Python Programming

Live / Classroom Sessions

Duration : 30 Days

Live Classes Fee : 1500/- 1000/- *

  • Basics, Operators, Data Types
  • Functions, Modules, Packages
  • Sequence or Collections - List, Dictionary, Tuple, Sets,
  • String Handling, RegEx
  • Control Statements, Loops
  • OOPS, Inheritance, Exception Handling, IO, Multithreading

Master the basics of Django/Data Analytics

Next Offline/Online Batch
  • 21/12/2020
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  • Tuesday
  • |
  • 03:30 AM

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Current Offline/Online Batch
  • 21/12/2020
  • |
  • Tuesday
  • |
  • 03:30 AM

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Course Content

  • What is Python and history of Python?
  • Unique features of Python
  • Install Python and Environment Setup
  • First Python Program
  • Python Identifiers, Keywords and Indentation
  • Comments and document interlude in Python
  • Command line arguments
  • Getting User Input
  • Operators Overview
  • Arithmetic Operations on Numeric Values
  • Logical Operators
  • Relational or Comparison Operators
  • Bitwise Operators
  • Identity Operators
  • Membership Operators
  • Order of Operands
  • Operators on Strings
  • Variables
  • Types of Variables
  • Types of Variables-String Types of Variables-Numeric
  • Types of Variables-Boolean Variables
  • Types of Variables-List Adding Elements to a List Accessing the Elements of a List
  • Types of Variables-Dictionary
  • Introduction to control Statements
  • Pass Statements
  • Conditional Statements
  • Types of Conditional Statements
  • If Statements
  • If...Else Statements
  • If...Else If Statements
  • If...Else If...Else Statements
  • Nested If Statements
  • Loops in Python
  • For Loop
  • While Loop
  • Loop else statement Nested Loop
  • range() Function
  • break Statements
  • continue Statements
  • Introduction to functions
  • Python user defined functions
  • Python packages functions Structure of Python module Importing module in a Python Program
  • Importing entire module Importing selected object from a module
  • Python’s processing of import module command
  • Working with math, random and other module
  • Defining and calling Function
  • Arguments and Return Statement
  • Variable-Length Arguments Recursion
  • Python Modules & Packages
  • Accessing Values in Strings
  • Various String Operators String Slices
  • String Functions and Methods
  • What are regular expressions?
  • The match Function
  • The search Function Matching vs searching
  • Search and Replace Extended Regular Expressions
  • Wildcard
  • Python Lists- Lists are mutable
  • Creating and Accessing Lists List Operations
  • Working with List
  • List Function and Methods
  • A Dictionary- Key: Value Pairs
  • Working with Dictionaries
  • Dictionary Functions and Methods
  • Advantages of Tuple over List
  • Creating and Accessing Tuples
  • Tuple Operations
  • Tuple Functions and Methods
  • How to create a set?
  • Iteration Over Sets
  • Python Set Methods
  • Python Set Operations
  • Union of sets
  • Built-in Functions with Set
  • Python Frozensett
  • Overview of OOP
  • Creating Classes and Objects
  • Accessing attributes
  • More about class and its members
  • Variable in class : Instance variable, Class variable Method in class
  • Instance method, Static method
  • Built-In ClassAttributes
  • Built-In ClassAttributes
  • The init method[__init__()] The del method [__del__()](Destroying Objects)
  • The str method [__str__()]
  • Private Attributes
  • Reading and modifying properties of classes using attr Methods
  • The Self Reference
  • Instance as an argument and return type
  • Introduction to Inheritance
  • Need for Inheritance Different Forms of Inheritance
  • Derived and Base classes (Subclassing)
  • Creating object of derive class
  • The derive class __init__()
  • Sub classing and scoping Overriding methods
  • What is Exception?
  • Handling an exception try....except...else
  • try-finally clause
  • Argument of an Exception
  • Python Standard Exceptions
  • Raising an exceptions
  • User-Defined Exceptions
  • Reading and writing text files Writing Text Files
  • Appending to Files and Challenge
  • Writing Binary Files Manually/
  • Using Pickle to Write Binary Files
  • What is multithreading? Starting a New Thread
  • The Threading Module Synchronizing Threads Multithreaded Priority Queue
  • Python Spreadsheet Interfaces
  • Python XML interfaces
  • What is HTML?
  • Basics of HTML- Structure of HTML
  • Div and Span tag and its attribute
  • Table tag and its attribute
  • Form tag, Label tag and its attribute
  • Input tag, Button tag all related tags and its attribute
  • Image Tag and its attribute
  • What is CSS and what is its need?
  • Type of CSS
  • Basic CSS syntax: attribute:proptery;
  • How to implements all three types
  • CSS Class / Id
  • CSS Media Query
  • CSS Rules
  • What is Bootstrap?
  • How to use bootstrap in HTML page Online mode Offline mode
  • Bootstrap Button classes, Form classes, Input classes, Div classes,
  • And classes for Container, Header, Footer, Slider
  • Bootstrap Navigation Bar
  • Table classes
  • Image classes
  • Alert classes
  • Text Classes
  • What is JavaScript?
  • Basic syntax and structure
  • DOM Properties in JavaScript
  • Variable declaration
  • Events like : onclick, onmouseover, onmouseout, etc.
  • Form validation using JavaScript
  • Animation using JavaScript
  • JavaScript basic functions
  • What is Jquery
  • Basic syntax and structure
  • JQuery Events
  • JQuery Functions
  • Live Project
  • Data, Database Concept
  • Entity, Relation
  • RDBMS Concept
  • Normalization
  • Codd’s Rules
  • List the capabilities of SQL SELECT statements
  • Execute a basic SELECT statement
  • Projection and selection of the rows
  • Limit the rows that are retrieved by a query
  • Sort the rows that are retrieved by a query
  • Use ampersand substitution to restrict and sort output at runtime
  • Describe various types of functions available in SQL
  • Use character, number, and date functions in SELECT statements
  • Describe various types of conversion functions that are available in SQL
  • Use the TO_CHAR, TO_NUMBER, and TO_DATE conversion functions
  • Apply conditional expressions in a SELECT statement (CASE, DECODE)
  • Identify the available group functions
  • Describe the use of group functions
  • Group data by using the GROUP BY clause
  • Include or exclude grouped rows by using the HAVING clause
  • Write SELECT statements to access data from more than one table using equijoins and no equijoins
  • Join a table to itself by using a self- join
  • View data that generally does not meet a join condition by using outer joins
  • Generate a Cartesian product of all rows from two or more tables
  • Define subqueries
  • Describe the types of problems that the subqueries can solve
  • List the types of subqueries
  • Write single-row and multiple-row subqueries
  • Describe set operators
  • Use a set operator to combine multiple queries into a single query
  • Control the order of rows returned
  • Describe each data manipulation language (DML) statement
  • Insert rows into a table
  • Update rows in a table
  • Delete rows from a table
  • Control transactions
  • Advance DML statement:- multiple Insert, Insert all
  • Categorize the main database objects
  • Review the table structure
  • List the data types that are available for columns
  • Create a simple table
  • Explain how constraints are created at the time of table creation
  • Flashback
  • Functionality of recycle Bin
  • Purge
  • Describe how schema objects work
  • Create simple and complex views
  • Retrieve data from views
  • Inline views
  • Top –N Analysis
  • Create, maintain, and use sequences
  • Create and maintain indexes
  • Create private and public synonyms
  • System security and data security
  • user creation and management
  • grant, revoke, with grant option
  • System Privileges
  • Objects Privileges
  • Public synonyms
  • Introduction, USES, INSTALLATION
  • Ndarray object, Data Types, data type object-dtype
  • Various Array Attributes of NumPy - shape, ndim,itemsize, etc.
  • Array Creation Routines- numpy.empty, numpy,zeros, numpy.ones
  • Array from Existing Data- numpy.arange, numpy.linspace, numpy.logspace
  • Array from Numerical Ranges- numpy.arange, numpy.limspace,numpy.logspace
  • NumPy- Indexing & Slicing
  • NumPy- Advanced Indexing- Boolean
  • Array Indexing, Integer Indexing
  • NumPy- Broadcasting
  • NumPy- Iterating over Array- nditer, Iteration Order, Modifying Array Values, External Loop, Broadcasting Iteration
  • NumPy- Array Manipulation-Changing Shape, Transpose Operations, Changing Dimensions, Joining Arrays, Splitting Arrays, Adding/Removing Elements
  • NumPy- Binary Operators
  • NumPy- String Functions
  • NumPy- Mathematical functions
  • NumPy- Arithmetic Operations
  • NumPy- Statistical Functions
  • NumPy- Sort, Search & Counting Functions
  • NumPy- Copies & Views
  • NumPy- Matrix Library
  • NumPy- Linear Algebra
  • I/O with NumPy
  • Installation
  • Introduction to data structures in Pandas: Series, Data Frame and
  • Operations on a Series:head,tail,vector operations
  • Data Frame operations: create, display, iteration, select column, add column, delete column
  • Binary operations in a Data Frame: add, sub, mul, div, radd, rsub
  • Matching and broadcasting operations
  • Missing data and filling values.
  • Comparisons, Boolean reductions, comparing Series, and combining Data Frames
  • Transfer data between CSV files/SQL databases, and Data Frame objects
  • Advanced operations on Data Frames: pivoting, sorting, and aggregation,
  • GroupBy- Split Data into Groups, View Groups, Iterating through Groups, Select a Group.
  • Aggregations -Multiple Aggregation, Filtration; Categorical Data, Indexing and Selecting Data
  • Descriptive statistics: min, max, mode, mean, count, sum, median, quartile, var
  • Create a histogram, and quantiles.
  • Function Application: pipe, apply, aggregation, transform and apply map
  • Function Applicaton- Tablewise , Row or Column-wise Function Application, Element-wise Function Application
  • ReIndexing - Reindexing, Reindex to Align with Other Objects, Filling while Reindexing, Renaming.
  • iteration - By Label, By Actual Value
  • Working with Text Data - Data Functionality; Timedelta , and altering labels.
  • Options and Customisation- get_option(), set_option(), describe_option(), option_context();
  • Merging /Joining; concatenation IO Tools- read_csv, read_table, Comparison with SQL
  • Basic Plotting -Plot, Bar Pilot, Histograms, Box Pilots, Area Pilot, Scatter Plot, Pie Chart.
  • MATPlot Library

Course Features

  • Complimentary Life time Access to Python Online course
  • Course mentored by Industry expert
  • Project-based learning which will add stars to your resume
  • Course completion certificate
  • 1 Minor Project based on real-world applications

Course Mentor

  • Nitesh Sir, synonymous for C, C++, Data Structure and Python Training is a very seasoned trainer loved by students from last 11 years. His knowledge and delivery style for any entry level programming languages training for beginners specifically ' C, C++, Data Structure & Python ' is appreciated not only by graduates, undergraduates but by professionals also who are working on these technologies. He is the most preferred trainer of beginners.

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Course Overview

  • This course will help you to learn Python Programming Language which is basic to build Scientific Computing, Data Science, Data Analytics, Machine Learing and AI models and general purpose web applications.. The course will be mentored & guided by an Industry expert having hands-on experience in the design, development & maintenance of Java based web applications.The course includes 2 minor projects based on real-world applications with guided lab sessions.
  • It will be an online live (Live Stream) class, so you can attend this class from any geographical location. It will be an interactive live session, where you can ask your doubts to the instructor (similar to an offline classroom program).
  • Pre-requisites: Will to learn
  • Recommended for: Anyone who wants to learn and build Data Analytics/ ML/ AI Model or Python-based web applications, specifically
    • 1. College students who are looking for training in Python/ NumPy/ Pandas/ Matplotlib/ Django/ Flask
    • 2. Working Professionals who want to learn backend development with Python / Django/ Flask or Data Analytics
Online Classes
  • Live Classes option is available for SSi Digital Academy annual subscribers, Know More about annual subscription..

  • Completion Certificates
  • Lifetime access to high-quality self-paced e-learning content and live class recordings
  • Monitored assignments & projects
  • Learner assistance
INR 1000/-

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Offline Classes
  • Completion Certificates
  • Lifetime access to high-quality self-paced e-learning content and live class recordings
  • Monitored assignments & projects
  • Learner assistance
  • 4 years of unlimited access
INR 999/-

Connect with us

WhatsApp Call