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--- products:ict:python:python_course [2024/03/06 14:52] – [Payment methods accepted :] wikiadmin
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-====== Beginning python and advanced python courses by the training company. ======
-{{:course:python.jpeg?400|}}
-Physical Classroom
-{{:products:ict:python:using-computers-in-classrooms.jpg?400|}}
-Online Instructor
-{{:products:ict:python:online_instructor.jpeg?400|}}
-===== Course One: Beginning Python =====
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-Course Overview:
-This course is designed for beginners who have little to no experience with programming. Through hands-on exercises and practical examples, students will learn the fundamentals of Python programming language.
-**Class 1: Introduction to Python**
-- Overview of Python
-- Installing Python
-- Writing and executing a simple Python program
-- Understanding variables and data types
-**Class 2: Control Flow and Loops**
-- Conditional statements (if, elif, else)
-- Loops (for loops, while loops)
-- Practice exercises
-**Class 3: Lists and Tuples**
-- Understanding lists and tuples
-- Accessing elements
-- List manipulation
-- Tuple immutability
-**Class 4: Dictionaries and Sets**
-- Introduction to dictionaries and sets
-- Working with dictionary keys and values
-- Set operations
-{{:products:ict:python:money_back_1.jpg?400|}}
-**Class 5: Functions**
-- Defining and calling functions
-- Parameters and return values
-- Scope of variables
-**Class 6: Modules and Packages**
-- Understanding modules and importing them
-- Creating and using packages
-- Exploring the Python Standard Library
-**Class 7: File Handling**
-- Reading from and writing to files
-- Using context managers (with statement)
-- Error handling with try-except blocks
-**Class 8: Introduction to Object-Oriented Programming (OOP)**
-- Basics of OOP
-- Classes and objects
-- Attributes and methods
-**Class 9: Inheritance and Polymorphism**
-- Extending classes using inheritance
-- Method overriding
-- Polymorphism in Python
-**Class 10: Exception Handling**
-- Handling exceptions in detail
-- Custom exception classes
-- Best practices for exception handling
-**Class 11: Introduction to Regular Expressions**
-- Overview of regular expressions
-- Using regex in Python
-- Pattern matching
-**Class 12: Debugging and Testing**
-- Debugging techniques
-- Unit testing with unittest module
-- Test-driven development (TDD)
-{{:products:ict:python:14_days_money-back-guarantee.png?400|}}
-**Class 13: Introduction to Data Analysis with Pandas**
-- Overview of Pandas library
-- Series and DataFrame objects
-- Basic data manipulation
-**Class 14: Introduction to Data Visualization with Matplotlib**
-- Overview of Matplotlib library
-- Creating basic plots
-- Customizing plots
-**Class 15: Introduction to Web Scraping with BeautifulSoup**
-- Overview of web scraping
-- Using BeautifulSoup for scraping
-- Scraping a simple webpage
-**Class 16: Final Project**
-- Students will work on a small project to apply the knowledge gained throughout the course.
-**Course Fees ( For the course beginning python listed above ) :**
-PKR Rs 30,000
-LTC 1.1968071394641624
-NANO XN0 : 72.48828106122843
-CNY : 772.80
-USD 107.40
-==== Payment methods accepted : ====
-Cheque, Credit card, Debit card, Cash, nano, LTC, bank transfer, payoneer, NayaPay.
-**Guarantee :** If you are not satisfied by the course, then you can request your money back within 14 days of the time you started the course. The start time is of the start time of the first lecture, physical class, or online course.
-You do not have to provide any reason for requesting the money back. Feedback is optional.
-Any financial instrument, payment, transaction or bank charges required to collect and refund the money shall be deducted from the fees.
-----
-==== Course Two: Advanced Python ====
-**Prerequisite :** Completion certificate from course 1
-**Course Overview:**
-This course is designed for students who are already familiar with the basics of Python programming. It
-covers advanced topics and techniques to enhance students' Python skills.
-(Note: Topics assume familiarity with the basics covered in Course One)
-**Class 1: Advanced Data Structures**
-- Collections module
-- Named tuples
-- Default dictionaries
-- Deque
-**Class 2: Functional Programming**
-- Lambda functions
-- Map, filter, and reduce functions
-- List comprehensions
-**Class 3: Decorators**
-- Understanding decorators
-- Creating and using decorators
-- Decorator applications
-**Class 4: Generators and Iterators**
-- Understanding iterators and iterables
-- Generator functions
-- Generator expressions
-**Class 5: Context Managers**
-- Using the `with` statement in detail
-- Creating context managers using contextlib module
-- Application in file handling and resource management
-**Class 6: Concurrency with Threading**
-- Overview of threading
-- Thread creation and management
-- Synchronization and race conditions
-**Class 7: Concurrency with Multiprocessing**
-- Introduction to multiprocessing
-- Process creation and management
-- Communication between processes
-**Class 8: Asynchronous Programming with Asyncio**
-- Understanding asynchronous programming
-- Async/await syntax
-- Working with asyncio module
-**Class 9: Design Patterns**
-- Overview of design patterns
-- Singleton, Factory, and Observer patterns in Python
-**Class 10: Functional Programming Patterns**
-- Currying
-- Partial functions
-- Memoization
-**Class 11: Metaprogramming**
-- Understanding metaprogramming
-- Using metaclasses
-- Dynamic attribute and method creation
-**Class 12: Pythonic Code**
-- Writing clean and Pythonic code
-- PEP 8 guidelines
-- Code optimization techniques
-**Class 13: Advanced File Handling**
-- Working with binary files
-- Serializing Python objects
-- Working with CSV and JSON files
-**Class 14: Database Interaction with SQLAlchemy**
-- Overview of SQLAlchemy
-- ORM concepts
-- CRUD operations
-**Class 15: Web Development with Flask**
-- Introduction to Flask framework
-- Creating web applications
-- Routing and views
-**Class 16: Final Project**
-- Students will work on an advanced project to demonstrate their understanding of the advanced Python
-concepts covered in the course.
-----
-====== Python Level 1 ======
-{{:course:python.jpeg?400|}}
-This course is designed for individuals with little to no programming experience who want to learn Python, a versatile and beginner-friendly programming language. Through a combination of lectures, hands-on exercises, and projects, students will gain a solid understanding of Python syntax, data structures, control flow, functions, and basic concepts of object-oriented programming.
-Course Outline:
-===== Week 1: Introduction to Python =====
-  *     [[products:ict:python:overview_of_programming_languages|Overview of programming languages]]
-  *     [[products:ict:python:introduction_to_python_and_its_features|Introduction to Python and its features]]
-  *     [[products:ict:python:setting_up_python_environment_interpreter_ide|Setting up Python environment (interpreter, IDE)]]
-  *     [[products:ict:python:writing_and_running_your_first_python_program|Writing and running your first Python program]]
-  *      [[products:ict:python:understanding_basic_syntax_and_variables|Understanding basic syntax and variables]]
-===== Week 2: Data Types and Operators =====
-  *     [[products:ict:python:numeric_data_types_int_float_complex|Numeric data types: int, float, complex]]
-  *     [[products:ict:python:strings_and_string_manipulation|Strings and string manipulation]]
-  *     [[products:ict:python:boolean_data_type_and_logical_operators|Boolean data type and logical operators]]
-  *     [[products:ict:python:basic_arithmetic_comparison_and_assignment_operators|Basic arithmetic, comparison, and assignment operators]]
-  *     [[products:ict:python:type_conversion_and_type_casting|Type conversion and type casting]]
-===== Week 3: Control Flow =====
-  *     [[products:ict:python:conditional_statements_if_elif_else|Conditional statements: if, elif, else]]
-  *     Using logical operators with conditionals
-  *     Looping constructs: while loop, for loop
-  *     Iterating over sequences (lists, strings, tuples)
-  *     Using break and continue statements
-===== Week 4: Data Structures Part I =====
-  *     Lists: creation, indexing, slicing, appending, and extending
-  *     List methods and operations
-  *     Tuples: creation, accessing elements, immutability
-  *     Sets: creation, operations, and methods
-  *     Using list comprehensions
-===== Week 5: Data Structures Part II =====
-  *     Dictionaries: creation, accessing elements, dictionary methods
-  *     Nested data structures
-  *     Combining data structures for complex data organization
-  *     Introduction to mutability and immutability
-===== Week 6: Functions =====
-  * Defining and calling functions
-  * Function parameters and arguments
-  * Return statements and returning values
-  * Scope of variables: global vs local
-  * Unordered List Item
-  * Recursion: concept and examples
-===== Week 7: Introduction to Object-Oriented Programming (OOP) =====
-  * Unordered List Item
-  * Understanding objects and classes
-  * Defining classes and creating objects
-  * Class attributes and methods
-  * Instance attributes and methods
-  * Inheritance and polymorphism basics
-===== Week 8: File Handling and Modules =====
-  * Opening, reading, writing, and closing files
-  * File modes and file objects
-  * Working with different file formats (text files, CSV, JSON)
-  * Creating and using modules
-  * Importing modules and packages
-===== Week 9: Error Handling and Debugging =====
-  * Understanding exceptions and errors
-  * Using try-except blocks for error handling
-  * Raising exceptions
-  * Debugging techniques and tools
-  * Best practices for writing clean and debuggable code
-===== Week 10: Final Project =====
-  * Applying learned concepts to a real-world project
-  * Planning, designing, and implementing a Python application
-  * Presenting and sharing final projects with peers
-  * Reflection and feedback on the course
-===== Topics for training =====
-[[https://campus.datacamp.com/courses/intro-to-python-for-data-science/chapter-1-python-basics?ex=1|
-Python training by data camp]]
-[[https://www.python.org/about/gettingstarted/|
-Python for beginners]]
-[[https://www.learnpython.org/|
-Learn Python]]
-[[https://www.learnpython.org/en/Hello%2C_World%21|
-Hello World]]
-[[https://www.learnpython.org/en/Variables_and_Types|
-Variables and Types]]
-[[https://developers.google.com/edu/python|
-Google's Python Class]]
-[[https://developers.google.com/edu/python/lists|
-Lists 1]]
-[[https://www.learnpython.org/en/Lists|
-Lists 2]]
-[[https://www.learnpython.org/en/Basic_Operators|
-Basic Operators]]
-[[https://developers.google.com/edu/python/set-up|
-Setup]]
-[[https://developers.google.com/edu/python/strings|
-Strings]]
-[[https://www.learnpython.org/en/String_Formatting|
-String Formatting]]
-[[https://www.learnpython.org/en/Basic_String_Operations|
-Basic String operations]]
-[[https://www.learnpython.org/en/Conditions|
-Conditions]]
-[[https://developers.google.com/edu/python/utilities|
-Utilities]]
-[[https://developers.google.com/edu/python/exercises/basic|
-Basic Python exercises]]
-[[https://developers.google.com/edu/python/dict-files|
-Dict and File]]
-[[https://www.learnpython.org/en/Dictionaries|
-Dictionaries]]
-[[https://developers.google.com/edu/python/sorting|
-Sorting]]
-[[https://developers.google.com/edu/python/regular-expressions|
-Regular Expressions]]
-[[https://www.learnpython.org/en/Regular_Expressions|
-Regular Expressions]]
-[[https://developers.google.com/edu/python/exercises/baby-names|
-Baby Names Python Exercise]]
-[[https://developers.google.com/edu/python/exercises/log-puzzle|
-Log Puzzle Python Exercise]]
-[[https://developers.google.com/edu/python/exercises/copy-special|
-Copy Special Python Exercise]]
-[[https://www.learnpython.org/en/Loops|
-Loops]]
-[[https://www.learnpython.org/en/Functions|
-Functions]]
-[[https://www.learnpython.org/en/Classes_and_Objects|
-Classes and Objects]]
-[[https://www.learnpython.org/en/Modules_and_Packages|
-Modules and Packages]]
-[[https://www.learnpython.org/en/Numpy_Arrays|
-Numpy Arrays]]
-[[https://www.learnpython.org/en/Pandas_Basics|
-Pandas Basics]]
-[[https://www.learnpython.org/en/Generators|
-Generators]]
-[[https://www.learnpython.org/en/List_Comprehensions|
-List comprehensions]]
-[[https://www.learnpython.org/en/Lambda_functions|
-Lambda Functions]]
-[[https://www.learnpython.org/en/Multiple_Function_Arguments|
-Multiple function arguments]]
-[[https://www.learnpython.org/en/Exception_Handling|
-Exception Handling]]
-[[https://www.learnpython.org/en/Sets|
-Sets]]
-[[https://www.learnpython.org/en/Serialization|
-Serialization]]
-[[https://www.learnpython.org/en/Partial_functions|
-partial functions]]
-[[https://www.learnpython.org/en/Code_Introspection|
-Code inspection]]
-[[https://www.learnpython.org/en/Closures|
-Closures]]
-[[https://www.learnpython.org/en/Decorators|
-Decorators]]
-[[https://www.learnpython.org/en/Map,_Filter,_Reduce|
-Map,Filter,Reduce]]
-==4 classes of 3 hours each.==
-Python Intro
-Python Get Started
-Python Syntax
-Python Comments
-Python Variables
-Python Data Types
-Python Numbers
-Python Casting
-Python Strings
-Python Booleans
-Python Operators
-Python Lists
-Python Tuples
-Python Sets
-Python Dictionaries
-Python If...Else
-Python While Loops
-Python For Loops
-Python Functions
-Python Lambda
-Python Arrays
-Python Classes/Objects
-Python Inheritance
-Python Iterators
-Python Scope
-Python Modules
-Python Dates
-Python Math
-Python JSON
-Python RegEx
-Python PIP
-Python Try...Except
-Python User Input
-Python String Formatting
-File Handling
-Python File Handling
-Python Read Files
-Python Write/Create Files
-Python Delete Files
-**Computer usage knowledge :**
-How to use the desktop.
-How to use a terminal.
-How to use a text editor.
-How to run commands on the command line.
-**Prerequisites :**
-Linux Desktop with python installed.
-Recommended distribution : MX Linux [[https://mxlinux.org/]]
-Download AHS from [[https://sourceforge.net/projects/mx-linux/files/Final/Xfce/MX-21.1_ahs_x64.iso/download]]
-[[https://mxlinux.org/download-links/]]
-[[https://mxlinux.org/manuals/|How to install Linux manual]]
-[[https://www.youtube.com/playlist?list=PLTRkAa6x1htWzSSOBCzyE6UJDtGtU8cuj|How to install Linux videos]]
-**To register for the course**
-Send a screenshot of the working python command in the terminal to register for the course.
-Send fee payment.
-The working python screenshot and fee payment is due by end of 22nd of July 2022 to be able to attend the course.
----------------
-[[https://pytorch.org/|PyTorch]]
-An open source machine learning framework that accelerates the path from research prototyping to production deployment.
-[[https://pytorch.org/tutorials/|Welcome to PyTorch Tutorials]]
-[[https://keras.io/|Keras]]
-Deep learning for humans.
-Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides.
-[[https://www.tensorflow.org/|TensorFlow]]
-TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.
-[[https://realpython.com/python-ai-neural-network/|Python AI: How to Build a Neural Network & Make Predictions]]
-[[https://www.tutorialspoint.com/artificial_intelligence_with_python/index.htm|AI with Python Tutorial]]
-[[https://www.edureka.co/blog/artificial-intelligence-with-python/|A Comprehensive Guide To Artificial Intelligence With Python]]
-[[https://www.w3schools.com/python/python_ml_getting_started.asp|Machine Learning]]
-[[https://pll.harvard.edu/course/cs50s-introduction-artificial-intelligence-python?delta=0|CS50's Introduction to Artificial Intelligence with Python]]
-[[https://www.coursera.org/learn/python-for-applied-data-science-ai|Python for Data Science, AI & Development]]
-[[https://www.mygreatlearning.com/academy/learn-for-free/courses/artificial-intelligence-with-python|Artificial Intelligence with Python]]
-[[https://www.udacity.com/course/ai-programming-python-nanodegree--nd089|AI Programming with Python]]
-[[https://www.cuelogic.com/blog/role-of-python-in-artificial-intelligence|Role of Python in Artificial Intelligence (AI)]]
-Topics for training
-Based on https://www.w3schools.com/python/
-classes of 3 hours each.
-Starting python.
-Python Intro
-Python Get Started
-Python Syntax
-Python Comments
-Python Variables
-Python Data Types
-Python Numbers
-Python Casting
-Python Strings
-Python Booleans
-Python Operators
-Python Lists
-Python Tuples
-Python Sets
-Python Dictionaries
-Python If...Else
-Python While Loops
-Python For Loops
-Python Functions
-Python Lambda
-Python Arrays
-Python Classes/Objects
-Python Inheritance
-Python Iterators
-Python Scope
-Python Modules
-Python Dates
-Python Math
-Python JSON
-Python RegEx
-Python PIP
-Python Try...Except
-Python User Input
-Python String Formatting
-File Handling
-Python File Handling
-Python Read Files
-Python Write/Create Files
-Python Delete Files
--------------
-Topic 1 Introduction to Python Programming
-    Business requirements and objectives
-    Applications of Python programming to meet business requirements
-    Install Python and Setup Python IDE
-Topic 2: Data Types and Operators
-    Data Types
-    Operators
-Topic 3 Problem Solving with Control Structures
-    Problem solving with conditional and loop techniques
-    Coding using comprehensions
-Topic 4 Scripting with Function and Lambda
-    Create Python functions to meet business use cases
-    Lambda function and its applications
-Topic 5 Import and Process Finance Data
-    Data analysis using Pandas package
-    DataFrame and Series data structures
-    Import finance data
-    Filter and slice finance data
-    Clean missing data
-Topic 6 Aggregate and Visualize Finance Data
-    Join finance data with concat, append and merge
-    Aggregate data with groupby and pivot table
-    Assess codes to identify gaps
-    Test and visualize finance data
-Topic 7 Analyze Finance Data
-    Improve codes with pipe and apply
-    Applications of statistics
-    Analyse finance data to track any changes
-Mode of Assessment
-    Written Assessment (Q&A)
-    Practical Performance
+[[products:ict:python_course_ttc_brochure|Python Courses]]