āĻŦāĻžāĻ‚āϞāĻžāĻĻ⧇āĻļ⧇ āϏāĻ°ā§āĻŦāĻĒā§āϰāĻĨāĻŽ: āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āϜāĻ—āϤ⧇ āĻāĻ•āĻžāϧāĻŋāĻ• āĻĻāĻ•ā§āώāϤāĻžāϰ āĻ…āϧāĻŋāĻ•āĻžāϰ⧀ āĻšāĻŦ⧇āύ āϏāĻŦāĻšā§‡ā§Ÿā§‡ āϏāĻžāĻļā§āĻ°ā§Ÿā§€ āĻŽā§āĻ˛ā§āϝ⧇ āĻāĻŦāĻ‚ āĻ­āĻŋāĻ¨ā§āύāϧāĻ°ā§āĻŽā§€ āϕ⧋āĻ°ā§āϏ āĻĒā§āϞāĻžāύ āĻ…āύ⧁āϝāĻžā§Ÿā§€ āĨ¤

āϝ⧇āĻ–āĻžāύ⧇ āĻāĻ•āϏāĻžāĻĨ⧇ āĻĒāĻžāĻšā§āϛ⧇āύ C Programming, Python & Data Science, Robotics—āϏāĻŦāĻ•āĻŋāϛ⧁ āĻŦāĻžāĻ‚āϞāĻž āĻ­āĻžāώāĻžā§Ÿ, āĻāĻ•āϟāĻŋāĻŽāĻžāĻ¤ā§āϰ āĻĒā§āĻ˛ā§āϝāĻžāϟāĻĢāĻ°ā§āĻŽā§‡āĨ¤Â 

āϝāĻž ā§§ā§Ļ āĻŦāĻ›āϰ āĻŦ⧟āϏ⧀ āĻšāϤ⧇ ā§Ēā§Ļ āĻŦāĻ›āϰ āĻŦ⧟āϏ⧀ āϝ⧇āϕ⧇āω āϖ⧁āĻŦ āϏāĻšāĻœā§‡ āĻļāĻŋāĻ–āϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύāĨ¤

FEATURE

āϭ⧁āϞ āϏāĻŋāĻĻā§āϧāĻžāĻ¨ā§āϤ, āϧ⧀āϰ āĻ•āĻžāϜ, āĻ…āĻ—ā§‹āĻ›āĻžāϞ⧋ āĻ­āĻžāĻŦāύāĻž āĻāϏāĻŦ⧇āϰ āĻĒ⧇āĻ›āύ⧇ āĻ•āĻžāϰāĻŖ āĻāĻ•āϟāĻžāχ:
āĻ āĻŋāĻ•āĻ­āĻžāĻŦ⧇ āϏāĻŽāĻ¸ā§āϝāĻž āĻŦāĻŋāĻļā§āϞ⧇āώāĻŖ āĻ•āϰāĻžāϰ āĻ¸ā§āĻ•āĻŋāϞ āύ⧇āχāĨ¤ āϤāĻžāχ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻ•ā§āϝāĻžāϰāĻŋ⧟āĻžāϰ āϜāύāĻĒā§āϰāĻŋ⧟, āĻ•āĻžāϰāύ āφāĻĒāύāĻŋ āύāĻŋāĻœā§‡āϰ āĻāĻŦāĻ‚ āĻ…āĻ¨ā§āϝāĻĻ⧇āϰ āĻšāĻžāϜāĻžāϰ⧋ āϏāĻŽāĻ¸ā§āϝāĻž āϏāĻŽāĻžāϧāĻžāύ āĻāϰ āϏāĻ•ā§āώāĻŽāϤāĻž āĻ…āĻ°ā§āϜāύ āĻ•āϰāĻŦ⧇āύāĨ¤
āĻ•āĻŋāĻ¨ā§āϤ⧁ āϝ⧇āϏāĻŦ āϜāĻŋāύāĻŋāϏ āϜāĻžāύāϞ⧇ āφāĻĒāύāĻŋ ⧝ā§Ļ% āĻŽāĻžāύ⧁āώ⧇āϰ āĻšā§‡ā§Ÿā§‡ āĻāĻ—āĻŋā§Ÿā§‡ āĻĨāĻžāĻ•āϤ⧇āύ,āϏ⧇āϗ⧁āϞ⧋ āϕ⧋āĻĨāĻžāĻ“ āĻļ⧇āĻ–āĻžāύ⧋ āĻšā§Ÿ āύāĻžāĨ¤āĻāχ āĻĒā§āϝāĻžāϕ⧇āϜāϟāĻž āϏ⧇āχ āĻ—ā§āϝāĻžāĻĒāϟāĻžāχ āĻĒā§‚āϰāĻŖ āĻ•āϰ⧇āĨ¤ āĻ•āĻžāϰāύ āĻāĻ–āĻžāύ⧇ āĻĒāĻžāĻŦ⧇āύ ā§Ē āϟāĻŋ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻ¸ā§āĻ•āĻŋāϞ āĻāϰ āĻļāĻ•ā§āϤāĻŋ, āχāωāύāĻŋāĻ• āϕ⧋āĻ°ā§āϏ āĻĒā§āϞāĻžāύ āĻāĻŦāĻ‚ āĻĒā§āϰāĻžāχāϭ⧇āϟ āϰāĻŋāϏ⧋āĻ°ā§āϏāĨ¤ āϝāĻž āĻļ⧇āĻ–āĻž āĻļ⧇āώ⧇ āĻ¸ā§āĻŽāĻžāĻ°ā§āϟ āĻ•ā§āϝāĻžāϰāĻŋ⧟āĻžāϰ āĻāĻŦāĻ‚ āĻ•ā§āϰāĻŋā§Ÿā§‡āϟāĻŋāĻ­ āĻŦā§āϝāĻžāĻ•ā§āϤāĻŋāϤ⧇ āĻĒāϰāĻŋāύāϤ āĻšāĻŦ⧇āύāĨ¤

āĻĒā§āϰāϤāĻŋāĻĻāĻŋāύ āφāĻĒāύāĻŋ āϞāϏ āĻ•āϰāϛ⧇āύ, āĻ•āĻŋāĻ¨ā§āϤ⧁ āĻŦ⧁āĻāϤ⧇ āĻĒāĻžāϰāϛ⧇āύ āύāĻž !

đŸŽ–ā§Žā§Ļā§Ļā§Ļ+ āĻāϰ āĻ…āϧāĻŋāĻ• āĻļāĻŋāĻ•ā§āώāĻžāĻ°ā§āĻĨā§€ āϝ⧁āĻ•ā§āϤ āĻšā§Ÿā§‡āϛ⧇āύ āφāĻŽāĻžāĻĻ⧇āϰ āĻāχ āϝāĻžāĻ¤ā§āϰāĻžā§ŸāĨ¤āϝāĻžāϰ āĻŦ⧇āĻļāĻŋāϰ āϝ⧁āĻ•ā§āϤ āĻšāĻ“ā§ŸāĻžāϰ āĻ•āĻžāϰāύ āφāĻŽāĻžāĻĻ⧇āϰ
(āĻĒāĻžāχāĻĨāύ+ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ)

â™ģ āϝ⧇āϕ⧋āύ⧋ āĻŦā§āϝāĻžāĻ•āĻ—ā§āϰāĻžāωāĻ¨ā§āĻĄ āĻŦāĻž āĻŦ⧟āϏ⧀ āĻāϕ⧇āĻŦāĻžāϰ⧇ āĻļ⧁āĻ¨ā§āϝ āĻ…āĻŦāĻ¸ā§āĻĨāĻž āĻšāϤ⧇ āĻĒā§āϰāĻĢ⧇āĻļāύāĻžāϞ āϞ⧇āϭ⧇āϞ āĻĒāĻ°ā§āϝāĻ¨ā§āϤ āĻļāĻŋāĻ–āϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύāĨ¤ āĻļ⧁āϧ⧁āĻŽāĻžāĻ¤ā§āϰ āĻ•ā§āϞāĻžāϏ āϗ⧁āϞ⧋ āϏāĻŋāϰāĻŋ⧟āĻžāϞāĻŋ āĻĻ⧇āĻ–āĻŦ⧇āύ+ āĻ…āύ⧁āĻļā§€āϞāύ āĻ•āϰāĻŦ⧇āύāĨ¤ āĻ•āĻžāϰāύ āφāĻŽāϰāĻž āĻāĻ–āĻžāύ⧇ āĻāχ āϏ⧇āĻ•ā§āϟāϰ āĻāϰ āϝāĻž āĻ•āĻŋāϛ⧁ āφāϛ⧇ āϏāĻŦāĻ•āĻŋāϛ⧁ āύāĻŋā§Ÿā§‡,āϤāĻžāϰ āĻĒā§āϰāĻ¤ā§āϝ⧇āĻ•āϟāĻŋ āĻ…āĻ‚āĻļ āϕ⧇ āφāϞāĻžāĻĻāĻž āφāϞāĻžāĻĻāĻž āĻ•ā§āϞāĻžāϏ āĻĻāĻŋā§Ÿā§‡ āĻ•āĻžāĻ­āĻžāϰ āĻ•āϰ⧇āĻ›āĻŋāĨ¤āϝāĻžāϤ⧇ āĻāĻ•āĻĻāĻŽ āϛ⧋āϟāϰāĻžāĻ“ āϖ⧁āĻŦ āϏāĻšāĻœā§‡ āĻŦ⧁āϜāϤ⧇ āĻĒāĻžāϰ⧇āĨ¤A to Z āϟāĻĒāĻŋāĻ•āϏāĻŽā§āĻš,āĻĒā§āϰāĻ­āϞāĻŽ āϏāϞāĻ­āĻŋāĻ‚,āĻĒā§āϰāϝ⧇āĻ•ā§āϟ, āĻ•ā§āϝāĻžāϰāĻŋ⧟āĻžāϰ āĻ—āĻžāχāĻĄāϞāĻžāχāύ āϏāĻŦāĻ•āĻŋāϛ⧁āχ āĻĒāĻžāĻšā§āϛ⧇āύ āĻāĻ•āϏāĻžāĻĨ⧇āĨ¤
āϝāĻž āϝāĻž āĻļāĻŋāĻ–āϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύāσ
#Python + Data science Module

1.Python Installation
2.Anaconda and Jupiter
3.Anaconda and Jupiter Installation
4.Using Google Colab
5.Python Basic
6.Data Types and Variables
7.Operators
8.Functions
9.Typecasting and Comments
10.Review
11.Python Expression
12.Type Conversion
13.Expression and Statement
14.Comparison Operators
15.Logical Expression and Logical Operators
16.Operator Precedence
17.Python Conditionals
18.If statement
19. Programming Problem
20.Elif Statement
21.Python Loop
22.While Loop
23.Programming Problem with While Loop
24.For Loop and Range
25.Python Function
26.Declaring a Function
27.Local and Global Namespace
28.Programming Problem
29.Keyword Argument and Default Parameter
30.Python String
31.String Indexing and Slicing
32.Multiline Strings and Operators
33.String Methods
34. Exercise Problem
35.Python List
36.Data Structure
37.List Indexing and Slicing
38.Mutability and Aliasing
39.List Operators
40.List Methods
41.Nested list
42.Python Tuple
43.How to Declare a Tuple
44.Indexing and Slicing and Immutibility
45.Tuple Operators
46.Tuple Methods
47.Tuple Usage
48.Nested Tuple
49.Python Dictionary
50.1Dictionary Declaration and Indexing
51.Mutability and Aliasing
52.Dictionary Operators and Functions
53.Dictionary Methods
54.Nested Dictionary
55.Python Objects
56.Class
57.Objects and Class
58.Creating a Class
59.Why Do We Need Class
60.Python file handling
61.Text and Binary Files
62.Read, Write and Create Files
63.Python miscellaneous concepts
64.None type and del operator
65.Escape Sequence and f-string
66.Stride and Assert
67.Python modules
68.Importing Modules and print Module
69.Copy Module
70.Math Module
71.OS Module
72.OS Module and File Path
73.Datetime Module
74.Collections Module
75.Installing Third Party Packages
76.Numpy Introduction
77.Numpy Introduction and array
78.Data and Limitations
79.Numpy Data types
80.Creating Arrays
81.Array Attributes
82.Indexing and Slicing
83.Numpy array operation
84.Elementwise Arithmetic Operation
85.Broadcasting
86.Linear Algebra Operations
87.Numpy Calculation Methods
88.Numpy array manipulation
89.Copy and View
90.Conversion Methods
91.Shape Manipulation in Numpy
92.Numpy Element Manipulation
93.Value Manipulation and Array Join

✅āĻāχ āĻĒāĻ°ā§āϝāĻ¨ā§āϤ āĻāϏ⧇ āφāĻĒāύāĻžāϰ āĻĒāĻžāχāĻĨāύ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻļ⧇āĻ–āĻž āĻļ⧇āώ āĻšāĻŦ⧇āĨ¤ āφāĻĒāύāĻžāϰ āϜāĻ¨ā§āϝ āϏ⧁āĻ–āĻŦāϰ āĻšāϞ⧋ 😃 āĻāĻ–āύ āĻāχ āĻĒāĻžāχāĻĨāύ āĻĻāĻŋā§Ÿā§‡āχ āφāĻĒāύāĻžāϕ⧇ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āĻļ⧇āĻ–āĻžāύ⧋ āĻšāĻŦ⧇!āφāϏ⧁āύ āĻāĻ–āύ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āĻāϰ āϜāĻ—āϤ⧇āĨ¤ (94-151)

94. data handling in numpy
95.Loading Data from Files
96.Missing Value Handling
97.Advanced Indexing in Numpy
98.Boolean Masking
99.Multiple Condition and Manipulation
100.Pandas introduction
101.Pandas dataframe and series
102.Why Pandas
103.Creating Dataframes
104.Pandas data munging
105.Pandas Data Munging Introduction
106.Reading Data from Files
107.Data Frame Basic Attributes
108.Basic Methods
109.Data Selection
110.Comparison Operators and Methods
111.Conditional Selection and Manipulation
112.Data Type Conversion
113.Missing Value Handling
114.Mathematical Operations
115.Calculation Methods
116.Saving Dataframe
117.Data Munging Workflow
118.Pandas data analysis
119.Dataset Introduction
120.Method Chaining
121.String Accessors
122.Datetime Accessor
123.Index and Column Manipulation
124.Sorting
125.Adding and Droping Data
126.GroupBy and Aggregate
127.Merge and Join (Part 1)
128.Merge and Join (Part 2)
129.Plotting using Pandas
130.Matplotib basics
131.Introduction to Matplotlib
132.Matplotlib Figure Anatomy
133.Basic Line Plot and its Components
134.Matplotlib GUI
135.Format String
136.Adjusting Colors
137.Matplotib plotting types
138.Plotting Types Overview
139.Line Plot
140.Scatter Plot
141.Area Plot
142.Bar Plot
143.Variants of Bar Plot
144.Histogram
145.Pie Chart
146.Eight practical projects.
147.Predictive Modelling
148.Python Programming
149.Data Analysis
150.Data Visualization (DataViz)
151.Model Selection

#Machine learning sagments

#Artificial Intilligence Sagments

🧠 10 Unique methods implement for growing brainstorming power & be genius from others.

ā§Ē āϟāĻŋ āĻŽā§āϝāĻžāϜāĻŋāĻ• āĻ•ā§ŒāĻļāϞāĻ­āĻŋāĻ¤ā§āϤāĻŋāĻ• āĻŽāĻĄāĻŋāωāϞ , āϝāĻž āφāĻĒāύāĻžāϕ⧇ āĻĻā§āϰ⧁āϤ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻ āĻĻāĻ•ā§āώāϤāĻž āĻĻāĻŋāϤ⧇ āĻĒāĻžāϰ⧇āĨ¤

āĻāχ āϕ⧋āĻ°ā§āϏāϟāĻŋāϤ⧇ āϰāϝāĻŧ⧇āϛ⧇ Data science āĻāϰ āϖ⧁āρāϟāĻŋāύāĻžāϟāĻŋ āĻŦāĻŋāώāϝāĻŧ | “āĻĒāĻžāχāĻĨāύ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āϏāĻ•āϞ āϟāĻĒāĻŋāĻ• āĻāĻŦāĻ‚ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ| āϕ⧋āĻ°ā§āϏāϟāĻŋāϤ⧇ āĻ¸ā§āĻ•āĻŋāϞ āĻĄā§‡āϭ⧇āϞāĻĒāĻŽā§‡āĻ¨ā§āĻŸā§‡āϰ āϏāĻžāĻĨ⧇ āĻ•ā§āϝāĻžāϰāĻŋ⧟āĻžāϰ āϰ⧋āĻĄāĻŽā§āϝāĻžāĻĒ āĻĒā§āϰāĻĻāĻžāύ āĻ•āϰāĻž āĻšā§Ÿā§‡āϛ⧇| āϝāĻž āĻāĻ• āϝ⧁āĻ—āĻžāĻ¨ā§āϤāĻ•āĻžāϰ⧀ āϕ⧋āĻ°ā§āϏāĨ¤

āĻāχ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽā§‡ āφāĻĒāύāĻŋ āĻāĻ•āϏāĻžāĻĨ⧇ āĻāĻ•āĻžāϧāĻŋāĻ• āĻĻāĻ•ā§āώāϤāĻžāϰ āĻ…āϧāĻŋāĻ•āĻžāϰ⧀ āĻšāϤ⧇ āĻĒāĻžāϰāϛ⧇āύ āĻ…āĻĨ⧇āύāϟāĻŋāĻ• āĻŽā§‡āĻĨāĻĄ āĻāĨ¤ āĻĻ⧇āϖ⧇ āύāĻŋāύ āĻāχ āχāωāύāĻŋāĻ• āĻĒā§āϞāĻžāύ:

🎖Stage 1: Mind Setup & Brain-Based Coding

✅ Brain-Based Python: Code Like a Genius
→ (Python Basics, Logic, Conditionals, Functions, Loop, Problem Solving)

✅ Logic Engineering: Build a Mind Like a Machine
→ (Operators, Expressions, While/For Loops, Real-life Logic Building)

🧠 āĻāĻ–āĻžāύ⧇ āϏāĻŦāĻžāχ āĻļ⧇āϖ⧇ “āϕ⧋āĻĄ āĻ•āĻŋāĻ­āĻžāĻŦ⧇ āĻ•āĻžāϜ āĻ•āĻ°ā§‡â€ āύāĻž, āĻŦāϰāĻ‚ “āϕ⧋āĻĄ āĻ•āĻŋāĻ­āĻžāĻŦ⧇ āĻ­āĻžāĻŦāϤ⧇ āĻšā§Ÿâ€āĨ¤

⚙ Stage 2: The Foundation of Real Programming

✅ The Code Psychology: How Programmers Think Differently
→ (OOP, File Handling, Debugging, Modules, Assert & Practice Projects)

✅ From Syntax to Strategy: Python Beyond Code
→ (Data Structure, Project Building, File Handling, Career Mindset)

🚀 āĻāĻ–āĻžāύ⧇ āĻļ⧇āĻ–āĻžāύ⧋ āĻšā§Ÿ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚-āĻāϰ āĻŦāĻžāĻ¸ā§āϤāĻŦ āϚāĻŋāĻ¨ā§āϤāĻž — āĻļ⧁āϧ⧁ āϞ⧇āĻ–āĻž āύ⧟, āĻĒāϰāĻŋāĻ•āĻ˛ā§āĻĒāύāĻž āĻ•āϰāĻžāĻ“ āĻļ⧇āĻ–āĻžā§ŸāĨ¤

📊 Stage 3: Data Intelligence & AI Think:

✅ Data Alchemy: Turning Numbers into Power
→ (Numpy, Pandas, Data Manipulation, Analysis, Visualization)

✅ Human Intelligence × Artificial Intelligence Fusion
→ (Predictive Modelling, Model Selection, Machine Learning Concepts)

🤖 āĻāĻ–āĻžāύ⧇ āĻĄāĻžāϟāĻž āĻĻāĻŋā§Ÿā§‡ “āĻ­āĻžāĻŦāĻ¤ā§‡â€ āĻļ⧇āĻ–āĻžāύ⧋ āĻšā§Ÿ — āϝ⧇āύ āĻŦā§āϰ⧇āχāύ + āĻŽā§‡āĻļāĻŋāύ āĻāĻ•āϏāĻžāĻĨ⧇ āĻ•āĻžāϜ āĻ•āϰ⧇āĨ¤

📈 Stage 4: Mastery & Storytelling

✅Data Storytelling: Speak the Language of Insights
→ (Matplotlib, DataViz, Visualization Projects, Communication)

✅ Zero-to-Supermind Python Journey
→ (Full A–Z Revision, Projects, Career Guideline, Portfolio Build)

đŸŽ¯ āĻāĻ–āĻžāύ⧇ āĻļ⧇āĻ–āĻžāύ⧋ āĻšā§Ÿ āύāĻŋāĻœā§‡āϰ āĻ•āĻžāϜāϕ⧇ “āĻĻ⧇āĻ–āĻŋā§Ÿā§‡â€ āĻĒā§āϰāĻ­āĻžāĻŦ āϤ⧈āϰāĻŋ āĻ•āϰāĻž — Professional Data Scientist mindset āĻ āύāĻŋā§Ÿā§‡ āϝāĻžāĻ“ā§ŸāĻžāĨ¤

āϕ⧇āύ āĻāχ āϕ⧋āĻ°ā§āϏāϟāĻŋ āφāĻĒāύāĻžāϰ āϜāĻ¨ā§āϝ āϜāϰ⧁āϰāĻŋ ?

FEATURE

  1. Python Installation
  1. Anaconda and Jupiter Installation
  2. Using Google Colab
  1. Data types & Variables
  2. Operators
  3. Functions
  4. Type casting & comments
  5. Review
  1. Type conversion
  2. Expression & Statement
  3. Comparison operators
  4. Logical expression & Logical operator
  5. Operator Precedence
  1. If statement
  2. A programming Problemn
  3. Elif Statement
  1. While Loop
  2. Programming problem with while loop
  3. For loop & Range
  1. Declaring a function
  2. Local & global name space
  3. A prograaming problem
  4. Keywar argument & Detail pararammeter
  1. String indexing & Slicing
  2. Multiline string & operators
  3. String Methods
  4. An excercise problem
  1. Data structure
  2. List indexing & Slicing
  3. Mutability & Aliasing
  4. List operators
  5. List Method
  6. Nested List
  1. How o deeclare a tuple
  2. Indexing & Slicing,Immutubility
  3. Tuple Operators
  4. Tuple Method
  5. Tuple Usage
  6. Nested touple
  1.  Dictionary  declaration & Indexing
  2. Mutability & Alliasing
  3. Dictionary operators & Functions
  4. Dictionary Methods
  5. Nested Dictionary
  1. Class
  2. Object & Class
  3. Creating a class
  4. Why do we need class
  1. Text & Binary files
  2. Read write & Create Files
  1. Non type & Dell operator
  2. Escape Sequence & F string
  3. Stride & Assert
  1. Importing modules & Print module
  2. Copy Module
  3. Math module
  4. Os module
  5. Os module & File path
  6. Datetime module 
  7. Collection module
  8. installing third party packages
  1. Numpy introduction & Array
  2. Data & Limitation
  3. Numpy Data types
  4. Creating Arrays
  5. Array atributes
  6. Indexing & Slicing
  1. Elementwise arithmetic Operation
  2. Broadcasting
  3. Linear algebra operations
  4. Numpy calculation methods
  1. Copy & View
  2. Conversion Methods
  3. Shape manipulation in numpy
  4. Numpy element manipulation
  5. Value manipulation & array join
  1. Loading data from files
  2. Missing Value Handling
  3. Advanced indexing in Numpy
  4. Boolean masking
  5. Multiple condition & Manipulation.
  1. Pandas data frame & Series
  2. Why pandas
  3. Creating Dataframes
  1. Pandas data munging introduction
  2. Reading Data from files
  3. Dataframe basic attributes
  4. Basic methods
  5. Data selection
  6. Conditional selection & Manipulation
  7. Data type conversion
  8. Missing value handling
  9. Mathmatical operations
  10. Calculation Method
  11. Saving Dataframe
  12. Data Munging Workflow
  1. Dataset Introduction
  2. Method Chaining
  3. String Accessors
  4. Datetime Accessors
  5. Index & Column Manipulation
  6. Sorting
  7. Adding & Dropping Data
  8. GroupBy & Aggregate
  9. Merge & Join (part-1)
  10. Merge & Join (part-2)
  11. Plotting using pandas
  1. Introduction to matplotlib
  2. Matplotlib figure anatomy
  3. Basic line plot & Its components
  4. Matplotib GUI
  5. Format string
  6. Adjusting Colors
  1. Plotting types overview
  2. Line plot
  3. Scatter plot
  4. Area plot
  5. Bar plot
  6. Variants of bar plot
  7. Histrogram
  8. Pie chart

.Predictive Modelling

Data analysis Sagments

āϏāĻŦāĻšā§‡āϝāĻŧ⧇ āϏāĻšāϜ āĻāĻŦāĻ‚ āĻ•ā§āϰāĻŋā§Ÿā§‡āϟāĻŋāĻ­ āĻŽā§‡āĻĨāĻĄ āĻ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻļ⧇āĻ–āĻžāϰ āϝ⧁āĻ—āĻžāĻ¨ā§āϤāĻ•āĻžāϰ⧀ āϏāĻŽāĻžāϧāĻžāύāĨ¤

āĻļāĻŋāĻ–āĻŦ⧇āύ āχāωāύāĻŋāĻ• āωāĻĒāĻžā§Ÿā§‡ āĻŽāĻžāĻ¤ā§āϰ ā§Ēā§Ļ āϘāĻ¨ā§āϟāĻžāϰ āĻāχ āϞāĻžāĻ°ā§āĻŖāĻŋāĻ‚ āϏāĻŋāϰāĻŋāϜ āĻšāϤ⧇āĨ¤ āĻāĻŦāĻ‚ āĻĒāϰāĻŦāĻ°ā§āϤ⧀āϤ⧇ āĻāχ āĻĻāĻ•ā§āώāϤāĻž āĻ•āĻžāĻœā§‡ āϞāĻžāĻ—āĻžāύ āφāĻĒāύāĻžāϰ āύāĻŋāĻœā§‡āϰ āĻ­āĻŦāĻŋāĻˇā§āϝāϤ⧇

āĻŦāĻ°ā§āϤāĻŽāĻžāύ⧇ āχāωāϟāĻŋāωāĻŦ āĻ“ āĻ…āĻ¨ā§āϝāĻžāĻ¨ā§āϝ āĻĒā§āĻ˛ā§āϝāĻžāϟāĻĢāĻ°ā§āĻŽā§‡ Python Programming āύāĻŋā§Ÿā§‡ āĻšāĻžāϜāĻžāϰāĻ“ āϰāĻŋāϏ⧋āĻ°ā§āϏ āĻĨāĻžāĻ•āϞ⧇āĻ“, āĻŦ⧇āĻļāĻŋāϰāĻ­āĻžāĻ—āχ āĻ…āĻ—ā§‹āĻ›āĻžāϞ⧋ āĻ“ āĻŦāĻžāĻ¸ā§āϤāĻŦ āĻœā§€āĻŦāύ⧇āϰ āĻ•āĻžāĻœā§‡āϰ āϜāĻ¨ā§āϝ āϤ⧇āĻŽāύ āĻ•āĻžāĻ°ā§āϝāĻ•āϰ āύ⧟āĨ¤ āϤāĻžāχ āĻŦāĻžāĻ‚āϞāĻžāĻĻ⧇āĻļ⧇ āĻāχ āϏ⧇āĻ•ā§āϟāϰ⧇ āφāĻŽāϰāĻž āĻāĻ–āύ⧋ āĻ…āύ⧇āĻ• āĻĒāĻŋāĻ›āĻŋā§Ÿā§‡āĨ¤

āφāϰ āĻāχ āϏāĻŽāĻ¸ā§āϝāĻžāϰ āĻĒāĻžāĻ°ā§āĻŽāĻžāύ⧇āĻ¨ā§āϟ āϏāĻŽāĻžāϧāĻžāύ⧇āϰ āϜāĻ¨ā§āϝ Metasys Bangladesh āύāĻŋā§Ÿā§‡ āĻāϏ⧇āϛ⧇ āϏāĻŽā§āĻĒā§‚āĻ°ā§āĻŖ āĻ­āĻŋāĻ¨ā§āύāϧāĻ°ā§āĻŽā§€ Python Programming Masterclass đŸŽ¯ āϕ⧋āĻ°ā§āϏ⧇ āϏāĻĢāϟāĻ“ā§Ÿā§āϝāĻžāϰ āχāĻ¨ā§āϏāϟāϞ āĻĻā§‡ā§ŸāĻž āĻĨ⧇āϕ⧇ āĻļ⧁āϰ⧁ āĻ•āϰ⧇ āϕ⧋āϰ āĻĒāĻžāχāĻĨāύ⧇āϰ āϏāĻŦāĻ•āĻŋāϛ⧁ Step-by-Step āĻļāĻŋāĻ–āĻžāύ⧋ āĻšā§Ÿā§‡āϛ⧇ 🐍

DATA SCIENCE WITH PYTHON

[With  competetive programming & Robotics sagments]

COURSE FEATURE

āĻ¸ā§āĻ•āĻŋāϞ āĻāĻŽāύ āĻāĻ•āϟāĻž āϜāĻŋāύāĻŋāϏ āϝāĻž āĻ•āĻ–āύ āĻ“ āĻŦ⧃āĻĨāĻž āϝāĻžā§ŸāύāĻžāĨ¤ āφāĻĒāύāĻžāϰ āύāĻŋāϜ āĻāϰ āϜāĻ¨ā§āϝ āϏ⧇āϰāĻž āĻāĻ•āϟāĻŋ āχāύāϭ⧇āĻ¸ā§āϟāĻŽā§‡āĻ¨ā§āϟ āĻ•āϰ⧁āύ āφāϜāχ āϝāĻž āφāĻĒāύāĻžāϕ⧇ āϞāĻžāχāĻĢāϟāĻžāχāĻŽ āωāĻĒāĻ•ā§ƒāϤ āĻ•āϰāĻŦ⧇āĨ¤

āϞāĻžāχāĻĢāϟāĻžāχāĻŽ āĻāĻ•ā§āϏ⧇āϏ āĻāĻŦāĻ‚ āϏāĻžāĻĒā§‹āĻ°ā§āϟ

āϕ⧇āύ āĻāχ āϕ⧋āĻ°ā§āϏāϟāĻŋ āĻŦāĻžāĻ‚āϞāĻžāĻĻ⧇āĻļ⧇āϰ āĻŦ⧇āĻ¸ā§āϟ āĻāĻ¨ā§āĻĄ āĻŽā§‹āĻ¸ā§āϟ āĻāĻĄāĻ­āĻžāĻ¨ā§āϏāĻĄ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āϕ⧋āĻ°ā§āϏ?

āĻĒā§āϰāĻĨāĻŽā§‡ āĻļāĻŋāĻ–āĻŦ⧇āύ āϏāĻŋ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚

āφāĻĒāύāĻŋ āφāϗ⧇āϰ āĻĨ⧇āϕ⧇ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āϜāĻžāύ⧁āύ āĻŦāĻž āύāĻž āϜāĻžāύ⧁āύāĨ¤ āφāĻĒāύāĻžāϕ⧇ āύāϤ⧁āύ āωāĻĻā§āϝāĻŽā§‡ āĻ—ā§œā§‡ āϤ⧁āϞāϤ⧇ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻāϰ āĻŽāĻžāϤ⧃āĻ­āĻžāώāĻž āϏāĻŋ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻĨ⧇āϕ⧇āχ āφāĻŽāϰāĻž āĻĻ⧇āĻ–āĻŋā§Ÿā§‡āĻ›āĻŋāĨ¤ āϝāĻž āφāĻĒāύāĻžāϕ⧇ āĻļ⧁āĻ¨ā§āϝ āĻ…āĻŦāĻ¸ā§āĻĨāĻž āĻĨ⧇āϕ⧇ āφāĻ¤ā§āύāĻŦāĻŋāĻļā§āĻŦāĻžāϏ⧀ āĻ•āϰ⧇ āϤ⧁āϞāĻŦ⧇āĨ¤ āĻāĻŦāĻ‚ āĻĒāϰāĻŦāĻ°ā§āϤ⧀āϤ⧇ āĻĒāĻžāχāĻĨāύ āĻļ⧇āĻ–āĻžāϕ⧇ āφāϰāĻ“ āĻŦ⧇āĻļāĻŋ āϏāĻšāϜ āĻ•āϰ⧇ āĻĻāĻŋāĻŦ⧇āĨ¤ āϝāĻž āĻāχ āĻ…āĻĢāĻžāϰ⧇ āĻŦā§‹āύāĻžāϏ āĻšāĻŋāϏ⧇āĻŦ⧇ āĻĒāĻžāĻŦ⧇āύ

⧍⧟ āϤ⧇ āĻļāĻŋāĻ–āĻŦ⧇āύ āĻĒāĻžāχāĻĨāύ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚

āϏāĻŋ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻļ⧇āĻ–āĻž āφāĻĒāύāĻŋ āφāĻ¤ā§āύāĻŦāĻŋāĻļā§āĻŦāĻžāϏ⧀ āĻšā§Ÿā§‡ āĻāχ āĻŽāĻĄāĻŋāωāϞ⧇ āĻĒāĻžāχāĻĨāύ āĻāϰ A to Z āĻĄāĻŋāĻŸā§‡āχāϞ āĻāĻŦāĻ‚ āϏāĻšāϜ āĻŽā§‡āĻĨāĻĄ āĻ āĻļ⧇āĻ–āĻž āĻļ⧇āώ āĻ•āϰāĻŦ⧇āύāĨ¤ āϝāĻž āφāĻĒāύāĻžāϕ⧇ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āĻāϰ āϜāĻ—āϤ⧇ āϝ⧇āϤ⧇ āĻĒā§āϰāĻ¸ā§āϤ⧁āϤ āĻ•āϰāĻŦ⧇āĨ¤

ā§Šā§Ÿ āϤ⧇ āĻļāĻŋāĻ–āĻŦ⧇āύ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āĻāĻŦāĻ‚ āĻāύāĻžāϞāĻžāχāϏāĻŋāϏ

āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āϏ⧇āĻ•ā§āϟāϰ āĻ āĻĒāĻžāχāĻĨāύ āϜāύāĻĒā§āϰāĻŋ⧟ āĻšāĻ“ā§ŸāĻžā§Ÿ āĻāχ āĻŽāĻĄāĻŋāωāϞ⧇ āφāĻŽāϰāĻž āĻĒāĻžāχāĻĨāύ āĻĻāĻŋā§Ÿā§‡āχ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āĻļāĻŋāĻ–āĻŋā§Ÿā§‡āĻ›āĻŋāĨ¤ āϝāĻž āφāĻĒāύāĻžāϰ āĻļ⧇āĻ–āĻžāϕ⧇ āĻ•āϰāĻŦ⧇ āφāϰāĻ“ āĻŦ⧇āĻļāĻŋ āωāĻĒāĻ­ā§‹āĻ—āĻŽā§ŸāĨ¤

āϏāĻ°ā§āĻŦāĻļ⧇āώ⧇ āĻļāĻŋāĻ–āĻŦ⧇āύ āϰ⧋āĻŦāϟāĻŋāĻ•ā§āϏ

āϏāĻ°ā§āĻŦāĻļ⧇āώ⧇ āφāĻĒāύāĻžāϕ⧇ āχāωāύāĻŋāĻ• āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻžāϰ āĻšāĻŋāϏ⧇āĻŦ⧇ āĻ—ā§œā§‡ āϤ⧁āϞāϤ⧇ āφāĻŽāϰāĻž āϰ⧋āĻŦāϟāĻŋāĻ•ā§āϏ āĻŽāĻĄāĻŋāωāϞ āĻ“ āĻļāĻŋāĻ–āĻŋā§Ÿā§‡āĻ›āĻŋāĨ¤ āϝāĻž āĻ•āϰ⧇ āϤ⧁āϞāĻŦ⧇ āφāĻĒāύāĻžāϕ⧇ āĻ…āύāĻ¨ā§āϝāĻŽā§ŸāĨ¤

āϞāĻžāχāĻĢ āϟāĻžāχāĻŽ āϏāĻžāĻĒā§‹āĻ°ā§āϟ āĻāĻŦāĻ‚ āĻāĻ•ā§āϏ⧇āϏ

āĻāĻ•āĻŦāĻžāϰ āĻāύāϰ⧋āϞ āĻāϰ āϏāĻžāĻĨ⧇ āϏāĻžāĻĨ⧇ āϏāĻŽā§āĻĒ⧁āĻ°ā§āύ āϕ⧋āĻ°ā§āϏ āĻĒā§āϝāĻžāύ⧇āϞ āφāĻĒāύāĻžāϰ āχāĻŽā§‡āχāϞ āĻ āĻĒā§‡ā§Ÿā§‡ āϝāĻžāĻŦ⧇āύāĨ¤ āϝ⧇āϕ⧋āύ⧋ āϏāĻŽā§Ÿ āϝ⧇āϕ⧋āύ⧋ āϜāĻžā§ŸāĻ—āĻžā§Ÿ āĻŦāϏ⧇ āĻļāĻŋāĻ–āϤ⧇ āĻĒāĻžāϰāϛ⧇āύ āĻāĻŦāĻ‚ āϝ⧇āϕ⧋āύ⧋ āϏāĻŽāĻ¸ā§āϝāĻžāϰ āϜāĻ¨ā§āϝ āϞāĻžāχāĻ­ āϏāĻžāĻĒā§‹āĻ°ā§āϟ āĻĒāĻžāĻŦ⧇āύ āφāĻŽāĻžāĻĻ⧇āϰ āϏāĻžāĻĒā§‹āĻ°ā§āϟ āĻĒā§‹āĻ°ā§āϟāĻžāϞ⧇

ā§§ā§Ļ āϜāĻŋāĻŦāĻŋ āĻĒā§āϰāĻžāχāϭ⧇āϟ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āϰāĻŋāϏ⧋āĻ°ā§āϏ

āĻŦā§‹āύāĻžāϏ āĻšāĻŋāϏ⧇āĻŦ⧇ āĻĒāĻžāĻŦ⧇āύ ā§§ā§Ļ āϜāĻŋāĻŦāĻŋ āĻŦāĻŋāĻļāĻŋāĻˇā§āϟ āĻ…āĻĨ⧇āύāϟāĻŋāĻ• āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āϰāĻŋāϏ⧋āĻ°ā§āϏāĨ¤ āϝāĻž āφāĻĒāύāĻžāϕ⧇ āφāĻ¨ā§āϤāĻ°ā§āϜāĻžāϤāĻŋāĻ• āĻŽāĻžāύ⧇āϰ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻžāϰ āĻšāĻŋāϏ⧇āĻŦ⧇ āĻ—ā§œā§‡ āϤ⧁āϞāĻŦ⧇āĨ¤

13440432 (1)

āĻĒā§āϰāĻŋāĻŽāĻŋ⧟āĻžāĻŽ āϏāĻžāĻ°ā§āϟāĻĢāĻŋāϕ⧇āϟ

āϕ⧋āĻ°ā§āϏ āĻļ⧇āώ⧇ āĻĒāĻžāĻšā§āϛ⧇āύ āχāωāύāĻŋāĻ• āϏāĻžāĻ°ā§āϟāĻŋāĻĢāĻŋāϕ⧇āϟ āϝāĻž āφāĻĒāύāĻžāϰ āĻ•ā§āϝāĻžāϰāĻŋ⧟āĻžāϰ āĻāϰ āĻŦāĻŋāĻļ⧇āώ āϏāĻšāϝ⧋āĻ—ā§€ āĻāĻŦāĻ‚ āφāĻĒāύāĻžāϕ⧇ āĻāĻ•āĻžāϧāĻŋāĻ• āĻĻāĻ•ā§āώāϤāĻžāϰ āĻ…āϧāĻŋāĻ•āĻžāϰ⧀ āĻšāĻŋāϏ⧇āĻŦ⧇ āĻĒāϰāĻŋāϚāĻŋāϤāĻŋ āĻ•āϰāĻŦ⧇āĨ¤

āĻāĻ•āϜāύ āύ⧟!

ā§Ē āϜāύ āϜāĻŋāύāĻŋ⧟āĻžāϏ āϞāĻŋāĻĄāĻžāϰ āĻāĻ•āϏāĻžāĻĨ⧇!

āϕ⧇āĻŽāύ āĻšāϤ āϝāĻĻāĻŋ āχāĻ¨ā§āĻĄāĻžāĻ¸ā§āĻŸā§āϰāĻŋ āϞāĻŋāĻĄāĻžāϰāĻĻ⧇āϰ āϏāĻŋāĻ•ā§āϰ⧇āϟāϗ⧁āϞ⧋ āϜāĻžāύāϤ⧇ āĻĒāĻžāϰāϤāĻžāĻŽ!

āĻāĻŦāĻžāϰ āĻĒāĻžāϰāĻŦ⧇āύ!

āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻļāĻŋāĻ–āĻž āĻ•āĻŋ āϏāĻ¤ā§āϝāĻŋāχ āĻ•āĻ āĻŋāύ?

āϚāϞ⧁āύ āĻĻ⧇āϖ⧇ āύāĻŋāχ āĻļāĻŋāĻ•ā§āώāĻžāĻ°ā§āĻĨā§€āĻĻ⧇āϰ āĻĢāĻŋāĻĄāĻŦā§āϝāĻžāĻ•āĨ¤

āĻŽāĻĄāĻŋāωāϞ/āĻ•āĻžāϰāĻŋāϕ⧁āϞāĻžāĻŽ

đŸŽ–ā§Žā§Ļā§Ļā§Ļ+ āĻāϰ āĻ…āϧāĻŋāĻ• āĻļāĻŋāĻ•ā§āώāĻžāĻ°ā§āĻĨā§€ āϝ⧁āĻ•ā§āϤ āĻšā§Ÿā§‡āϛ⧇āύ āφāĻŽāĻžāĻĻ⧇āϰ āĻāχ āϝāĻžāĻ¤ā§āϰāĻžā§ŸāĨ¤āϝāĻžāϰ āĻŦ⧇āĻļāĻŋāϰ āϝ⧁āĻ•ā§āϤ āĻšāĻ“ā§ŸāĻžāϰ āĻ•āĻžāϰāύ āφāĻŽāĻžāĻĻ⧇āϰ
(āĻĒāĻžāχāĻĨāύ+ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ)

â™ģ āϝ⧇āϕ⧋āύ⧋ āĻŦā§āϝāĻžāĻ•āĻ—ā§āϰāĻžāωāĻ¨ā§āĻĄ āĻŦāĻž āĻŦ⧟āϏ⧀ āĻāϕ⧇āĻŦāĻžāϰ⧇ āĻļ⧁āĻ¨ā§āϝ āĻ…āĻŦāĻ¸ā§āĻĨāĻž āĻšāϤ⧇ āĻĒā§āϰāĻĢ⧇āĻļāύāĻžāϞ āϞ⧇āϭ⧇āϞ āĻĒāĻ°ā§āϝāĻ¨ā§āϤ āĻļāĻŋāĻ–āϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύāĨ¤ āĻļ⧁āϧ⧁āĻŽāĻžāĻ¤ā§āϰ āĻ•ā§āϞāĻžāϏ āϗ⧁āϞ⧋ āϏāĻŋāϰāĻŋ⧟āĻžāϞāĻŋ āĻĻ⧇āĻ–āĻŦ⧇āύ+ āĻ…āύ⧁āĻļā§€āϞāύ āĻ•āϰāĻŦ⧇āύāĨ¤ āĻ•āĻžāϰāύ āφāĻŽāϰāĻž āĻāĻ–āĻžāύ⧇ āĻāχ āϏ⧇āĻ•ā§āϟāϰ āĻāϰ āϝāĻž āĻ•āĻŋāϛ⧁ āφāϛ⧇ āϏāĻŦāĻ•āĻŋāϛ⧁ āύāĻŋā§Ÿā§‡,āϤāĻžāϰ āĻĒā§āϰāĻ¤ā§āϝ⧇āĻ•āϟāĻŋ āĻ…āĻ‚āĻļ āϕ⧇ āφāϞāĻžāĻĻāĻž āφāϞāĻžāĻĻāĻž āĻ•ā§āϞāĻžāϏ āĻĻāĻŋā§Ÿā§‡ āĻ•āĻžāĻ­āĻžāϰ āĻ•āϰ⧇āĻ›āĻŋāĨ¤āϝāĻžāϤ⧇ āĻāĻ•āĻĻāĻŽ āϛ⧋āϟāϰāĻžāĻ“ āϖ⧁āĻŦ āϏāĻšāĻœā§‡ āĻŦ⧁āϜāϤ⧇ āĻĒāĻžāϰ⧇āĨ¤A to Z āϟāĻĒāĻŋāĻ•āϏāĻŽā§āĻš,āĻĒā§āϰāĻ­āϞāĻŽ āϏāϞāĻ­āĻŋāĻ‚,āĻĒā§āϰāϝ⧇āĻ•ā§āϟ, āĻ•ā§āϝāĻžāϰāĻŋ⧟āĻžāϰ āĻ—āĻžāχāĻĄāϞāĻžāχāύ āϏāĻŦāĻ•āĻŋāϛ⧁āχ āĻĒāĻžāĻšā§āϛ⧇āύ āĻāĻ•āϏāĻžāĻĨ⧇āĨ¤
āϝāĻž āϝāĻž āĻļāĻŋāĻ–āϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύāσ
#Python + Data science Module

1.Python Installation
2.Anaconda and Jupiter
3.Anaconda and Jupiter Installation
4.Using Google Colab
5.Python Basic
6.Data Types and Variables
7.Operators
8.Functions
9.Typecasting and Comments
10.Review
11.Python Expression
12.Type Conversion
13.Expression and Statement
14.Comparison Operators
15.Logical Expression and Logical Operators
16.Operator Precedence
17.Python Conditionals
18.If statement
19. Programming Problem
20.Elif Statement
21.Python Loop
22.While Loop
23.Programming Problem with While Loop
24.For Loop and Range
25.Python Function
26.Declaring a Function
27.Local and Global Namespace
28.Programming Problem
29.Keyword Argument and Default Parameter
30.Python String
31.String Indexing and Slicing
32.Multiline Strings and Operators
33.String Methods
34. Exercise Problem
35.Python List
36.Data Structure
37.List Indexing and Slicing
38.Mutability and Aliasing
39.List Operators
40.List Methods
41.Nested list
42.Python Tuple
43.How to Declare a Tuple
44.Indexing and Slicing and Immutibility
45.Tuple Operators
46.Tuple Methods
47.Tuple Usage
48.Nested Tuple
49.Python Dictionary
50.1Dictionary Declaration and Indexing
51.Mutability and Aliasing
52.Dictionary Operators and Functions
53.Dictionary Methods
54.Nested Dictionary
55.Python Objects
56.Class
57.Objects and Class
58.Creating a Class
59.Why Do We Need Class
60.Python file handling
61.Text and Binary Files
62.Read, Write and Create Files
63.Python miscellaneous concepts
64.None type and del operator
65.Escape Sequence and f-string
66.Stride and Assert
67.Python modules
68.Importing Modules and print Module
69.Copy Module
70.Math Module
71.OS Module
72.OS Module and File Path
73.Datetime Module
74.Collections Module
75.Installing Third Party Packages
76.Numpy Introduction
77.Numpy Introduction and array
78.Data and Limitations
79.Numpy Data types
80.Creating Arrays
81.Array Attributes
82.Indexing and Slicing
83.Numpy array operation
84.Elementwise Arithmetic Operation
85.Broadcasting
86.Linear Algebra Operations
87.Numpy Calculation Methods
88.Numpy array manipulation
89.Copy and View
90.Conversion Methods
91.Shape Manipulation in Numpy
92.Numpy Element Manipulation
93.Value Manipulation and Array Join

✅āĻāχ āĻĒāĻ°ā§āϝāĻ¨ā§āϤ āĻāϏ⧇ āφāĻĒāύāĻžāϰ āĻĒāĻžāχāĻĨāύ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻļ⧇āĻ–āĻž āĻļ⧇āώ āĻšāĻŦ⧇āĨ¤ āφāĻĒāύāĻžāϰ āϜāĻ¨ā§āϝ āϏ⧁āĻ–āĻŦāϰ āĻšāϞ⧋ 😃 āĻāĻ–āύ āĻāχ āĻĒāĻžāχāĻĨāύ āĻĻāĻŋā§Ÿā§‡āχ āφāĻĒāύāĻžāϕ⧇ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āĻļ⧇āĻ–āĻžāύ⧋ āĻšāĻŦ⧇!āφāϏ⧁āύ āĻāĻ–āύ āĻĄāĻžāϟāĻž āϏāĻžāχāĻ¨ā§āϏ āĻāϰ āϜāĻ—āϤ⧇āĨ¤ (94-151)

94. data handling in numpy
95.Loading Data from Files
96.Missing Value Handling
97.Advanced Indexing in Numpy
98.Boolean Masking
99.Multiple Condition and Manipulation
100.Pandas introduction
101.Pandas dataframe and series
102.Why Pandas
103.Creating Dataframes
104.Pandas data munging
105.Pandas Data Munging Introduction
106.Reading Data from Files
107.Data Frame Basic Attributes
108.Basic Methods
109.Data Selection
110.Comparison Operators and Methods
111.Conditional Selection and Manipulation
112.Data Type Conversion
113.Missing Value Handling
114.Mathematical Operations
115.Calculation Methods
116.Saving Dataframe
117.Data Munging Workflow
118.Pandas data analysis
119.Dataset Introduction
120.Method Chaining
121.String Accessors
122.Datetime Accessor
123.Index and Column Manipulation
124.Sorting
125.Adding and Droping Data
126.GroupBy and Aggregate
127.Merge and Join (Part 1)
128.Merge and Join (Part 2)
129.Plotting using Pandas
130.Matplotib basics
131.Introduction to Matplotlib
132.Matplotlib Figure Anatomy
133.Basic Line Plot and its Components
134.Matplotlib GUI
135.Format String
136.Adjusting Colors
137.Matplotib plotting types
138.Plotting Types Overview
139.Line Plot
140.Scatter Plot
141.Area Plot
142.Bar Plot
143.Variants of Bar Plot
144.Histogram
145.Pie Chart
146.Eight practical projects.
147.Predictive Modelling
148.Python Programming
149.Data Analysis
150.Data Visualization (DataViz)
151.Model Selection

🧠Secret & unique method implement for growing brainstorming power & be genius from others.👑

āĻĒāĻžāĻŦ⧇āύ āϏāĻžāϰāĻĒā§āϰāĻžāχāϜāĻŋāĻ‚ āĻ—āĻŋāĻĢāϟ !

āĻĒāĻžāĻļāĻžāĻĒāĻžāĻļāĻŋ āĻĒāĻžāĻŦ⧇āύ āĻāĻ•āϟāĻŋ āĻāĻ•ā§āϏāĻŸā§āϰāĻž āĻĒā§āϰāĻžāχāϭ⧇āϟ āϰāĻŋāϏ⧋āĻ°ā§āϏ āĻĒā§āϝāĻžāύ⧇āϞāĨ¤ āĻāύāϰ⧋āϞ āĻāϰ āϏāĻžāĻĨ⧇ āϏāĻžāĻĨ⧇ āĻĒā§‡ā§Ÿā§‡ āϝāĻžāĻŦ⧇āύ āφāĻĒāύāĻžāϰ āϕ⧋āĻ°ā§āϏ āĻĒā§āϝāĻžāύ⧇āϞ⧇āĨ¤ āϝāĻž āφāĻĒāύāĻžāϕ⧇ āϞāĻ•ā§āώ āϟāĻžāĻ•āĻžāϰ āϭ⧇āĻ˛ā§āϝ⧁ āĻĻāĻŋāĻŦ⧇āĨ¤

āϝ⧇āĻ–āĻžāύ⧇ āĻĒā§āϰ⧋āĻ—ā§āϰāĻžāĻŽāĻŋāĻ‚ āĻĻ⧁āύāĻŋ⧟āĻžāϰ āϏāĻŋāĻ•ā§āϰ⧇āϟ āϏāĻ•āϞ āĻŽā§‡āĻĨāĻĄ, āĻŸā§‡āĻ•āύāĻŋāĻ•, āφāĻ¨ā§āϤāĻ°ā§āϜāĻžāϤāĻŋāĻ• āϰāĻŋāϏ⧋āĻ°ā§āϏ, āĻļāĻŋāϟāϏ āĻĒāĻžāĻŦ⧇āύāĨ¤ āϝāĻž āφāĻŽāĻžāĻĻ⧇āϰ āχāωāύāĻŋāĻ• āĻĻāĻŋāĻ• āĻāĻŦāĻ‚ āφāĻĒāύāĻžāϰ āϜāĻ¨ā§āϝ āϏāĻžāϰāĻĒā§āϰāĻžāχāϜāĻŋāĻ‚
āĻ—āĻŋāĻĢāϟ āĻšāϤ⧇ āϝāĻžāĻšā§āϛ⧇…

What will you get?

āφāĻ°ā§āϞāĻŋ āĻŦāĻžāĻ°ā§āĻĄ āĻ…āĻĢāĻžāϰ⧇ ā§§ā§Ļā§Ļā§Ļā§Ļ āϟāĻžāĻ•āĻž āĻ›āĻžā§œāĨ¤ (āϞāĻŋāĻŽāĻŋāĻŸā§‡āĻĄ āĻāĻĄāĻŋāĻļāύ)

āĻĒ⧇āĻŽā§‡āĻ¨ā§āϟ āϏāĻŽā§āĻĒāĻ¨ā§āύ āĻšāĻ“ā§ŸāĻžāϰ āϏāĻžāĻĨ⧇ āϏāĻžāĻĨ⧇, āĻĒā§āϝāĻžāϕ⧇āĻœā§‡āϰ āϏāĻ•āϞ āĻĢāĻžāχāϞ⧇āϰ āĻ…ā§āϝāĻžāĻ•ā§āϏ⧇āϏ āĻ¸ā§āĻŦāϝāĻŧāĻ‚āĻ•ā§āϰāĻŋāϝāĻŧāĻ­āĻžāĻŦ⧇ āφāĻĒāύāĻžāϰ āχāĻŽā§‡āχāϞ⧇ āĻĒ⧌āρāϛ⧇ āϝāĻžāĻŦ⧇āĨ¤.

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āϞāĻžāχāĻĢāϟāĻžāχāĻŽ āĻāĻ•ā§āϏ⧇āϏ āĻāĻŦāĻ‚ āϏāĻžāĻĒā§‹āĻ°ā§āϟ

  1. Python Installation
  1. Anaconda and Jupiter Installation
  2. Using Google Colab
  1. Data types & Variables
  2. Operators
  3. Functions
  4. Type casting & comments
  5. Review
  1. Type conversion
  2. Expression & Statement
  3. Comparison operators
  4. Logical expression & Logical operator
  5. Operator Precedence
  1. If statement
  2. A programming Problemn
  3. Elif Statement
  1. While Loop
  2. Programming problem with while loop
  3. For loop & Range
  1. Declaring a function
  2. Local & global name space
  3. A prograaming problem
  4. Keywar argument & Detail pararammeter
  1. String indexing & Slicing
  2. Multiline string & operators
  3. String Methods
  4. An excercise problem
  1. Data structure
  2. List indexing & Slicing
  3. Mutability & Aliasing
  4. List operators
  5. List Method
  6. Nested List
  1. How o deeclare a tuple
  2. Indexing & Slicing,Immutubility
  3. Tuple Operators
  4. Tuple Method
  5. Tuple Usage
  6. Nested touple
  1.  Dictionary  declaration & Indexing
  2. Mutability & Alliasing
  3. Dictionary operators & Functions
  4. Dictionary Methods
  5. Nested Dictionary
  1. Class
  2. Object & Class
  3. Creating a class
  4. Why do we need class
  1. Text & Binary files
  2. Read write & Create Files
  1. Non type & Dell operator
  2. Escape Sequence & F string
  3. Stride & Assert
  1. Importing modules & Print module
  2. Copy Module
  3. Math module
  4. Os module
  5. Os module & File path
  6. Datetime module 
  7. Collection module
  8. installing third party packages
  1. Numpy introduction & Array
  2. Data & Limitation
  3. Numpy Data types
  4. Creating Arrays
  5. Array atributes
  6. Indexing & Slicing
  1. Elementwise arithmetic Operation
  2. Broadcasting
  3. Linear algebra operations
  4. Numpy calculation methods
  1. Copy & View
  2. Conversion Methods
  3. Shape manipulation in numpy
  4. Numpy element manipulation
  5. Value manipulation & array join
  1. Loading data from files
  2. Missing Value Handling
  3. Advanced indexing in Numpy
  4. Boolean masking
  5. Multiple condition & Manipulation.
  1. Pandas data frame & Series
  2. Why pandas
  3. Creating Dataframes
  1. Pandas data munging introduction
  2. Reading Data from files
  3. Dataframe basic attributes
  4. Basic methods
  5. Data selection
  6. Conditional selection & Manipulation
  7. Data type conversion
  8. Missing value handling
  9. Mathmatical operations
  10. Calculation Method
  11. Saving Dataframe
  12. Data Munging Workflow
  1. Dataset Introduction
  2. Method Chaining
  3. String Accessors
  4. Datetime Accessors
  5. Index & Column Manipulation
  6. Sorting
  7. Adding & Dropping Data
  8. GroupBy & Aggregate
  9. Merge & Join (part-1)
  10. Merge & Join (part-2)
  11. Plotting using pandas
  1. Introduction to matplotlib
  2. Matplotlib figure anatomy
  3. Basic line plot & Its components
  4. Matplotib GUI
  5. Format string
  6. Adjusting Colors
  1. Plotting types overview
  2. Line plot
  3. Scatter plot
  4. Area plot
  5. Bar plot
  6. Variants of bar plot
  7. Histrogram
  8. Pie chart

.Predictive Modelling

Data analysis Sagments

āϕ⧋āĻ°ā§āϏāϟāĻŋ āϰ⧇āĻ•āĻ°ā§āĻĄā§‡āĻĄ āĻ­āĻŋāĻĄāĻŋāĻ“ āϟāĻŋāωāĻŸā§‹āϰāĻŋ⧟āĻžāϞ āϕ⧋āĻ°ā§āϏāĨ¤ āφāĻĒāύāĻŋ āϕ⧋āĻ°ā§āϏ⧇ āĻœā§Ÿā§‡āύ āĻ•āϰāĻžāϰ āĻĒāϰ āφāĻĒāύāĻžāϰ āχāĻŽā§‡āχāĻ˛ā§‡Â  āĻĒāĻžāĻ āĻžāύ⧋ āĻšāĻŦ⧇āĨ¤ āφāĻĒāύāĻŋ āĻ­āĻŋāĻĄāĻŋāĻ“ āĻĻ⧇āĻ–āϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύāĨ¤

āϕ⧋āĻ°ā§āϏ⧇ āϏāĻ°ā§āĻŦāĻŽā§‹āϟ ⧍ā§Ļā§Ē āϟāĻŋ āĻ•ā§āϞāĻžāϏ āφāϛ⧇āĨ¤ āϏāĻ°ā§āĻŦāĻŽā§‹āϟ āĻĄāĻŋāωāϰ⧇āĻļāύ ā§Šā§Ģ āϘāĻ¨ā§āϟāĻž +

āĻāϟāĻž āĻĄāĻŋāĻĒ⧇āĻ¨ā§āĻĄ āĻ•āϰāĻŦ⧇ āφāĻĒāύāĻžāϰ āωāĻĒāϰ, āφāĻĒāύāĻžāϰ āĻļ⧇āĻ–āĻžāϰ āĻ•ā§āϝāĻžāĻĒāĻžāϏāĻŋāϟāĻŋ āϕ⧇āĻŽāύ, āĻĒā§āϰāϤāĻŋāĻĻāĻŋāύ āϕ⧇āĻŽāύ āϏāĻŽā§Ÿ āĻĻāĻŋāĻšā§āϛ⧇āύ āϏ⧇āϟāĻžāϰ āωāĻĒāϰāĨ¤ āϕ⧇āω ⧍ā§Ļ-⧍ā§Ģ āĻĻāĻŋāύ⧇ , āϕ⧇āω ⧍ āĻŽāĻžāϏ⧇ āφāĻŦāĻžāϰ āĻ•āĻžāϰ⧋āϰ ā§Š āĻŽāĻžāϏ āϞāĻžāĻ—āϤ⧇ āĻĒāĻžāϰ⧇āĨ¤ āĻĒā§āϰāϤāĻŋāĻĻāĻŋāύ ā§§-⧍ āϘāĻ¨ā§āϟāĻž āϏāĻŽā§Ÿ āĻĻāĻŋāϞ⧇ ⧍-ā§Š āĻŽāĻžāϏ āχ āϝāĻĨ⧇āĻˇā§āϟāĨ¤

āφāĻĒāύāĻžāϰ āϝ⧇āϕ⧋āύ⧋ āϏāĻŽāĻ¸ā§āϝāĻžāϰ āϜāĻ¨ā§āϝ āϞāĻžāχāĻ­ āϏāĻžāĻĒā§‹āĻ°ā§āϟ āĻĒāĻžāĻŦ⧇āύāĨ¤ We are too much supportive and friendly… āφāĻŽāϰāĻž āĻšā§‹ā§ŸāĻžāϟāϏāĻ…ā§āϝāĻžāĻĒ⧇ āϏāϰāĻžāϏāϰāĻŋ āĻ“ā§ŸāĻžāύ āϟ⧁ āĻ“ā§ŸāĻžāύ āϏāĻžāĻĒā§‹āĻ°ā§āϟ āĻ•āϰ⧇ āĻĨāĻžāĻ•āĻŋ

āϞāĻžāχāĻĢāϟāĻžāχāĻŽ āĻ…ā§āϝāĻžāĻ•ā§āϏ⧇āϏ āĻāĻŦāĻ‚ āϏāĻžāĻĒā§‹āĻ°ā§āϟ

āϕ⧋āĻ°ā§āϏāϟāĻŋ āϏāĻŽā§āĻĒ⧁āĻ°ā§āύ āϜāĻŋāϰ⧋ āϞ⧇āϭ⧇āϞ āĻĨ⧇āϕ⧇ āĻļ⧁āϰ⧁ āĻšā§Ÿā§‡ āĻĒā§āϰāĻĢ⧇āĻļāύāĻžāϞ āϞ⧇āϭ⧇āϞ āĻĒāĻ°ā§āϝāĻ¨ā§āϤāĨ¤ āφāĻĒāύāĻžāϰ āϏāĻĢāϞāϤāĻž āϞāĻžāϭ⧇āϰ āϜāĻ¨ā§āϝ āĻāϟāĻŋāχ āϝāĻĨ⧇āĻˇā§āϟāĨ¤ āϝ⧇āϕ⧋āύ⧋ āĻŦā§āϝāĻžāĻ•āĻ—ā§āϰāĻžāωāĻ¨ā§āĻĄ āĻŦāĻž āϝ⧇āϕ⧋āύ⧋ āĻŦ⧟āϏ⧀ āϏāĻšāĻœā§‡ āĻļāĻŋāĻ–āϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύāĨ¤ āϏāĻŽā§āĻĒ⧁āĻ°ā§āύ āĻĄāĻŋāĻŸā§‡āχāϞāĻ­āĻžāĻŦ⧇ āϏāĻšāϜ āωāĻĒāĻ¸ā§āĻšāĻžāĻĒāύ⧇ āĻļ⧇āĻ–āĻžāύ⧋ āĻšā§Ÿā§‡āϛ⧇ āϝāĻž āφāĻĒāύāĻžāϕ⧇ āĻ…āĻ¨ā§āϝāϰāĻ•āĻŽ āĻ…āĻ­āĻŋāĻœā§āĻžāϤāĻž āĻĒā§āϰāĻĻāĻžāύ āĻ•āϰāĻŦ⧇

āĻœā§Ÿā§‡āύ āĻ•āϰ⧁āύ āĻ…āĻĨāĻŦāĻž āĻāύāϰ⧋āϞ āĻ•āϰ⧁āύ āĻŦāĻžāϟāύ⧇ āĻ•ā§āϞāĻŋāĻ• āĻ•āϰāĻžāϰ āĻĒāϰ āωāĻ˛ā§āϞ⧇āĻ–āĻŋāϤ āĻĢāĻ°ā§āĻŽā§‡ āφāĻĒāύāĻžāϰ āύāĻžāĻŽ, āĻĢā§‹āύ āύāĻžāĻŽā§āĻŦāĻžāϰ āĻāĻŦāĻ‚ āχāĻŽā§‡āχāϞ āĻĒā§āϰāĻĻāĻžāύ āĻ•āϰāϤ⧇ āĻšāĻŦ⧇āĨ¤ āϤāĻžāϰāĻĒāϰ āĻĒāĻ›āĻ¨ā§āĻĻ⧇āϰ āĻĒ⧇āĻŽā§‡āĻ¨ā§āϟ āĻ…āĻĒāĻļāύ āϏāĻŋāϞ⧇āĻ•ā§āϟ āĻ•āϰ⧇ āĻĒ⧇āĻŽā§‡āĻ¨ā§āϟ āϏāĻŽā§āĻĒāĻ¨ā§āύ āĻ•āϰāϤ⧇ āĻšāĻŦ⧇āĨ¤ āĻĒ⧇āĻŽā§‡āĻ¨ā§āϟ āϏāĻŽā§āĻĒāĻ¨ā§āύ āĻšāĻ“ā§ŸāĻžāϰ āϏāĻžāĻĨ⧇ āϏāĻžāĻĨ⧇ āφāĻĒāύāĻžāϰ āχāĻŽā§‡āχāϞ āĻ āϕ⧋āĻ°ā§āϏ āĻĒā§āϝāĻžāύ⧇āϞ āĻāĻŦāĻ‚ āĻĒā§āĻ°ā§Ÿā§‹āϜāĻ¨ā§€ā§Ÿ āϤāĻĨā§āϝ āϚāϞ⧇ āϝāĻžāĻŦ⧇āĨ¤ āĻāĻŦāĻ‚ āĻļ⧁āϰ⧁ āĻ•āϰāϤ⧇ āĻĒāĻžāϰāĻŦ⧇āύ āφāĻĒāύāĻžāϰ āĻļ⧇āĻ–āĻžāϰ āϝāĻžāĻ¤ā§āϰāĻžāĨ¤

Address List

Company Inc.

Our Address

Address: 62/B ,North Dhanmondi,Kalabagan, Dhaka-1205
Mobile No: 01610922183
Email: metasysbangladesh@gmail.com
Website: www.metasysbd.com
Trade no: 032700