Best Python course in Pune
Welcome to Tech Amplifiers, the leading platform for mastering Python programming. The Best Python course in Pune is designed to provide you with the essential skills and knowledge needed to excel in the world of coding. Whether you’re a beginner or an experienced programmer, our course offers a structured and comprehensive learning experience that will help you become proficient in Python. Join us today and unlock the potential of this versatile programming language
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Become a Python expert with our industry-leading course. Are you looking to enhance your programming skills and boost your career prospects?
Our Python course in Pune is the ideal choice for individuals who want to dive deep into the world of Python programming. With our course, you will gain a solid foundation in Python syntax, data structures, algorithms, and more. Our experienced instructors will guide you through hands-on exercises and real-world projects to ensure you develop a strong grasp of Python concepts.
What you will learn in our Python course Our Python course aims to equip you with the necessary knowledge and skills to become a proficient Python programmer. Throughout the course, you will:
Understand the fundamentals of Python programming, including variables, data types, and control structures.
Explore object-oriented programming (OOP) concepts and learn how to create classes and objects.
Dive into advanced topics such as file handling, exception handling, and regular expressions.
Gain practical experience by working on real-world projects that demonstrate your Python proficiency.
Master popular Python libraries and frameworks used in data analysis, web development, and more.
Why choose our Python course in Pune When you enroll in our Python course, you can expect the following benefits:
Expert Instructors: Learn from industry professionals with extensive experience in Python programming.
Hands-on Learning: Gain practical skills through coding exercises, quizzes, and real-world projects.
Personalized Attention: Receive individual attention and guidance from instructors to enhance your learning experience.
Industry-Relevant Curriculum: Our course is designed to meet the demands of the ever-evolving tech industry.
Career Support: Access career resources, job placement assistance, and networking opportunities to kickstart your Python career.
Python Course
- What is Python and history of Python?
- Why Python and where to use it?
- Discussion about Python 2 and Python 3
- Set up Python environment for development
- Demonstration on Python Installation
- Discuss about IDE’s like IDLE, Pycharm and Enthought Canopy
- Discussion about unique feature of Python
- Write first Python Program
- Start programming on interactive shell.
- Using Variables, Keywords
- Interactive and Programming techniques
- Comments and document interlude in Python
- Practical use cases using data analysis
- Introduction to Hadoop
- Python Core Objects and builtin functions
- Number Object and operations
- String Object and Operations
- List Object and Operations
- Tuple Object and operations
- Dictionary Object and operations
- Set object and operations
- Boolean Object and None Object
- Different data Structures, data processing
- What are conditional statements?
- How to use the indentations for defining if, else, elif block
- What are loops?
- How to control the loops
- How to iterate through the various object
- Sequence and iterable objects
- What are various type of functions
- Create UDF functions
- Parameterize UDF function, through named and unnamed parameters
- Defining and calling Function
- The anonymous Functions – Lambda Functions
- String Object functions
- List and Tuple Object functions
- Dictionary Object functions
- Process text files using Python
- Read/write and Append file object
- File object functions
- File pointer and seek the pointer
- Truncate the file content and append data
- File test operations using os.path
- Python inbuilt Modules
- os, sys, datetime, time, random, zip modules
- Create Python UDM – User Defined Modules
- Define PYTHONPATH
- Create Python Packages
- init File for package initialization
- Python Exceptions Handling
- What is Exception?
- Handling various exceptions using try….except…else
- Try-finally clause
- Argument of an Exception and create self exception class
- Python Standard Exceptions
- Raising an exceptions, User-Defined Exceptions
- Object oriented features
- Understand real world examples on OOP
- Implement Object oriented with Python
- Creating Classes and Objects, Destroying Objects
- Accessing attributes, Built-In Class Attributes
- Inheritance and Polymorphism
- Overriding Methods, Data Hiding
- Overloading Operators
- Debug Python programs using pdb debugger
- Pycharm Debugger
- Assert statement for debugging
- Testing with Python using UnitTest Framework
- What are regular expressions?
- The match and search Function
- Compile and matching
- Matching vs searching
- Search and Replace feature using RE
- Extended Regular Expressions
- Wildcard characters and work with them
- What are various type of functions
- Create UDF functions
- Parameterize UDF function, through named and unnamed parameters
- Defining and calling Function
- The anonymous Functions – Lambda Functions
- String Object functions
- List and Tuple Object functions
- Dictionary Object functions
- Process text files using Python
- Read/write and Append file object
- File object functions
- File pointer and seek the pointer
- Truncate the file content and append data
- File test operations using os.path
Python Foundation
- What is Python and history of Python?
- Why Python and where to use it?
- Discussion about Python 2 and Python 3
- Set up Python environment for development
- Demonstration on Python Installation
- Discuss about IDE’s like IDLE, Pycharm and Enthought Canopy
- Discussion about unique feature of Python
- Write first Python Program
- Start programming on interactive shell.
- Using Variables, Keywords
- Interactive and Programming techniques
- Comments and document interlude in Python
- Practical use cases using data analysis
- Introduction to Hadoop
Core Objects and Built-in Functions
- Python Core Objects and builtin functions
- Number Object and operations
- String Object and Operations
- List Object and Operations
- Tuple Object and operations
- Dictionary Object and operations
- Set object and operations
- Boolean Object and None Object
- Different data Structures, data processing
Conditional Statements and Loops
- What are conditional statements?
- How to use the indentations for defining if, else, elif block
- What are loops?
- How to control the loops
- How to iterate through the various object
- Sequence and iterable objects
UDF Functions and Object Functions
- What are various type of functions
- Create UDF functions
- Parameterize UDF function, through named and unnamed parameters
- Defining and calling Function
- The anonymous Functions – Lambda Functions
- String Object functions
- List and Tuple Object functions
- Dictionary Object functions
File Handling with Python
- Process text files using Python
- Read/write and Append file object
- File object functions
- File pointer and seek the pointer
- Truncate the file content and append data
- File test operations using os.path
Python Advance
- Python inbuilt Modules
- os, sys, datetime, time, random, zip modules
- Create Python UDM – User Defined Modules
- Define PYTHONPATH
- Create Python Packages
- init File for package initialization
Exceptional Handing and Object-Oriented Python
- Python Exceptions Handling
- What is Exception?
- Handling various exceptions using try….except…else
- Try-finally clause
- Argument of an Exception and create self exception class
- Python Standard Exceptions
- Raising an exceptions, User-Defined Exceptions
- Object oriented features
- Understand real world examples on OOP
- Implement Object oriented with Python
- Creating Classes and Objects, Destroying Objects
- Accessing attributes, Built-In Class Attributes
- Inheritance and Polymorphism
- Overriding Methods, Data Hiding
- Overloading Operators
Debugging, Framework & Regular expression
- Debug Python programs using pdb debugger
- Pycharm Debugger
- Assert statement for debugging
- Testing with Python using UnitTest Framework
- What are regular expressions?
- The match and search Function
- Compile and matching
- Matching vs searching
- Search and Replace feature using RE
- Extended Regular Expressions
- Wildcard characters and work with them
Database interaction with Python
- What are various type of functions
- Create UDF functions
- Parameterize UDF function, through named and unnamed parameters
- Defining and calling Function
- The anonymous Functions – Lambda Functions
- String Object functions
- List and Tuple Object functions
- Dictionary Object functions
Package Installation, Windows spreadsheet parsing and webpage scrapping
- Process text files using Python
- Read/write and Append file object
- File object functions
- File pointer and seek the pointer
- Truncate the file content and append data
- File test operations using os.path
What our Students say
FAQ'S
Among the various programming languages available in the market, Python has made its way to become one of the fastest-growing languages.
Python Interview Questions for Freshers
- What is Python? What are the benefits of using Python
- What is a dynamically typed language?
- What is an Interpreted language?
- What is PEP 8 and why is it important?
- What is Scope in Python?
- What are lists and tuples? What is the key difference between the two?
- What are the common built-in data types in Python?
- What is pass in Python?
- What are modules and packages in Python?
- What are global, protected and private attributes in Python?
1. What is Python? What are the benefits of using Python
Python is a high-level, interpreted, general-purpose programming language. Being a general-purpose language, it can be used to build almost any type of application with the right tools/libraries. Additionally, python supports objects, modules, threads, exception-handling, and automatic memory management which help in modelling real-world problems and building applications to solve these problems.
Benefits of using Python:
- Python is a general-purpose programming language that has a simple, easy-to-learn syntax that emphasizes readability and therefore reduces the cost of program maintenance. Moreover, the language is capable of scripting, is completely open-source, and supports third-party packages encouraging modularity and code reuse.
- Its high-level data structures, combined with dynamic typing and dynamic binding, attract a huge community of developers for Rapid Application Development and deployment.
2. What is a dynamically typed language?
Before we understand a dynamically typed language, we should learn about what typing is. Typing refers to type-checking in programming languages. In a strongly-typed language, such as Python, “1” + 2 will result in a type error since these languages don’t allow for “type-coercion” (implicit conversion of data types). On the other hand, a weakly-typed language, such as Javascript, will simply output “12” as result.
Type-checking can be done at two stages –
- Static – Data Types are checked before execution.
- Dynamic – Data Types are checked during execution.
Python is an interpreted language, executes each statement line by line and thus type-checking is done on the fly, during execution. Hence, Python is a Dynamically Typed Language.
3. What is an Interpreted language?
An Interpreted language executes its statements line by line. Languages such as Python, Javascript, R, PHP, and Ruby are prime examples of Interpreted languages. Programs written in an interpreted language runs directly from the source code, with no intermediary compilation step.
4. What is PEP 8 and why is it important?
PEP stands for Python Enhancement Proposal. A PEP is an official design document providing information to the Python community, or describing a new feature for Python or its processes. PEP 8 is especially important since it documents the style guidelines for Python Code. Apparently contributing to the Python open-source community requires you to follow these style guidelines sincerely and strictly.
5. What is Scope in Python?
Every object in Python functions within a scope. A scope is a block of code where an object in Python remains relevant. Namespaces uniquely identify all the objects inside a program. However, these namespaces also have a scope defined for them where you could use their objects without any prefix. A few examples of scope created during code execution in Python are as follows:
- A local scope refers to the local objects available in the current function.
- A global scope refers to the objects available throughout the code execution since their inception.
- A module-level scope refers to the global objects of the current module accessible in the program.
- An outermost scope refers to all the built-in names callable in the program. The objects in this scope are searched last to find the name referenced.
Note: Local scope objects can be synced with global scope objects using keywords such as global.
6. What are lists and tuples? What is the key difference between the two?
Lists and Tuples are both sequence data types that can store a collection of objects in Python. The objects stored in both sequences can have different data types. Lists are represented with square brackets ['sara', 6, 0.19], while tuples are represented with parantheses ('ansh', 5, 0.97).
But what is the real difference between the two? The key difference between the two is that while lists are mutable, tuples on the other hand are immutable objects. This means that lists can be modified, appended or sliced on the go but tuples remain constant and cannot be modified in any manner. You can run the following example on Python IDLE to confirm the difference:
my_tuple = ('sara', 6, 5, 0.97)
my_list = ['sara', 6, 5, 0.97]
print(my_tuple[0]) # output => 'sara'
print(my_list[0]) # output => 'sara'
my_tuple[0] = 'ansh' # modifying tuple => throws an error
my_list[0] = 'ansh' # modifying list => list modified
print(my_tuple[0]) # output => 'sara'
print(my_list[0]) # output => 'ansh'7. What are the common built-in data types in Python?
There are several built-in data types in Python. Although, Python doesn’t require data types to be defined explicitly during variable declarations type errors are likely to occur if the knowledge of data types and their compatibility with each other are neglected. Python provides type() and isinstance() functions to check the type of these variables. These data types can be grouped into the following categories-
- None Type:
Nonekeyword represents the null values in Python. Boolean equality operation can be performed using these NoneType objects.
| Class Name | Description |
|---|---|
| NoneType | Represents the NULL values in Python. |
- Numeric Types:
There are three distinct numeric types – integers, floating-point numbers, and complex numbers. Additionally, booleans are a sub-type of integers.
| Class Name | Description |
|---|---|
| int | Stores integer literals including hex, octal and binary numbers as integers |
| float | Stores literals containing decimal values and/or exponent signs as floating-point numbers |
| complex | Stores complex numbers in the form (A + Bj) and has attributes: real and imag |
| bool | Stores boolean value (True or False). |
Note: The standard library also includes fractions to store rational numbers and decimal to store floating-point numbers with user-defined precision.
- Sequence Types:
According to Python Docs, there are three basic Sequence Types – lists, tuples, and range objects. Sequence types have theinandnot inoperators defined for their traversing their elements. These operators share the same priority as the comparison operations.
| Class Name | Description |
|---|---|
| list | Mutable sequence used to store collection of items. |
| tuple | Immutable sequence used to store collection of items. |
| range | Represents an immutable sequence of numbers generated during execution. |
| str | Immutable sequence of Unicode code points to store textual data. |
Note: The standard library also includes additional types for processing:
1. Binary data such as bytearray bytes memoryview , and
2. Text strings such as str.
- Mapping Types:
A mapping object can map hashable values to random objects in Python. Mappings objects are mutable and there is currently only one standard mapping type, the dictionary.
| Class Name | Description |
|---|---|
| dict | Stores comma-separated list of key: value pairs |
- Set Types:
Currently, Python has two built-in set types – set and frozenset. set type is mutable and supports methods likeadd()andremove(). frozenset type is immutable and can’t be modified after creation.
| Class Name | Description |
|---|---|
| set | Mutable unordered collection of distinct hashable objects. |
| frozenset | Immutable collection of distinct hashable objects. |
Note: set is mutable and thus cannot be used as key for a dictionary. On the other hand, frozenset is immutable and thus, hashable, and can be used as a dictionary key or as an element of another set.
- Modules:
Module is an additional built-in type supported by the Python Interpreter. It supports one special operation, i.e., attribute access:mymod.myobj, wheremymodis a module and myobj references a name defined in m’s symbol table. The module’s symbol table resides in a very special attribute of the module __dict__, but direct assignment to this module is neither possible nor recommended. - Callable Types:
Callable types are the types to which function call can be applied. They can be user-defined functions, instance methods, generator functions, and some other built-in functions, methods and classes.
the callable types.
