Python Level 3 – Advanced Python
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Python Level 3 – Advanced Python

Prepare for machine learning, algorithms, and advanced real-world projects.

26 Classes (24 regular + 2 Q&A, 13 weeks, 2 per week)
Age 16-20
Advanced Level
2 classes/week
8,500
10,000
Save ৳1,500
BDT (Bangladeshi Taka)
Or pay ৳2,850/month
Contact us for enrollment →

Course Syllabus

1

Arrays & Lists (intro & usage)

Understanding arrays and advanced list operations

Topics Covered:

  • Array concepts
  • List vs Array differences
  • Memory management
  • Performance considerations
2

Advanced List Operations

Mastering complex list manipulations and algorithms

Topics Covered:

  • List comprehensions
  • Advanced slicing
  • List algorithms
  • Performance optimization
3

Linked Lists (concept)

Understanding linked list data structure concepts

Topics Covered:

  • Linked list theory
  • Node structure
  • Advantages vs arrays
  • Use cases
4

Linked List Implementation

Building linked lists from scratch in Python

Topics Covered:

  • Node class creation
  • Insertion operations
  • Deletion operations
  • Traversal methods
5

Stacks (concept & use cases)

Understanding stack data structure and applications

Topics Covered:

  • LIFO principle
  • Stack operations
  • Real-world applications
  • Stack use cases
6

Stack Implementation (list-based)

Implementing stack using Python lists

Topics Covered:

  • Push operation
  • Pop operation
  • Peek operation
  • Stack applications
7

Queues (concept & variations)

Understanding queue data structure and its types

Topics Covered:

  • FIFO principle
  • Queue types
  • Circular queues
  • Priority queues
8

Queue Implementation

Building queue data structure from scratch

Topics Covered:

  • Enqueue operation
  • Dequeue operation
  • Queue using lists
  • Queue applications
9

Quiz 1 & Review

Testing knowledge of basic data structures

Topics Covered:

  • Arrays and lists quiz
  • Linked lists quiz
  • Stacks and queues review
  • Problem solving practice
10

Trees (intro & terminology)

Introduction to tree data structures

Topics Covered:

  • Tree concepts
  • Tree terminology
  • Tree types
  • Tree applications
11

Binary Trees (insert & traversal)

Working with binary tree structures

Topics Covered:

  • Binary tree structure
  • Node insertion
  • Tree construction
  • Basic traversal
12

Binary Tree Traversal (inorder, preorder, postorder)

Implementing different tree traversal methods

Topics Covered:

  • Inorder traversal
  • Preorder traversal
  • Postorder traversal
  • Traversal applications
13

Binary Search Tree (insert, search, delete)

Implementing binary search tree operations

Topics Covered:

  • BST properties
  • Insertion algorithm
  • Search algorithm
  • Deletion algorithm
14

Graph Basics (representation)

Introduction to graph data structures

Topics Covered:

  • Graph concepts
  • Graph types
  • Adjacency matrix
  • Adjacency list
15

Graph Traversal (DFS)

Implementing Depth-First Search algorithm

Topics Covered:

  • DFS algorithm
  • Recursive DFS
  • Iterative DFS
  • DFS applications
16

Graph Traversal (BFS)

Implementing Breadth-First Search algorithm

Topics Covered:

  • BFS algorithm
  • Queue-based BFS
  • Level-order traversal
  • BFS applications
17

Quiz 2 & Review

Testing knowledge of advanced data structures

Topics Covered:

  • Trees quiz
  • Graph algorithms quiz
  • Traversal methods review
  • Algorithm analysis
18

Hashing Basics & Hash Functions

Understanding hashing concepts and hash functions

Topics Covered:

  • Hash function concepts
  • Hash table basics
  • Hash function design
  • Hash applications
19

Implementing a Hash Table

Building hash table from scratch

Topics Covered:

  • Hash table implementation
  • Key-value storage
  • Hash function integration
  • Performance analysis
20

Collision Handling Methods

Dealing with hash collisions

Topics Covered:

  • Collision types
  • Chaining method
  • Open addressing
  • Collision resolution strategies
21

Heaps (min & max heap)

Understanding heap data structure

Topics Covered:

  • Heap properties
  • Min heap implementation
  • Max heap implementation
  • Heap operations
22

Priority Queues Implementation

Building priority queues using heaps

Topics Covered:

  • Priority queue concept
  • Heap-based implementation
  • Priority operations
  • Real-world applications
23

Mini Project: Task Scheduler

Building a task scheduling system using data structures

Topics Covered:

  • Priority-based scheduling
  • Queue management
  • Task prioritization
  • System design
24

Final Project: Mini Social Network

Creating a social network using graphs and advanced data structures

Topics Covered:

  • Graph-based relationships
  • User connections
  • Data structure integration
  • System architecture
25

Q&A / Revision

Interactive Q&A session and concept revision

Topics Covered:

  • Data structure review
  • Algorithm optimization
  • Performance analysis
  • Best practices
26

Q&A / Revision

Final Q&A session and course wrap-up

Topics Covered:

  • Advanced algorithms
  • Project presentations
  • Career guidance
  • Course completion

What You'll Learn

Hands-on projects and real-world applications
Expert instruction and personalized feedback
Certificate of completion
Lifetime access to course materials

Course Summary

Duration:26 Classes (24 regular + 2 Q&A, 13 weeks, 2 per week)
Level:Advanced
Age Group:Age 16-20
Classes:24 sessions
Schedule:Fri & Sat
8,500
10,000
Save ৳1,500
BDT (Bangladeshi Taka)

Need help? Contact us

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