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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. Sai Phanindra Tholeti

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:

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,
  • 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.write
  •, 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

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

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

Plan A

1. Python

Plan B

1. SQL Server TSQL
2. Python

Plan C

1. SQL Server TSQL
2. Python
3. Power BI Analytics
Total Duration4 Weeks7 Weeks11 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
DA 100 Certification Exam Guidance
Total Course Fee ( Payable in Installments)*INR 7000INR 11000INR 24000

Python Training Schedules

S NoTime (IST, Mon - Fri)Start DateTrainerRegister
16:15 AM - 7:15 AMJuly 31stMr. Guna SekharRegister
26 PM - 7 PMJuly 15thMr. Guna SekharRegister

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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 ServerT-SQLSQL Server DBA and MSBI (SSISSSASSSRS) 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.

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.html. Alternatively, participants may request for video demo by mailing us to 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.

Why Choose SQL School

  • 100% Real-Time and Practical
  • ISO 9001:2008 Certified
  • Concept wise FAQs
  • TWO Real-time Case Studies, One Project
  • Weekly Mock Interviews
  • 24/7 LIVE Server Access
  • Realtime Project FAQs
  • Course Completion Certificate
  • Placement Assistance
  • Job Support
  • Realtime Project Solution
  • MS Certification Guidance