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DEMO CLASS: [ক্লিক করে দেখে নিন কোর্সের ডেমো ক্লাসগুলো]
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Demo Class 1: Build a Simple Calculator Using Python Function
07:29
Demo Class 2: How to Define Views in Django
03:10
Demo Class 3: Dataset Visualization and Plotting Graphs
05:48
Module 1: Introduction to Python (Beginner Friendly)
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Lecture 1: Installing Python and IDEs (PyCharm, VSCode, Jupyter) . .[FREE CLASS]. .
03:06
Lecture 2: Variables and Data Types . .[FREE CLASS]. .
09:37
Lecture 3: Typecasting and Conversion
06:45
Lecture 4: Conditional Statements: if, elif, else
08:22
Lecture 5: Loops: for and while
05:34
Lecture 6: Functions & Reusability
06:01
Lecture 7: Data Structures
07:34
Python Cheat Sheet
Project: Build a Number Guessing Game
04:03
Project: Build a Simple Calculator Using Python Function
07:29
Support: Join the WhatsApp group to get any help from instructor
Module 2: Core Python Concepts
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Lecture 1: Lists, Tuples, Sets, Dictionaries (with use-cases), List Comprehensions . .[FREE CLASS]. .
18:12
Lecture 2: String Operations and Formatting . .[FREE CLASS]. .
08:49
Lecture 3: Functions (parameters, return, scope)
17:24
Lecture 4: Recursion Basics
03:21
Lecture 5: Lambda Functions & map(), filter(), reduce()
08:02
Lecture 6: Error Handling (try, except, finally)
07:31
Lecture 7: File I/O: Reading & Writing Files (Part 1)
08:14
Lecture 8: File I/O: Reading & Writing Files (Part 2)
02:57
Lecture 9: File I/O: Reading & Writing Files (Part 3)
04:07
Module 3: Data Structures & Algorithms in Python
0/15
Lecture 1: Stack . .[FREE CLASS]. .
11:20
Lecture 2: Queues (Part 1)
08:13
Lecture 3: Queue (Part 2)
03:04
Lecture 4: Linked List (Part 1)
05:45
Lecture 5: Linked list (Part 2)
05:32
Lecture 6: Binary tree (Part 1)
02:36
Lecture 7: Binary tree (Part 2)
10:28
Lecture 8: Trees
15:19
Lecture 9: Hash Maps (Dictionaries)
05:56
Lecture 10: Searching Algo
12:52
Lecture 11: Bubble Sort
05:13
Lecture 12: Merge Sort (Part 1)
03:08
Lecture 13: Merge Sort (Part 2)
10:35
Lecture 14: Quick Sort
07:19
Lecture 15: Selection Sort
05:02
Module 4: Advanced Python Concepts and File Handling
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Lecture 1: Type Hinting
17:29
Lecture 2: Aggregation and Composition (Part 1)
07:38
Lecture 3: Aggregation and Composition (Part 2)
14:43
Lecture 4: Magic Methods
09:47
Lecture 5: Decorator (Part 1)
07:26
Lecture 6: Decorator (Part 2)
08:09
Lecture 7: Generator
12:31
Lecture 8: Working with csv file
10:08
Lecture 9: Working with json file (Part 1)
06:11
Lecture 10: Working with json file (Part 2)
03:30
Module 5: Project- Build A Library Management System
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Build A Library Management System (Part 1)
15:58
Build A Library Management System (Part 2)
19:31
Module 6: Machine Learning & Data Science
0/15
Lecture 1: Introduction to Machine Learning
05:02
Lecture 2: Types of Machine Learning
12:41
Lecture 3: Machine Learning Pipeline
09:21
Lecture 4: Environment Setup
03:28
Lecture 5: Downloading Dataset
05:46
Lecture 6: Import Dataset and Visualize
07:37
Lecture 7: Dataset Visualization and Plotting Graphs
05:47
Lecture 8: Introduction to Data Science
04:53
Lecture 9: Introduction to Pandas Dataframes and Series
14:06
Lecture 10: Import & Export Data
07:00
Lecture 11: Data Exploration Functions
07:31
Lecture 12: Statistical Functions & Plotting
12:02
Lecture 13: Accessing Individual Data
13:19
Lecture 14: Data Manipulation
20:20
Lecture 15: Cleaning Data
09:12
Module 7: Project – Build A Movie Recommendation System
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Lecture 1: Real World Project
04:36
Lecture 2: Importing Dataset
05:40
Lecture 3: Preprosessing Data
06:37
Lecture 4: Model Creation and Training
05:37
Lecture 5: Prediction
04:37
Lecture 6: Splitting the Dataset
07:24
Lecture 7: Calculating Accuracy Score
06:14
Python for Data Science & ML (Crash Course)
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