Age group: 15-89
Running Python - Numbers- Introduction to Python Numerical Types: Int, Float and Complex Numbers- Introduction to Python Numerical Types: Int, Float and Complex - Numbers- Number Type Conversion Numbers- Number Type Conversion - Numbers- Basic Mathematical Functions Numbers- Basic Mathematical Functions - Numbers- Random Number Functions Numbers- Random Number Functions - Numbers- Trigonometric Functions Numbers- Trigonometric Functions - Numbers- Mathematical Constants (Pi and e) Numbers- Mathematical Constants (Pi and e) - Numbers- Coding Practice Using Different Functions Numbers- Coding Practice Using Different Functions - Numbers- Assignment Basic Syntax- Python Identifiers - Strings- Accessing Values in Strings - What Is Python List? - Introduction to Python Dictionary - What Are Modules in Python? - Date & Time- What Is Tick? Strings- Accessing Values in Strings - Strings- Updating the Strings Strings- Updating the Strings - Strings- Escape Operators Strings- Escape Operators - String Operators String Operators - String Slicing String Slicing - String Formatting Operators String Formatting Operators - Built-in String Functions Built-in String Functions - Strings- Triple Quotes Strings- Triple Quotes - Strings- Coding Practice Using Different Functions What Is Python List? - Accessing Values Within Lists Accessing Values Within Lists - List Slicing List Slicing - List Updating List Updating - Deleting List Elements Deleting List Elements - Appending List Elements Appending List Elements - Basic List Operations: Len, +, In, * Basic List Operations: Len, +, In, * - List Built-in Functions (Methods) List Built-in Functions (Methods) - Looping Through Lists Looping Through Lists - Write a Program to Find the Square of the Integers Given in a List Write a Program to Find the Square of the Integers Given in a List - Write a Program to Find the Average of Numbers Given in a List Numbers- Assignment - NUMPY- NUMPY Array NUMPY- NUMPY Array - NUMPY- Indexing AND Slicing NUMPY- Indexing AND Slicing - NUMPY- Operations on Arrays NUMPY- Operations on Arrays - NUMPY- Concatenation Arrays NUMPY- Concatenation Arrays - NUMPY- Loading Arrays From Files NUMPY- Loading Arrays From Files - NUMPY- Saving NUMPY Arrays In NUMPY- Saving NUMPY Arrays In - NUMPY- Files on Disk Introduction to Python Dictionary - Syntax of Python Dictionary Syntax of Python Dictionary - Properties of Dictionary Keys Properties of Dictionary Keys - Accessing Values in Dictionary Accessing Values in Dictionary - Updating Dictionary Updating Dictionary - Deleting Dictionary Elements Deleting Dictionary Elements - Check If a Given Key Already Exists in Dictionary Check If a Given Key Already Exists in Dictionary - Using Tuples as Keys in Dictionary Using Tuples as Keys in Dictionary - In-built Functions of Dictionary In-built Functions of Dictionary - Merging the Dictionaries Merging the Dictionaries - Dictionary- Coding Practice Using Different Functions What Are Modules in Python? - Python Import Module Python Import Module - Modules- The Three Import Statement Modules- The Three Import Statement - Modules- Importing a Class in Python Modules- Importing a Class in Python - Using from Import Statement Using from Import Statement - Modules- Practice Date & Time- What Is Tick? - Date & Time- What Is Time Tuple? Date & Time- What Is Time Tuple? - Date & Time- Getting Current Date & Time Date & Time- Getting Current Date & Time - Date & Time- Getting Formatted Date & Time Output Date & Time- Getting Formatted Date & Time Output - Date & Time- The Time Module Date & Time- The Time Module - Date & Time- Getting Calendar for the Month Date & Time- Getting Calendar for the Month - Date & Time- The Calendar Module Date & Time- The Calendar Module - Date & Time- Other Modules and Functions Date & Time- Other Modules and Functions - Date & Time- How to Use Time Delta Objects Date & Time- How to Use Time Delta Objects - Date & Time- Coding Practice to Create a Formatted Calendar
Basic knowledge of Python programming
Familiarity with object-oriented programming concepts.
Enthuziasm to become a Python programmer
Working with Libraries and Modules: Enhance proficiency in using Python libraries and modules, such as NumPy, Pandas, and Matplotlib, to perform data analysis, visualization, and other specialized tasks.
Error Handling and Debugging: Learn advanced techniques for error handling, debugging, and testing Python code to ensure robust and error-free programs.
File Handling and Data Persistence: Develop skills in file I/O operations, working with different file formats, and using libraries to manage data persistence in Python applications.
Object-Oriented Programming (OOP): Master the principles of OOP in Python, including classes, inheritance, polymorphism, and encapsulation, to create more complex and reusable code.
Advanced Data Structures: Gain a deeper understanding of data structures such as sets, dictionaries, and linked lists, and learn to implement them effectively in Python.
You'll learn Python syntax and semantics and the flow of programming
You'll get proficient in advanced data structures
You'll be able to build your own programs in Python
You'll become an expert in file reading and writing functions
You'll be able to make efficient use of arrays
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