Differences

This shows you the differences between two versions of the page.

--- products:ict:python:python_course [2024/03/01 19:15] – [Week 3: Control Flow] wikiadmin
+++ products:ict:python:python_course [2024/03/07 15:23] (current) – created wikiadmin
@@ Line 1: / Line 1: @@
-====== 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 ItemRecursion: 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]]