PYTHON CORE/ADVANCED

About Python

Python is a high-level, general-purpose programming language that is widely used in the software industry. It was first released in 1991 and has since become one of the most popular programming languages in the world, due to its simplicity, flexibility, and versatility.

One of the main features of Python is its simplicity and readability. The language is designed to be easy to learn and use, with a syntax that is simple and intuitive. This makes it an excellent choice for beginners who are just starting to learn programming.

Python is also a very flexible and versatile language. It can be used for a wide range of applications, including web development, scientific computing, data analysis, and artificial intelligence. Additionally, Python has a large and active community of developers and users, which means that there is a wealth of libraries, frameworks, and tools available for use.

One of the key benefits of Python is its scalability. It is used by companies of all sizes, from small start ups to large enterprises. It is also used in a variety of industries, including finance, healthcare, and retail.

One of the main reasons for Python's popularity is its use in data science and machine learning. Python has a number of libraries and frameworks specifically designed for data analysis and machine learning, such as NumPy, Pandas, and scikit-learn. This has made it a popular choice for data scientists and machine learning engineers.

Overall, Python is a powerful and widely-used programming language that is known for its simplicity, flexibility, and versatility. It is an excellent choice for beginners who are just starting to learn programming, as well as for experienced developers who are looking for a language that can be used for a wide range of applications.

Top 10 Reason Why We Should Learn Python

1. 1. Simplicity and readability:  Python is known for its simple and intuitive syntax, which makes it easy to learn and use. This is especially beneficial for beginners who are just starting to learn programming.


2. 2. Flexibility and versatility:  Python can be used for a wide range of applications, including web development, scientific computing, data analysis, and artificial intelligence.


3. 3. Large and active community:  Python has a large and active community of developers and users, which means that there is a wealth of libraries, frameworks, and tools available for use


4. 4. Widely used in industry:  Python is used by companies of all sizes and in a variety of industries, including finance, healthcare, and retail.


5. 5. Excellent for data science and machine learning:   Python has a number of libraries and frameworks specifically designed for data analysis and machine learning, such as NumPy, Pandas, and scikit-learn.


6. 6. Good for prototyping:  Python's simplicity and flexibility make it a good choice for prototyping and testing out ideas


7. 7. High-paying jobs:  Python is a popular language in the tech industry and knowing it can lead to high-paying jobs with good job security.


8. 8. Excellent for web development:  Python has a number of frameworks and libraries specifically designed for web development, such as Django and Flask.


9. 9. Can be used on multiple platforms:  Python can be used on multiple platforms, including Windows, Mac, and Linux, making it a versatile choice.


10. 10. Strong support for education:  Python is often used in educational settings and there is a strong emphasis on supporting and promoting the use of Python in education.

Features of Python

Python is a high-level, general-purpose programming language that is widely used in the software industry. It was first released in 1991 and has since become one of the most popular programming languages in the world, due to its simplicity, flexibility, and versatility. Here are some of the key features of Python:

1. 1. Simplicity and readability:  Python is known for its simple and intuitive syntax, which makes it easy to learn and use. This is especially beneficial for beginners who are just starting to learn programming


2. 2. Flexibility and versatility:  Python can be used for a wide range of applications, including web development, scientific computing, data analysis, and artificial intelligence. It also has a large and active community of developers and users, which means that there is a wealth of libraries, frameworks, and tools available for use.


3. 3. Object-oriented programming:  Python is an object-oriented programming language, which means that it is based on the concept of "objects" that contain data and code. This makes it easier to model real-world concepts and create reusable code.


4. 4. Dynamically-typed: Python:  Python is a dynamically-typed language, which means that the data type of a variable is determined at runtime, rather than at the time of writing the code. This can make it easier to write code quickly, but it can also lead to some potential errors that may not be detected until runtime.


5. 5. High-level:  Python is a high-level language, which means that it is abstracted from the details of the computer's hardware and operating system. This makes it easier to write and maintain code, but it can also make it slower than some other languages.


6. 6. Automatic memory management:  Python has automatic memory management, which means that the programmer does not have to worry about allocating and freeing up memory. This can make it easier to write efficient and stable code.


7. 7. Support for multiple programming paradigms:  Python supports multiple programming paradigms, including object-oriented, imperative, and functional programming. This makes it a flexible choice for a wide range of applications.


8. 8. Extensive standard library:  Python has a large and comprehensive standard library, which means that it comes with a wide range of built-in functions and modules that can be used for a variety of tasks. This can make it easier to get started with programming in Python


9. 9. Good for prototyping:  Python's simplicity and flexibility make it a good choice for prototyping and testing out ideas.


10. 10. Widely used:  Python is used by companies of all sizes and in a variety of industries, including finance, healthcare, and retail. It is also popular for use in data science and machine learning.

Overall, Python is a powerful and widely-used programming language that is known for its simplicity, flexibility, and versatility. It is an excellent choice for beginners who are just starting to learn programming, as well as for experienced developers who are looking for a language that can be used for a wide range of applications.

Application of Python

Python is a versatile programming language that can be used for a wide range of applications. Some common areas where Python is used include:

1. 1. Web development:  Python has a number of frameworks and libraries specifically designed for web development, such as Django and Flask. These frameworks make it easy to build and deploy web applications.


2. 2. Scientific computing:  Python is widely used in scientific computing, due to its support for numerical and scientific computing libraries, such as NumPy and SciPy.


3. 3. Data analysis:  Python has a number of libraries and tools specifically designed for data analysis, such as Pandas and scikit-learn. It is a popular choice for data scientists and analysts.


4. 4. Artificial intelligence:  Python has a number of libraries and frameworks specifically designed for artificial intelligence and machine learning, such as TensorFlow and PyTorch.


5. 5. Desktop applications:  Python can be used to develop desktop applications, using frameworks such as PyQt or PyGTK.


6. 6. Networking:  Python has a number of libraries and modules specifically designed for networking, such as sockets and twisted.


7. 7. Games:  Python can be used to develop games, using frameworks such as Pygame.


8. 8. Automation:  Python can be used to automate tasks, such as web scraping and data processing.

Overall, Python is a versatile language that can be used for a wide range of applications, including web development, scientific computing, data analysis, artificial intelligence, desktop applications, networking, games, and automation.

Career Opportunity After Python

There are many career opportunities available for individuals who have learned Python, a popular programming language known for its simplicity and versatility. Some examples of roles that may be open to individuals with Python skills include:

1. 1. Data Scientist:  Python is a popular language for data analysis and machine learning, so data scientists who know Python may have an advantage in the job market.


2. 2. Software Developer:  Python is often used for developing web applications, so developers who know Python may have an advantage in finding work in this field.


3. 3. DevOps Engineer:  Python is often used for automating tasks and building tools to aid in software development and deployment, so DevOps engineers with Python skills may be in high demand.


4. 4. Data Engineer:  Python is a useful tool for building and maintaining data pipelines, so data engineers with Python skills may be sought after by employers.


5. 5. Financial Analyst:  Many financial firms use Python for data analysis and trading, so analysts with Python skills may have an advantage in this field.

Overall, Python is a widely-used programming language with many applications, so individuals who have learned Python may have a range of career opportunities available to them.

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Course Syllabus

• Syllabus
• Duration
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• •   INTRODUCTION TO PYTHON
  • WHY PYTHON
  • APPLICATION AREAS OF PYTHON
  • PYTHON IMPLEMENTATIONS
  • PYTHON COMPILER
  • PYTHON VERSIONS
  • INSTALLING PYTHON
  • PYTHON INTERPRETER ARCHITECTURE
  • PYTHON BYTE CODE COMPILER
  • PYTHON VIRTUAL MACHINE(PVM)
• •   WRITING AND EXECUTING FIRST PYTHON PROGRAM
  • USING INTERACTIVE MODE
  • USING SCRIPT MODE
  • UNDERSTANDING PRINT() FUNCTION
  • HOW TO COMPILE PYTHON PROGRAM EXPLICITLY
• •   PYTHON LANGUAGE FUNDAMENTALS
  • CHARACTER SET
  • KEYWORDS
  • COMMENTS
  • VARIABLES
  • LITERALS
  • OPERATORS
  • READING INPUT FROM CONSOLE
  • PARSING STRING TO INT, flOAT
• •   PYTHON CONDITIONAL STATEMENTS
  • IF STATEMENT
  • IF ELSE STATEMENT
  • IF ELIF STATEMENT
  • IF ELIF ELSE STATEMENT
  • NESTED IF STATEMENT
• •   LOOPING STATEMENTS
  • WHILE LOOP
  • FOR LOOP
  • NESTED LOOPS
  • PASS, BREAK AND CONTINUE KEYWORDS
• •   STANDARD DATA TYPES
  • INT, flOAT, COMPLEX, BOOL, NONETYPE
  • STR, LIST, TUPLE, RANGE
  • DICT, SET, FROZENSET
• •   STRING HANDLING
  • WHAT IS STRING
  • STRING REPRESENTATIONS
  • UNICODE STRING
  • STRING FUNCTIONS, METHODS
  • STRING INDEXING AND SLICING
  • STRING FORMATTING
• •   PYTHON TUPLE
  • CREATING TUPLE
  • ACCESSING TUPLE
  • IMMUTABILITY OF TUPLE
• •   PYTHON SET
  • HOW TO CREATE A SET
  • ITERATION OVER SETS
  • PYTHON SET METHODS
  • PYTHON FROZENSET
• •   PYTHON DICTIONARY
  • CREATING A DICTIONARY
  • DICTIONARY METHODS
  • ACCESSING VALUES FROM DICTIONARY
  • UPDATING DICTIONARY
  • ITERATING DICTIONARY
  • DICTIONARY COMPREHENSION
• •   PYTHON FUNCTIONS
  • DEfiNING A FUNCTION
  • CALLING A FUNCTION
  • TYPES OF FUNCTIONS
  • FUNCTION ARGUMENTS
  • POSITIONAL ARGUMENTS, KEYWORD ARGUMENTS
  • DEFAULT ARGUMENTS, NON-DEFAULT ARGUMENTS
  • ARBITRARY ARGUMENTS, KEYWORD ARBITRARY ARGUMENTS
  • FUNCTION RETURN STATEMENT
  • NESTED FUNCTION
  • FUNCTION AS ARGUMENT
  • FUNCTION AS RETURN STATEMENT
  • DECORATOR FUNCTION
  • CLOSURE
  • MAP(), fiLTER(), REDUCE(), ANY() FUNCTIONS
  • ANONYMOUS OR LAMBDA FUNCTION
• •   MODULES & PACKAGES
  • WHY MODULES
  • SCRIPT V/S MODULE
  • IMPORTING MODULE
  • STANDARD V/S THIRD PARTY MODULES
  • WHY PACKAGES
  • UNDERSTANDING PIP UTILITY
• •   FILE I/O
  • INTRODUCTION TO fiLE HANDLING
  • FILE MODES
  • FUNCTIONS AND METHODS RELATED TO fiLE HANDLING
  • UNDERSTANDING WITH BLOCK
• •   OBJECT ORIENTED PROGRAMMING
  • PROCEDURAL V/S OBJECT ORIENTED PROGRAMMING
  • OOP PRINCIPLES
  • DEfiNING A CLASS & OBJECT CREATION
  • OBJECT ATTRIBUTES
  • INHERITANCE
  • ENCAPSULATION
  • POLYMORPHISM
• •   EXCEPTION HANDLING
  • DIffERENCE BETWEEN SYNTAX ERRORS AND EXCEPTIONS
  • KEYWORDS USED IN EXCEPTION HANDLING
  • TRY, EXCEPT, fiNALLY, RAISE, ASSERT
  • TYPES OF EXCEPT BLOCKS
• •   REGULAR EXPRESSIONS(REGEX)
  • NEED OF REGULAR EXPRESSIONS
  • RE MODULE
  • FUNCTIONS /METHODS RELATED TO REGEX
  • META CHARACTERS & SPECIAL SEQUENCES
• •   MULTI-THREADING PROGRAMMING
  • MULTI-PROCESSING V/S MULTI-THREADING
  • NEED OF THREADS
  • CREATING CHILD THREADS
  • FUNCTIONS /METHODS RELATED TO THREADS
  • THREAD SYNCHRONIZATION AND LOCKING
• •   SQL INTRODUCTION TO DATABASE
  • DATABASE CONCEPTS
  • WHAT IS DATABASE PACKAGE?
  • UNDERSTANDING DATA STORAGE
  • RELATIONAL DATABASE (RDBMS) CONCEPT
• •   SQL (STRUCTURED QUERY LANGUAGE)
  • SQL BASICS
  • DML, DDL & DQL
  • DDL: CREATE, ALTER, DROP
  • SQL CONSTRAINTS:
  • NOT NULL, UNIQUE,
  • PRIMARY & FOREIGN KEY, COMPOSITE KEY
  • CHECK, DEFAULT
  • DML: INSERT, UPDATE, DELETE AND MERGE
  • DQL : SELECT
  • SELECT DISTINCT
  • SQL WHERE
  • SQL OPERATORS
  • SQL LIKE
  • SQL ORDER BY
  • SQL ALIASES
  • SQL VIEWS
  • SQL JOINS
  • INNER JOIN
  • LEFT (OUTER) JOIN
  • RIGHT (OUTER) JOIN
  • FULL (OUTER) JOIN
  • MYSQL FUNCTIONS
  • STRING FUNCTIONS
  • CHAR_LENGTH
  • CONCAT
  • LOWER
  • REVERSE
  • UPPER
  • NUMERIC FUNCTIONS
  • MAX, MIN, SUM
  • AVG, COUNT, ABS
  • DATE FUNCTIONS
  • CURDATE
  • CURTIME
  • NOW
• •   PYTHON DATABASE CONNECTIVITY
  • CREATING DATABASE CONNECTION
  • UNDERSTANDING CURSOR
  • EXECUTING QUERIES
  • PARAMETERIZED QUERIES

TYPE	DURATION	HOURS	TRAINING MODE
Regular Track	45-60 Days	2 Hours a Day	Live Classroom
Weekend Track	8 Weekends	3 Hours a Day	Live Classroom
Fast Track	7 Days	6+ Hours a Day	Live Classroom

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