📘 PHASE 1: PYTHON BASICS (FOUNDATION) 1️⃣ Python Introduction
Python kya hai
Python kaha use hota hai (DS, ML, Web)
Python vs C vs Java
Interpreter kya hota hai
2️⃣ A. Variables & Data Types
Padhna hai:
1.Variable kya hota hai
2.Naming rules
3.Dynamic typing
B. Data Types (VERY IMPORTANT):
1.int
2.float
3.string
4.boolean
5.type()
3️⃣ Input / Output
1.input()
2.print()
3.type casting (int(), float())
4️⃣ Operators
1.Arithmetic (+ - * / %)
2.Relational (>, <, ==)
3.Logical (and, or, not)
4.Assignment (=, +=)
5.Membership (in)
5️⃣ Conditional Statements
1.if
2.if-else
3.if-elif-else
4.nested if
6️⃣ Loops
1.for loop
2.while loop
3.break
4.continue
5.pass
7️⃣ Functions
1.function definition
2.parameters
3.return
4.default arguments
5.recursion (basic)
8️⃣ Python Collections (VERY VERY IMPORTANT 🔥)
🔹 List
1.list kya hoti hai
2.indexing
3.slicing
4.append, insert
5.remove, pop
6.sort, reverse
7.copy
8.nested list
🔹 Tuple
1.tuple kya hota hai
2.list vs tuple
3.packing & unpacking
🔹 Set
1.set kya hota hai
2.unique elements
3.add, remove
4.union, intersection
🔹 Dictionary
1.key-value pair
2.access values
3.update
4.delete
5.loop in dict
9️⃣ File Handling
1.open()
2.read()
3.write()
4.append
5.CSV file basics
1️⃣0️⃣ OOP (Basic)
1.class
2.object
3.init
4.inheritance (basic)
5.encapsulation (basic)
📘 PHASE 2: DSA (DATA STRUCTURES & ALGORITHMS)
❗ Data Science ke liye HARD DSA nahi chahiye ✔️ Logic + understanding enough
1️⃣ Array (MOST IMPORTANT 🔥)
Definition: Array ek data structure hai jo same type ke data ko continuous memory me store karta hai.
1.Padhna hai:
2.array kya hota hai
3.indexing
4.traversal
5.insertion
6.deletion
7.searching (linear search)
8.sorting (basic)
👉 Practice:
1.sum of array
2.max/min element
3.reverse array
4.frequency count
2️⃣ String
1.string kya hoti hai
2.indexing
3.slicing
4.string methods
5.palindrome
6.frequency count
3️⃣ Linked List (BASIC ONLY)
1.linked list kya hoti hai
2.node
3.traversal
4.insertion (beginning)
5.deletion (basic)
4️⃣ Stack
1.stack kya hota hai
2.push
3.pop
4.peek
5.real life example
5️⃣ Queue
1.queue kya hota hai
2.enqueue
3.dequeue
4.circular queue (idea)
6️⃣ Searching
1.Linear search
2.Binary search (concept only)
7️⃣ Sorting
1.Bubble sort
2.Selection sort
3.Insertion sort
4.Python sort()
📌 DSA yahin tak kaafi hai Data Science ke liye ❌ Graph, Tree, DP deep nahi chahiye
📘 PHASE 3: MATHEMATICS & STATISTICS 1️⃣ Statistics Basics
1.Mean
2.Median
3.Mode
4.Range
5.Variance
6.Standard Deviation
2️⃣ Probability
1.probability kya hoti hai
2.events
3.basic formula
3️⃣ Linear Algebra (Basic)
1.scalar
2.vector
3.matrix
4.matrix operations
📘 PHASE 4: NUMPY
1.numpy kya hai
2.array creation
3.array shape
4.reshape
5.indexing
s6.licing
7.mathematical operations
8.axis concept
📘 PHASE 5: PANDAS (VERY IMPORTANT 🔥🔥) 1️⃣ Series
1.create series
2.indexing
2️⃣ DataFrame
1.read_csv()
2.head(), tail()
3.info()
4.describe()
5.column access
6.row access (iloc, loc)
3️⃣ Data Cleaning
1.missing values
2.dropna()
3.fillna()
4.duplicates
5.rename columns
4️⃣ Data Analysis
1.groupby()
2.aggregation
3.sorting
4.filtering
📘 PHASE 6: DATA VISUALIZATION Tools:
1.Matplotlib
2.Seaborn
3.Charts:
4.line chart
5.bar chart
6.histogram
7.pie chart
8.box plot
📘 PHASE 7: SQL
1.database kya hota hai
2.table
3.primary key
4.Queries:
5.SELECT
6.WHERE
7.AND / OR
8.ORDER BY
9.GROUP BY
10.HAVING
11.JOIN (inner, left)
12.subquery (basic)
📘 PHASE 8: MACHINE LEARNING Basics
1.ML kya hai
2.types of ML
3.supervised vs unsupervised
4.Algorithms (IMPORTANT LIST)
5.Linear Regression
6.Logistic Regression
7.KNN
8.Decision Tree
9.Random Forest
10.Naive Bayes
11.K-Means
12.Concepts
13.training data
14.testing data
15.accuracy
16.overfitting
17.underfitting
📘 PHASE 9: PROJECTS & JOB READY A.Projects:
1.student result analysis
2.sales prediction
3.house price prediction
4.loan approval system
B.Tools:
1.GitHub
2.Resume
3.Kaggle
🔥 FINAL TRUTH (IMPORTANT)
👉 Data Science =
Python + DSA (basic) + Statistics + Pandas + ML + Projects