Python With Data Science

Training Mode Regular Fastrack Crash
Classroom | Online 6 Months

(M,W,F or T,T,S Class)

(3 Class in a week)

4 Months

(Monday to Friday Class)

(5 Class in a week)

2 Months

(Monday to Friday Class)

(5 Class in a week 1:30 hour duration)

The Advance Python Expert Course at Next G Classes is meticulously crafted for individuals aiming to master both foundational and advanced aspects of Python programming, as well as dive into the dynamic field of data science. This comprehensive program is divided into two modules, each targeting essential skills and knowledge areas.

Module 1: Python Basic Course & Python Advance Course This module starts with the essentials of Python programming, ensuring a solid understanding of core concepts. Participants learn the basics of Python, covering syntax, data types, control structures, functions, and modules. As the course progresses, the curriculum delves into advanced Python topics, including object-oriented programming, file handling, exception handling, and advanced data structures. This rigorous module equips students with the skills needed to write efficient and scalable Python code, laying a strong foundation for more complex applications and developments.

Module 2: Data Science In the second module, participants transition to the exciting realm of data science. The module begins with SQL, an essential tool for data manipulation and database management. Participants learn how to query databases, manage data, and perform complex data operations using SQL. Building on this, the course covers key data science concepts such as data cleaning, data analysis, and data visualization. Students gain hands-on experience with data science libraries and tools, applying their skills to real-world datasets and projects.

Throughout the Advance Python Expert Course at Next G Classes, a blend of theoretical knowledge and practical application ensures that participants gain comprehensive expertise. By the end of the course, graduates are proficient in Python programming and well-versed in data science techniques, ready to tackle challenging roles in the tech industry.

WHO CAN JOIN Python With Data Science
  • 10th, 12th or Equivalent
  • BCA/MCA, B.Tech, M.Tech, B.sc (IT), B.sc(CS)
  • Diploma Candidates

Module-1 COURSE DETAILS

Introduction to Languages

  • What is Language?
  • Types of languages
  • Introduction to Translators
  • Compiler
  • Interpreter
  • What is Scripting Language?
  • Types of Script
  • Programming Languages v/s Scripting Languages
  • Difference between Scripting and Programming languages
  • What is programming paradigm?
  • Procedural programming paradigm
  • Object Oriented Programming paradigm
Introduction to Python
  • WHY PYTHON?
  • History
  • Features – Dynamic, Interpreted, Object oriented, Embeddable, Extensible, Large standard libraries, Free and Open source
  • Why Python is General Language?
  • Limitations of Python
  • What is PSF?
  • Python implementations
  • Python applications
  • Python versions
  • PYTHON IN REALTIME INDUSTRY
  • Difference between Python 2.x and 3.x
  • Difference between Python 3.7 and 3.8
  • Software Development Architectures

Python Software’s

  • Python Distributions
  • Download &Python Installation Process in Windows, Unix, Linux and Mac
  • Online Python IDLE
  • Python Real-time IDEs like Spyder, Jupyter Note Book, PyCharm, Rodeo, Visual Studio Code, ATOM, PyDevetc
  • Python Language Fundamentals

Operators

  • Arithmetic Operators
  • Comparison Operators
  • Python Assignment Operators
  • Logical Operators
  • Bitwise Operators
  • Shift operators
  • Membership Operators
  • Identity Operators
  • Ternary Operator
  • Operator precedence
  • Difference between “is” vs “==”
  • Input & Output Operators
  • Print
  • Input
  • Command-line arguments

Control Statements

  • Conditional control statements
  • If
  • If-else
  • If-elif-else
  • Nested-if
  • Loop control statements
  • for
  • while
  • Nested loops
  • Branching statements
  • Break
  • Continue
  • Pass
  • Return
  • Case studies


Data Structures or Collections

  • Introduction
  • Importance of Data structures
  • Applications of Data structures
  • Types of Collections
  • Sequence
  • Strings, List, Tuple, range
  • Non sequence
  • Set, Frozen set, Dictionary
  • Strings
  • What is string
  • Representation of Strings
  • Processing elements using indexing
  • Processing elements using Iterators
  • Manipulation of String using Indexing and Slicing
  • String operators
  • Methods of String object
  • String Formatting
  • String functions
  • String Immutability
  • Case studies


List Collection

  • What is List
  • Need of List collection
  • Different ways of creating List
  • List comprehension
  • List indices
  • Processing elements of List through Indexing and Slicing
  • List object methods
  • List is Mutable
  • Mutable and Immutable elements of List
  • Nested Lists
  • List_of_lists
  • Hardcopy, shallowCopy and DeepCopy
  • zip() in Python
  • How to unzip?
  • Python Arrays:
  • Case studies

Tuple Collection

  • What is tuple?
  • Different ways of creating Tuple
  • Method of Tuple object
  • Tuple is Immutable
  • Mutable and Immutable elements of Tuple
  • Process tuple through Indexing and Slicing
  • List v/s Tuple
  • Case studies

Set Collection

  • What is set?
  • Different ways of creating set
  • Difference between list and set
  • Iteration Over Sets
  • Accessing elements of set
  • Python Set Methods
  • Python Set Operations
  • Union of sets
  • functions and methods of set
  • Python Frozen set
  • Difference between set and frozenset ?
  • Case study


Dictionary Collection

  • What is dictionary?
  • Difference between list, set and dictionary
  • How to create a dictionary?
  • PYTHON HASHING?
  • Accessing values of dictionary
  • Python Dictionary Methods
  • Copying dictionary
  • Updating Dictionary
  • Reading keys from Dictionary
  • Reading values from Dictionary
  • Reading items from Dictionary
  • Delete Keys from the dictionary
  • Sorting the Dictionary
  • Python Dictionary Functions and methods
  • Dictionary comprehension

Functions

  • What is Function?
  • Advantages of functions
  • Syntax and Writing function
  • Calling or Invoking function
  • Classification of Functions
  • No arguments and No return values
  • With arguments and No return values
  • With arguments and With return values
  • No arguments and With return values
  • Recursion
  • Python argument type functions :
  • Default argument functions
  • Required(Positional) arguments function
  • Keyword arguments function
  • Variable arguments functions
  • pass’ keyword in functions
  • Lambda functions/Anonymous functions
  • map()
  • filter()
  • reduce()
  • Nested functions
  • Non local variables, global variables
  • Closures
  • Decorators
  • Generators
  • Iterators
  • Monkey patching

Module 1: Introduction to SQL

  • Duration: 1 Month
  1. Overview of Databases

    • Understanding databases and their importance
    • Types of databases: Relational vs. Non-relational
  2. Introduction to SQL

    • What is SQL?
    • History and evolution of SQL
    • SQL syntax and conventions
  3. Basic SQL Commands

    • SELECT, INSERT, UPDATE, DELETE
    • Understanding data types
  4. Database Schema

    • Tables, rows, and columns
    • Primary keys and foreign keys
    • Creating and modifying database schemas
  5. Hands-on Practice

    • Setting up a local SQL environment
    • Basic query exercises

Module 2: Intermediate SQL

  • Duration: 2 Months
  1. Advanced Querying Techniques

    • WHERE clause and filtering data
    • Using aliases for tables and columns
    • Sorting results with ORDER BY
  2. Joins and Subqueries

    • INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN
    • Subqueries and nested queries
    • UNION, INTERSECT, and EXCEPT
  3. Aggregate Functions and Grouping

    • COUNT, SUM, AVG, MIN, MAX
    • GROUP BY and HAVING clauses
  4. Data Manipulation

    • Bulk inserts and updates
    • Transactions and rollbacks
    • Indexing for performance optimization
  5. Hands-on Practice

    • Complex query exercises
    • Real-world database scenarios

Module 3: Advanced SQL

  • Duration: 2 Months
  1. Stored Procedures and Functions

    • Creating and using stored procedures
    • User-defined functions
  2. Triggers and Views

    • Creating and managing triggers
    • Using views for simplified querying
  3. Performance Tuning and Optimization

    • Query optimization techniques
    • Indexing strategies
    • Analyzing query performance with EXPLAIN
  4. Database Security

    • User roles and permissions
    • Encryption and data protection
    • Best practices for securing databases
  5. Data Warehousing and Analytics

    • Introduction to data warehousing
    • Using SQL for data analysis and reporting
  6. Hands-on Practice

    • Creating and using stored procedures and triggers
    • Performance tuning exercises
    • Data analysis projects

Module 4: SQL for Specific Databases

  • Duration: 1 Month
  1. SQL in Different Database Management Systems

    • Differences in SQL syntax across MySQL, PostgreSQL, SQL Server, Oracle
  2. Advanced Features in Specific DBMS

    • MySQL: Advanced indexing, full-text search
    • PostgreSQL: Window functions, JSON support
    • SQL Server: Advanced security features, SQL CLR
    • Oracle: PL/SQL, advanced transaction control
  3. Database Migration and Integration

    • Techniques for migrating databases
    • Integrating SQL with other programming languages and tools
  4. Hands-on Practice

    • Working with different DBMS
    • Database migration projects
    • Integration exercises

Module: 1

  • Importance of modular programming
  • What is module
  • Types of Modules – Pre defined, User defined.
  • User defined modules creation
  • Functions based modules
  • Class based modules
  • Connecting modules
  • Import module
  • From … import
  • Module alias / Renaming module
  • Built In properties of module
Module: 2 Packages

  • Organizing python project into packages
  • Types of packages – pre defined, user defined.
  • Package v/s Folder
  • py file
  • Importing package
  • PIP
  • Introduction to PIP
  • Installing PIP
  • Installing Python packages
  • Un installing Python packages
Module: 3 OOPS

  • Procedural v/s Object oriented programming
  • Principles of OOP – Encapsulation , Abstraction (Data Hiding)
  • Classes and Objects
  • How to define class in python
  • Types of variables – instance variables, class variables.
  • Types of methods – instance methods, class method, static method
  • Object initialization
  • ‘self’ reference variable
  • ‘cls’ reference variable
  • Access modifiers – private(__) , protected(_), public
  • AT property class
  • Property() object
  • Creating object properties using setaltr, getaltr functions
  • Encapsulation(Data Binding)
  • What is polymorphism?

Module: 4 Overriding

  • Method overriding
  • Constructor overriding
Overloading
  •   Method Overloading
  •   Constructor Overloading
Operator Overloading
  • Class re-usability
  • Composition
  • Aggregation
  • Inheritance – single , multi level, multiple, hierarchical and hybrid inheritance and Diamond inheritance
  • Constructors in inheritance
  • Object class
  • super()
  • Runtime polymorphism
  • Method overriding
  • Method resolution order(MRO)
  • Method overriding in Multiple inheritance and Hybrid Inheritance
  • Duck typing
  • Concrete Methods in Abstract Base Classes
  • Difference between Abstraction & Encapsulation
  • Inner classes
  • Introduction
  • Writing inner class
  • Accessing class level members of inner class
  • Accessing object level members of inner class
  • Local inner classes
  • Complex inner classes
  • Case studies
Module: 5

Regular expressions

  • Understanding regular expressions
  • String v/s Regular expression string
  • “re” module functions
  • Match()
  • Search()
  • Split()
  • Findall()
  • Compile()
  • Sub()
  • Subn()
  • Expressions using operators and symbols
  • Simple character matches
  • Special characters
  • Character classes
  • Mobile number extraction
  • Mail extraction
  • Different Mail ID patterns
  • Data extraction
  • Password extraction
  • URL extraction
  • Vehicle number extraction
  • Case study
Module: 7

File &Directory handling

  • Introduction to files
  • Opening file
  • File modes
  • Reading data from file
  • Writing data into file
  • Appending data into file
  • Line count in File
  • CSV module
  • Creating CSV file
  • Reading from CSV file
  • Writing into CSV file
  • Object serialization – pickle module
  • XML parsing
  • JSON parsing
Module: 8

Date & Time module

  • How to use Date & Date Time class
  • How to use Time Delta object
  • Formatting Date and Time
  • Calendar module
  • Text calendar
  • HTML calendar

OS module

  • Shell script commands
  • Various OS operations in Python
  • Python file system shell methods
  • Creating files and directories
  • Removing files and directories
  • Shutdown and Restart system
  • Renaming files and directories
  • Executing system commands
Module: 9

Multi-threading & Multi Processing

  • Introduction
  • Multi-tasking v/s Multi-threading
  • Threading module
  • Creating thread – inheriting Thread class , Using callable object
  • Life cycle of thread
  • Single threaded application
  • Multi-threaded application
  • Can we call run() directly?
  • Need to start() method
  • Sleep()
  • Join()
  • Synchronization – Lock class – acquire(), release() functions
  • Case studies

Garbage collection

  • Introduction
  • Importance of Manual garbage collection
  • Self-reference objects garbage collection
  • ‘gc’ module
  • Collect() method
  • Threshold function
  • Case studies
Module: 10

Python Data Base Communications (PDBC)

  • Introduction to DBMS applications
  • File system v/s DBMS
  • Communicating with MySQL
  • Python – MySQL connector
  • connector module
  • connect() method
  • Oracle Database
  • Install cx_Oracle
  • Cursor Object methods
  • execute() method
  • executeMany() method
  • fetchone()
  • fetchmany()
  • fetchall()
  • Static queries v/s Dynamic queries
  • Transaction management
  • Case studies
Module: 11

Python – Network Programming

  • What is Sockets?
  • What is Socket Programming?
  • The socket Module
  • Server Socket Methods
  • Connecting to a server
  • A simple server-client program
  • Server
  • Client
Module: 12

Tkinter & Turtle

  • Introduction to GUI programming
  • Tkinter module
  • Tk class
  • Components / Widgets
  • Label , Entry , Button , Combo, Radio
  • Types of Layouts
  • Handling events
  • Widgets properties
  • Case studies

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One year free class retake facility provides an opportunity to retake class at No Cost as per your convenience. Because at our institute our aim is to enhance the concepts of every student’s, after provide in-depth knowledge of every software’s, languages etc.

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