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Python Programming & Data Structures for AIML and Data Science
👉 Enroll Today & Become a Job-Ready Python Programmer!
📞 Contact: 8485898120
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RS. 8,000 Only
This course includes
- 2 Months Training Program
- Live Online Sessions
- Basic to advance Training
- 3+ Projects Implementations
- Resume & Interview Preparation
- Hindi Language
- Lifetime Validity
- Chance to win Gifts from us
About Course
This course helps students build a strong foundation in Python programming and core data structures essential for Artificial Intelligence, Machine Learning, and Data Science. Learn how to write efficient programs, manage data, and solve complex problems using practical coding techniques.
By mastering Python and data structures, students gain the skills required to move forward into AI, Machine Learning, and advanced data-driven technologies. 🚀
Course Content
Introduction to Python Programming
- Introduction to Programming : Languages Introduction to Programming Languages, High Level vs Low Level Languages, Compilers and Interpreters, Programming Logic and Algorithm Basics, Python Language Overview, Applications of Python in AI, Machine Learning, Data Science and Automation.
- Python Installation and Setup : Installing Python on Windows / Linux / Mac, Setting up Development Environment, IDE Setup (VS Code / PyCharm), Python Interpreter and Script Mode, Running First Python Program, Understanding Python File Structure.
Python Fundamentals
- Variables and Data Types : Python Variables and Naming Rules, Primitive Data Types – int, float, string, boolean, Dynamic Typing in Python, Type Conversion and Casting, Working with Strings, String Operations and Methods.
- Operators and Expressions : Arithmetic Operators, Relational Operators, Logical Operators, Assignment Operators, Bitwise Operators Basics, Operator Precedence and Expressions Evaluation.
- Input and Output Operations : Reading User Input using input(), Printing Output using print(), String Formatting – f-strings and format(), Escape Characters and Formatting Techniques.
Control Flow Statements
- Conditional Statements : If Statement, If Else Statement, Nested If Statements, Elif Ladder, Conditional Expressions.
- Looping Statements : For Loop, While Loop, Nested Loops, Break Statement, Continue Statement, Pass Statement, Iterating Over Sequences.
Functions and Modular Programming
- Python Functions : Defining Functions, Function Parameters and Return Values, Positional and Keyword Arguments, Default Arguments, Variable Length Arguments.
- Lambda Functions : Anonymous Functions, Functional Programming Basics, Using Lambda with map(), filter(), reduce().
- Modules and Packages : Importing Modules, Creating Custom Modules, Python Standard Libraries Overview, Package Structure in Python.
Python Data Structures
- Lists : List Creation and Initialization, Indexing and Slicing, List Methods – append(), extend(), remove(), pop(), Iterating Through Lists, List Comprehensions.
- Tuples : Tuple Creation and Usage, Tuple Packing and Unpacking, Tuple Operations, Differences between Lists and Tuples.
- Sets : Set Creation and Initialization, Set Operations – Union, Intersection, Difference, Set Methods and Applications.
- Dictionaries : Dictionary Creation, Key Value Pairs, Dictionary Methods, Iterating Through Dictionaries, Nested Dictionaries.
Advanced Python Concepts
- File Handling : Working with Text Files, File Modes – Read, Write, Append, Reading and Writing Files, Handling CSV and JSON Files.
- Exception Handling : Errors vs Exceptions, Try and Except Blocks, Multiple Exceptions Handling, Finally Block, Raising Custom Exceptions.
- Object Oriented Programming : Classes and Objects, Constructors, Instance and Class Variables, Encapsulation, Inheritance, Polymorphism, Method Overriding.
Data Structures and Algorithms
- Linear Data Structures : Stack Implementation using Lists, Queue Implementation, Introduction to Linked Lists, Applications of Linear Data Structures.
- Searching Algorithms : Linear Search Algorithm, Binary Search Algorithm, Performance Comparison.
- Sorting Algorithms : Bubble Sort, Selection Sort, Insertion Sort, Merge Sort Basics, Sorting Complexity.
- Algorithm Complexity : Introduction to Time Complexity, Space Complexity Concepts, Big-O Notation Basics.
Python Libraries for Data Science
- NumPy : Introduction to NumPy Arrays, Creating Arrays, Array Indexing and Slicing, Mathematical Operations on Arrays, Broadcasting Concepts.
- Pandas : Introduction to Pandas DataFrames, Importing Data from CSV and Excel Files, Data Cleaning Techniques, Handling Missing Values, Data Filtering and Aggregation.
- Data Visualization : Introduction to Data Visualization, Creating Graphs using Matplotlib, Line Charts, Bar Charts, Scatter Plots, Data Visualization Best Practices.
Problem Solving and Coding Practice
- Programming Problem Solving : Logic Building Techniques, Pattern Problems, Algorithm Implementation Exercises.
- Coding Interview Preparation : Common Python Interview Questions, Data Structure Problem Solving, Coding Practice Platforms.
