6 : CONSTRAINTS,INDEXES BASICS

Constraints and Keys – Data Integrity
NULL, NOT NULL Property on Tables
UNIQUE KEY Constraints: Importance
PRIMARY KEY Constraint: Importance
FOREIGN KEY Constraint: Importance
REFERENCES, CHECK and DEFAULT
Candidate Keys and Identity Property
Database Diagrams and ER Models
Relationships Verification and Links
Indexes : Basic Types and Creation
Index Sort Options, Search Advantages
Clustered and NonClustered Indexes
Primary Key and Unique Key Indexes
Need for Indexes – working with Keys

Real-time Case Study – 1 (Sales & Retail)

Objective : DB Design, Table Design, Relations
Involves Purchases, Products, Customers
and Time Data with Various Data Types.

Ch 7: JOINS, T-SQL Queries : Level 1

JOINS – Table Comparisons Queries
INNER JOINS For Matching Data
OUTER JOINS For (non) Match Data
Left Outer Joins with Example Queries
Right Outer Joins with Example Queries
FULL Outer Joins – Realtime Scenarios
Join Queries with “ON” Conditions
Join Unrelated Tables in SQL Server
NULL, IS NULL Operators in Joins
CROSS JOIN and CROSS APPLY
CROSS JOIN Versus CROSS APPLY
One-way & Two Way Data Comparisons
Important Join Queries in T-SQL
Join Options: Merge, Loop, Hash

Ch 8: Group By, T-SQL Queries Level 2

GROUP BY Queries and Aggregations
Group By Queries with Having Clause
Group By Queries with Where Clause
Using WHERE and HAVING in T-SQL
Rollup : Usage and T-SQL Queries
Cube : Usage and T-SQL Queries
UNION and UNION ALL Operator
EXISTS Operator, Query Conditions
Sub Queries and Alternatives to Joins
Using Joins with Group By Queries
Using Joins with Nested Sub Queries
Sub Queries with Joins and Group By
Using UNION and UNION ALL in Queries
Nested Sub Queries with Group By, Joins
Comparing WHERE, HAVING Conditions

Ch 9: JOINS, T-SQL QUERIES Level 3

GetDate, Year, Month, Day Functions
Date & Time Styles, Data Formatting
DateAdd and DateDiff Functions
Cast and, Convert Functions in Queries
String Functions: SubString, Relicate
Len, Upper, Lower, Left and Right
LTrim, RTrim, CharIndex Functions
MERGE Statement – Comparing Tables
WHEN MATCHED and NOT MATCHED
Incremental Load with MERGE Statement
IIF() Function for Value Compares
CASE Statement : WHEN, ELSE, END
ROW_NUMBER() and RANK() Queries
Dense Rank and Partition By Queries

Ch 10: View, SPs, Function Basics

Views : Types, Usage in Real-time
System Predefined Views and Audits
Listing Databases, Tables, Schemas
Functions : Types, Usage in Real-time
Scalar, Inline and Multi-Line Functions
System Predefined Functions, Audits
DBId, DBName, ObjectID, ObjectName
Variables & Parameters in SQL Server
Procedures : Types, Usage in Real-time
User & System Predefined Procedures
Parameters and Dynamic SQL Queries
Sp_help, Sp_helpdb and sp_helptext
sp_pkeys, sp_rename and sp_help
Important System Objects and Metadata
When to use Which Database Objects

Ch 11: Triggers & Transactions

Triggers – Purpose, Real-world Usage
FOR/AFTER Triggers – Real time Use
INSTEAD OF Triggers – Real time Use
INSERTED, DELETED Memory Tables
Using Triggers for Data Replication
Enable Triggers and Disable Triggers
Database Level, Server Level Triggers
Auditting Triggers and Real World Use
Transactions : Types, ACID Properties
Transaction Types and AutoCommit
EXPLICIT & IMPLICIT Transactions
COMMIT and ROLLBACK Statements
Open Transaction Scenarios & Cause
Query Blocking Scenarios @ Real-time
NOLOCK and READPAST Lock Hints

Ch 12 : ER MODELS, NORMAL FORMS

Normal Forms for Entity Relationships
First Normal Form and Atomocity
Second Normal Form, Candidate Keys
3rd Normal Form Multi Value Dependancy
Boycee-Codd Normal Form : BNCF
Fourth Normal Form Realtime Advantages
1:1, 1:M, M:1, M:M Relationship Types
Joins with Group By Queries
Joins with Sub Queries, Formating
Office Data Connections, Excel Reports
Excel Pivot Reports and Reports
SQL Queries (Auto Generated) in BI Tools
FETCH OFFSET, NEXT ROWS, Order By
Data Refresh (Manual and Automated)

Real-time Case Study – 2 (Sales & Retail)

Objective : Query Writing, Excel Integration
Excel Pivot Tables, Pivot Charts,
Data Formatting, ODC Connections & Labelling

Ch 13: STORED PROCEDURES Level 2

Table Valued Parameters (TVP)
ReadOnly Parameters, Stored Procedures
Output Parameters, Stored Procedures
User Data Types and Real-time Use
Dynamic Data Insertions with SPs
Table Cloning, Inserts @ Table Variables
SQL Injection Attacks – Precautions
CTE : Common Table Expressions
Real-time Scenarios with CTEs – Usage
ROW_NUMBER() with CTE Queries
Using CTEs for Avoiding Self Joins
Using CTEs for Avoiding Sub Queries
Recursive CTEs and ANCHOR Element
Termination Checks in Recursive CTEs

Ch 14: STORED PROCEDURES – Level 3

DML Triggers and DDL Triggers
FOR and INSTEAD OF Triggers
Magic Tables : Inserted, Deleted
Views on Tables – SCHEMABINDING
ENCRYPTION and CHECK OPTION
Cascaded Views, Encrypted Views
Updatable Views, Joins with Triggers
Stored Procedures @ Triggers, Views
Cursors – Benefits, Cursors in SProcs
ForwardOnly, Scroll & Local Cursors
Static, Dynamic & Global Cursors
Keyset Cursors and @@FetchStatus
Nesting of Stored Procedures – Dynamic
Data Formatting and WHILE Loops
Using Temporary Tables for Formatting

Ch 15: XML,BLOB,FUNCTIONS Level 2

Functions : Types, Real-world Usage
Scalar Value Returning Functions
Inline Table Value Functions
Multi-Line Table Value Functions
WHILE Loops and Iterations in T-SQL
Table Variables Usage in T-SQL
Data Type Conversions with Functions
Composite Keys , Computed Columns
Self Referencing Keys, Self Joins
Adding Keys to Existing Tables
XML AUTO, XML RAW and XML PATH
BULK INSERT, BULKCOLUMN, JSON
OPENROWSET, PIVOT and UNPIVOT
JSON Files – Data Import into SQL DB

Ch 16: Server, DB Architecture

Server Architecture and Protocols
Database Engine and Query Processor
Parser, Optimizer, SQL & DB Manager
Storage Engine Components, SQL OS
File Manager and Database Files
Transaction Services, Buffer Manager
Lock Manager, IO Manager, MDAC
CLR, WAL, Lazy Writer, Checkpoint
Database Architecture – Data Files
Database Architecture – Log Files
Primary (mdf), Secondary Files (ndf)
Filegroups Usage, ReadOnly Filegroups
Database Files : Size and Location
Pages, Extents. Uniform, Mixed Extents
Transaction Log File [LDF], LSN, VLF

Ch 17 – 20: REAL-TIME PROJECT (BANKING)

Includes 2500 Lines of Code (COMPLETELY SOLVED).

Phase 1: DATABASE DESIGN

Understanding Project Requirements
End to End Project Work Flow
Naming Conventions in Real-time
Primary (mdf) and Secondary (ndf) Files
Table Schemas : Creation and Use
Implementing Normal Forms (OLTP)
Computed Columns and Data Types
SQL_Variant, Bit, sysname Data Types
Email and Phone Number Validations
Data Types Conversions, Validations

Phase 2: QUERY DESIGN

Joining Tables for Reports
Views with JOIN Options
Implementing Indexed Views
Using PIVOT Tables in Queries
Dynamic Conditions in Queries
Parameterized Queries in T-SQL

Phase 3: PROGRAMMING

Event Handling , Error Handling
Stored Procedures with Transactions
Error Handling, Event Handling Options
Transaction Nesting, Save Points
Stored Procedures with Tables
Stored Procedures with Views
Stored Procedures with Functions
Automating DML with Triggers
Project Deployments, Project FAQ

Project Solution Explanation

Resume Points from the Project

Interview FAQs from Project

Python Training (with Pandas Dataframes, SQL. Excel, Power BI)

	Plan A 1.Python	Plan B 1. SQL Server TSQL 2. Python
Total Duration	4 Weeks	7 Weeks
Python Introduction	✔	✔
Python Data Types	✔	✔
Variables, Expressions	✔	✔
If.. Else, While, For	✔	✔
Loops & Interactions	✔	✔
Python Classes, Objects	✔	✔
Python Modules, File IO	✔	✔
Python Dataframes	✔	✔
Pandas & Big Data	✔	✔
NumpPy & Statistics	✔	✔
Python IoT, Data Analytics	✔	✔
Python Programming	✔	✔
Python Controls	✔	✔
TSQL : Database Basics, T-SQL	✖	✔
TSQL : Constraints, Joins, Queries	✖	✔
TSQL : Views, Group By, Self Joins	✖	✔
TSQL : Excel Analytics & Pivot	✖	✔
TSQL : Procedures & Functions	✖	✔
Power BI : Report Design, Visuals	✖	✖
Power BI : M Lang, DAX for ETL	✖	✖
Power BI : Cloud, Apps, Tenant	✖	✖
Power BI : Paginated Reports	✖	✖
Power BI with Python	✖	✖
Total Course Fee ( Payable in Installments)*	INR 9000USD 100	INR 14000USD 150

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SQL Server & TSQL Schedules

S No	Time (IST, Mon - Fri)	Start Date	Trainer	Register
1	9 AM - 10 AM	Nov 25th	Mr. Sai Phanindra	Register
2	10:30 AM - 11:30 AM	Dec 10th	Mr. Sai Phanindra	Register
3	8 PM - 9 PM	Dec 2nd	Mr. Sai Phanindra	Register

Python Training Schedules

S No	Time (IST, Mon - Fri)	Start Date	Register
1	7 AM -8 AM	Dec 3rd	Register
2	8 PM - 9 PM	Nov 26th	Register

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SQL SCHOOL

24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.

Technical FAQs

Who is SQL School? How far you have been in the training services ?

SQL School is a registered training institute, established in February 2008 at Hyderabad, India. We offer Real-time trainings and projects including Job Support exclusively on Microsoft SQL Server, T-SQL, SQL Server DBA and MSBI (SSIS, SSAS, SSRS) Courses. All our training services are completely practical and real-time.CREDITS of SQL School Training Center

We are Microsoft Partner. ID# 4338151
ISO Certified Training Center
Completely dedicated to Microsoft SQL Server
All trainings delivered by our Certified Trainers only
One of the few institutes consistently delivering the trainings for more than 8+ Years online as inhouse
Real-time projects in
- Healthcare
- Banking
- Insurance
- Retail Sales
- Telecom
- ECommerce

I registered for the Demo but did not get any response?

Make sure you provide all the required information. Upon Approval, you should be receiving an email containing the information on how to join for the demo session. Approval process usually takes minutes to few hours. Please do monitor your spam emails also.

Why you need our Contact Number and Full Name for Demo/Training Registration?

This is to make sure we are connected to the authenticated / trusted attendees as we need to share our Bank Details / Other Payment Information once you are happy with our Training Procedure and demo session. Your contact information is maintained completely confidential as per our Privacy Policy. Payment Receipt(s) and Course Completion Certificate(s) would be furnished with the same details.

What is the Training Registration & Confirmation Process?

Upon submitting demo registration form and attending LIVE demo session, we need to receive your email confirmation on joining for the training. Only then, payment details would be sent and slot would be allocated subject to availability of seats. We have the required tools for ensuring interactivity and quality of our services.

Please Note: Slot Confirmation Subject to Availability Of Seats.

Will you provide the Software required for the Training and Practice?

Yes, during the free demo session itself.

How am I assured quality of the services?

We have been providing the Trainings – Online, Video and Classroom for the last EIGHT years – effectively and efficiently for more than 100000 (1 lakh) students and professionals across USA, India, UK, Australia and other countries. We are dedicated to offer realtime and practical project oriented trainings exclusively on SQL Server and related technologies. We do provide 24×7 Lab and Assistance with Job Support – even aftrer the course! To make sure you are gaining confidence on our trainings, participans are requested to attend for a free LIVE demo based on the schedules posted @ Register. Alternatively, participants may request for video demo by mailing us to contact@sqlschool.com Registration process to take place once you are happy with the demo session. Further, payments accepted in installments (via Paypal / Online Banking) to ensure trusted services from SQL School™

YES, We use Enterprise Edition Evaluation Editions (Full Version with complete feature support valid for SIX months) for our trainings. Software and Installation Guidance would be provided for T-SQL, SQL DBA and MSBI / DW courses.

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Concept wise FAQs
TWO Real-time Case Studies, One Project
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Realtime Project FAQs
Course Completion Certificate
Placement Assistance
Job Support
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