SQL Essential Concepts for Data Analyst Interviews โ
1. SQL Syntax: Understand the basic structure of SQL queries, which typically include
2. SELECT Statement: Learn how to use the
3. WHERE Clause: Use the
4. JOIN Operations: Master the different types of joinsโ
5. GROUP BY and HAVING Clauses: Use the
6. ORDER BY Clause: Sort the result set of a query by one or more columns using the
7. Aggregate Functions: Be familiar with aggregate functions like
8. DISTINCT Keyword: Use the
9. LIMIT/OFFSET Clauses: Understand how to limit the number of rows returned by a query using
10. Subqueries: Learn how to write subqueries, or nested queries, which are queries within another SQL query. Subqueries can be used in
11. UNION and UNION ALL: Know the difference between
12. IN, BETWEEN, and LIKE Operators: Use the
13. NULL Handling: Understand how to work with
14. CASE Statements: Use the
15. Indexes: Know the basics of indexing, including how indexes can improve query performance by speeding up the retrieval of rows. Understand when to create an index and the trade-offs in terms of storage and write performance.
16. Data Types: Be familiar with common SQL data types, such as
17. String Functions: Learn key string functions like
18. Date and Time Functions: Master date and time functions such as
19. INSERT, UPDATE, DELETE Statements: Understand how to use
20. Constraints: Know the role of constraints like
Here you can find SQL Interview Resources๐
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
1. SQL Syntax: Understand the basic structure of SQL queries, which typically include
SELECT, FROM, WHERE, GROUP BY, HAVING, and ORDER BY clauses. Know how to write queries to retrieve data from databases.2. SELECT Statement: Learn how to use the
SELECT statement to fetch data from one or more tables. Understand how to specify columns, use aliases, and perform simple arithmetic operations within a query.3. WHERE Clause: Use the
WHERE clause to filter records based on specific conditions. Familiarize yourself with logical operators like =, >, <, >=, <=, <>, AND, OR, and NOT.4. JOIN Operations: Master the different types of joinsโ
INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOINโto combine rows from two or more tables based on related columns.5. GROUP BY and HAVING Clauses: Use the
GROUP BY clause to group rows that have the same values in specified columns and aggregate data with functions like COUNT(), SUM(), AVG(), MAX(), and MIN(). The HAVING clause filters groups based on aggregate conditions.6. ORDER BY Clause: Sort the result set of a query by one or more columns using the
ORDER BY clause. Understand how to sort data in ascending (ASC) or descending (DESC) order.7. Aggregate Functions: Be familiar with aggregate functions like
COUNT(), SUM(), AVG(), MIN(), and MAX() to perform calculations on sets of rows, returning a single value.8. DISTINCT Keyword: Use the
DISTINCT keyword to remove duplicate records from the result set, ensuring that only unique records are returned.9. LIMIT/OFFSET Clauses: Understand how to limit the number of rows returned by a query using
LIMIT (or TOP in some SQL dialects) and how to paginate results with OFFSET.10. Subqueries: Learn how to write subqueries, or nested queries, which are queries within another SQL query. Subqueries can be used in
SELECT, WHERE, FROM, and HAVING clauses to provide more specific filtering or selection.11. UNION and UNION ALL: Know the difference between
UNION and UNION ALL. UNION combines the results of two queries and removes duplicates, while UNION ALL combines all results including duplicates.12. IN, BETWEEN, and LIKE Operators: Use the
IN operator to match any value in a list, the BETWEEN operator to filter within a range, and the LIKE operator for pattern matching with wildcards (%, _).13. NULL Handling: Understand how to work with
NULL values in SQL, including using IS NULL, IS NOT NULL, and handling nulls in calculations and joins.14. CASE Statements: Use the
CASE statement to implement conditional logic within SQL queries, allowing you to create new fields or modify existing ones based on specific conditions.15. Indexes: Know the basics of indexing, including how indexes can improve query performance by speeding up the retrieval of rows. Understand when to create an index and the trade-offs in terms of storage and write performance.
16. Data Types: Be familiar with common SQL data types, such as
VARCHAR, CHAR, INT, FLOAT, DATE, and BOOLEAN, and understand how to choose the appropriate data type for a column.17. String Functions: Learn key string functions like
CONCAT(), SUBSTRING(), REPLACE(), LENGTH(), TRIM(), and UPPER()/LOWER() to manipulate text data within queries.18. Date and Time Functions: Master date and time functions such as
NOW(), CURDATE(), DATEDIFF(), DATEADD(), and EXTRACT() to handle and manipulate date and time data effectively.19. INSERT, UPDATE, DELETE Statements: Understand how to use
INSERT to add new records, UPDATE to modify existing records, and DELETE to remove records from a table. Be aware of the implications of these operations, particularly in maintaining data integrity.20. Constraints: Know the role of constraints like
PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, and CHECK in maintaining data integrity and ensuring valid data entry in your database.Here you can find SQL Interview Resources๐
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
โค1
Complete roadmap to learn Python and Data Structures & Algorithms (DSA) in 2 months
### Week 1: Introduction to Python
Day 1-2: Basics of Python
- Python setup (installation and IDE setup)
- Basic syntax, variables, and data types
- Operators and expressions
Day 3-4: Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
Day 5-6: Functions and Modules
- Function definitions, parameters, and return values
- Built-in functions and importing modules
Day 7: Practice Day
- Solve basic problems on platforms like HackerRank or LeetCode
### Week 2: Advanced Python Concepts
Day 8-9: Data Structures in Python
- Lists, tuples, sets, and dictionaries
- List comprehensions and generator expressions
Day 10-11: Strings and File I/O
- String manipulation and methods
- Reading from and writing to files
Day 12-13: Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance, polymorphism, encapsulation
Day 14: Practice Day
- Solve intermediate problems on coding platforms
### Week 3: Introduction to Data Structures
Day 15-16: Arrays and Linked Lists
- Understanding arrays and their operations
- Singly and doubly linked lists
Day 17-18: Stacks and Queues
- Implementation and applications of stacks
- Implementation and applications of queues
Day 19-20: Recursion
- Basics of recursion and solving problems using recursion
- Recursive vs iterative solutions
Day 21: Practice Day
- Solve problems related to arrays, linked lists, stacks, and queues
### Week 4: Fundamental Algorithms
Day 22-23: Sorting Algorithms
- Bubble sort, selection sort, insertion sort
- Merge sort and quicksort
Day 24-25: Searching Algorithms
- Linear search and binary search
- Applications and complexity analysis
Day 26-27: Hashing
- Hash tables and hash functions
- Collision resolution techniques
Day 28: Practice Day
- Solve problems on sorting, searching, and hashing
### Week 5: Advanced Data Structures
Day 29-30: Trees
- Binary trees, binary search trees (BST)
- Tree traversals (in-order, pre-order, post-order)
Day 31-32: Heaps and Priority Queues
- Understanding heaps (min-heap, max-heap)
- Implementing priority queues using heaps
Day 33-34: Graphs
- Representation of graphs (adjacency matrix, adjacency list)
- Depth-first search (DFS) and breadth-first search (BFS)
Day 35: Practice Day
- Solve problems on trees, heaps, and graphs
### Week 6: Advanced Algorithms
Day 36-37: Dynamic Programming
- Introduction to dynamic programming
- Solving common DP problems (e.g., Fibonacci, knapsack)
Day 38-39: Greedy Algorithms
- Understanding greedy strategy
- Solving problems using greedy algorithms
Day 40-41: Graph Algorithms
- Dijkstraโs algorithm for shortest path
- Kruskalโs and Primโs algorithms for minimum spanning tree
Day 42: Practice Day
- Solve problems on dynamic programming, greedy algorithms, and advanced graph algorithms
### Week 7: Problem Solving and Optimization
Day 43-44: Problem-Solving Techniques
- Backtracking, bit manipulation, and combinatorial problems
Day 45-46: Practice Competitive Programming
- Participate in contests on platforms like Codeforces or CodeChef
Day 47-48: Mock Interviews and Coding Challenges
- Simulate technical interviews
- Focus on time management and optimization
Day 49: Review and Revise
- Go through notes and previously solved problems
- Identify weak areas and work on them
### Week 8: Final Stretch and Project
Day 50-52: Build a Project
- Use your knowledge to build a substantial project in Python involving DSA concepts
Day 53-54: Code Review and Testing
- Refactor your project code
- Write tests for your project
Day 55-56: Final Practice
- Solve problems from previous contests or new challenging problems
Day 57-58: Documentation and Presentation
- Document your project and prepare a presentation or a detailed report
Day 59-60: Reflection and Future Plan
- Reflect on what you've learned
- Plan your next steps (advanced topics, more projects, etc.)
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://t.iss.one/free4unow_backup
ENJOY LEARNING ๐๐
### Week 1: Introduction to Python
Day 1-2: Basics of Python
- Python setup (installation and IDE setup)
- Basic syntax, variables, and data types
- Operators and expressions
Day 3-4: Control Structures
- Conditional statements (if, elif, else)
- Loops (for, while)
Day 5-6: Functions and Modules
- Function definitions, parameters, and return values
- Built-in functions and importing modules
Day 7: Practice Day
- Solve basic problems on platforms like HackerRank or LeetCode
### Week 2: Advanced Python Concepts
Day 8-9: Data Structures in Python
- Lists, tuples, sets, and dictionaries
- List comprehensions and generator expressions
Day 10-11: Strings and File I/O
- String manipulation and methods
- Reading from and writing to files
Day 12-13: Object-Oriented Programming (OOP)
- Classes and objects
- Inheritance, polymorphism, encapsulation
Day 14: Practice Day
- Solve intermediate problems on coding platforms
### Week 3: Introduction to Data Structures
Day 15-16: Arrays and Linked Lists
- Understanding arrays and their operations
- Singly and doubly linked lists
Day 17-18: Stacks and Queues
- Implementation and applications of stacks
- Implementation and applications of queues
Day 19-20: Recursion
- Basics of recursion and solving problems using recursion
- Recursive vs iterative solutions
Day 21: Practice Day
- Solve problems related to arrays, linked lists, stacks, and queues
### Week 4: Fundamental Algorithms
Day 22-23: Sorting Algorithms
- Bubble sort, selection sort, insertion sort
- Merge sort and quicksort
Day 24-25: Searching Algorithms
- Linear search and binary search
- Applications and complexity analysis
Day 26-27: Hashing
- Hash tables and hash functions
- Collision resolution techniques
Day 28: Practice Day
- Solve problems on sorting, searching, and hashing
### Week 5: Advanced Data Structures
Day 29-30: Trees
- Binary trees, binary search trees (BST)
- Tree traversals (in-order, pre-order, post-order)
Day 31-32: Heaps and Priority Queues
- Understanding heaps (min-heap, max-heap)
- Implementing priority queues using heaps
Day 33-34: Graphs
- Representation of graphs (adjacency matrix, adjacency list)
- Depth-first search (DFS) and breadth-first search (BFS)
Day 35: Practice Day
- Solve problems on trees, heaps, and graphs
### Week 6: Advanced Algorithms
Day 36-37: Dynamic Programming
- Introduction to dynamic programming
- Solving common DP problems (e.g., Fibonacci, knapsack)
Day 38-39: Greedy Algorithms
- Understanding greedy strategy
- Solving problems using greedy algorithms
Day 40-41: Graph Algorithms
- Dijkstraโs algorithm for shortest path
- Kruskalโs and Primโs algorithms for minimum spanning tree
Day 42: Practice Day
- Solve problems on dynamic programming, greedy algorithms, and advanced graph algorithms
### Week 7: Problem Solving and Optimization
Day 43-44: Problem-Solving Techniques
- Backtracking, bit manipulation, and combinatorial problems
Day 45-46: Practice Competitive Programming
- Participate in contests on platforms like Codeforces or CodeChef
Day 47-48: Mock Interviews and Coding Challenges
- Simulate technical interviews
- Focus on time management and optimization
Day 49: Review and Revise
- Go through notes and previously solved problems
- Identify weak areas and work on them
### Week 8: Final Stretch and Project
Day 50-52: Build a Project
- Use your knowledge to build a substantial project in Python involving DSA concepts
Day 53-54: Code Review and Testing
- Refactor your project code
- Write tests for your project
Day 55-56: Final Practice
- Solve problems from previous contests or new challenging problems
Day 57-58: Documentation and Presentation
- Document your project and prepare a presentation or a detailed report
Day 59-60: Reflection and Future Plan
- Reflect on what you've learned
- Plan your next steps (advanced topics, more projects, etc.)
Best DSA RESOURCES: https://topmate.io/coding/886874
Credits: https://t.iss.one/free4unow_backup
ENJOY LEARNING ๐๐
โค1๐1
SQL Essential Concepts for Data Analyst Interviews โ
1. SQL Syntax: Understand the basic structure of SQL queries, which typically include
2. SELECT Statement: Learn how to use the
3. WHERE Clause: Use the
4. JOIN Operations: Master the different types of joinsโ
5. GROUP BY and HAVING Clauses: Use the
6. ORDER BY Clause: Sort the result set of a query by one or more columns using the
7. Aggregate Functions: Be familiar with aggregate functions like
8. DISTINCT Keyword: Use the
9. LIMIT/OFFSET Clauses: Understand how to limit the number of rows returned by a query using
10. Subqueries: Learn how to write subqueries, or nested queries, which are queries within another SQL query. Subqueries can be used in
11. UNION and UNION ALL: Know the difference between
12. IN, BETWEEN, and LIKE Operators: Use the
13. NULL Handling: Understand how to work with
14. CASE Statements: Use the
15. Indexes: Know the basics of indexing, including how indexes can improve query performance by speeding up the retrieval of rows. Understand when to create an index and the trade-offs in terms of storage and write performance.
16. Data Types: Be familiar with common SQL data types, such as
17. String Functions: Learn key string functions like
18. Date and Time Functions: Master date and time functions such as
19. INSERT, UPDATE, DELETE Statements: Understand how to use
20. Constraints: Know the role of constraints like
Here you can find SQL Interview Resources๐
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
1. SQL Syntax: Understand the basic structure of SQL queries, which typically include
SELECT, FROM, WHERE, GROUP BY, HAVING, and ORDER BY clauses. Know how to write queries to retrieve data from databases.2. SELECT Statement: Learn how to use the
SELECT statement to fetch data from one or more tables. Understand how to specify columns, use aliases, and perform simple arithmetic operations within a query.3. WHERE Clause: Use the
WHERE clause to filter records based on specific conditions. Familiarize yourself with logical operators like =, >, <, >=, <=, <>, AND, OR, and NOT.4. JOIN Operations: Master the different types of joinsโ
INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOINโto combine rows from two or more tables based on related columns.5. GROUP BY and HAVING Clauses: Use the
GROUP BY clause to group rows that have the same values in specified columns and aggregate data with functions like COUNT(), SUM(), AVG(), MAX(), and MIN(). The HAVING clause filters groups based on aggregate conditions.6. ORDER BY Clause: Sort the result set of a query by one or more columns using the
ORDER BY clause. Understand how to sort data in ascending (ASC) or descending (DESC) order.7. Aggregate Functions: Be familiar with aggregate functions like
COUNT(), SUM(), AVG(), MIN(), and MAX() to perform calculations on sets of rows, returning a single value.8. DISTINCT Keyword: Use the
DISTINCT keyword to remove duplicate records from the result set, ensuring that only unique records are returned.9. LIMIT/OFFSET Clauses: Understand how to limit the number of rows returned by a query using
LIMIT (or TOP in some SQL dialects) and how to paginate results with OFFSET.10. Subqueries: Learn how to write subqueries, or nested queries, which are queries within another SQL query. Subqueries can be used in
SELECT, WHERE, FROM, and HAVING clauses to provide more specific filtering or selection.11. UNION and UNION ALL: Know the difference between
UNION and UNION ALL. UNION combines the results of two queries and removes duplicates, while UNION ALL combines all results including duplicates.12. IN, BETWEEN, and LIKE Operators: Use the
IN operator to match any value in a list, the BETWEEN operator to filter within a range, and the LIKE operator for pattern matching with wildcards (%, _).13. NULL Handling: Understand how to work with
NULL values in SQL, including using IS NULL, IS NOT NULL, and handling nulls in calculations and joins.14. CASE Statements: Use the
CASE statement to implement conditional logic within SQL queries, allowing you to create new fields or modify existing ones based on specific conditions.15. Indexes: Know the basics of indexing, including how indexes can improve query performance by speeding up the retrieval of rows. Understand when to create an index and the trade-offs in terms of storage and write performance.
16. Data Types: Be familiar with common SQL data types, such as
VARCHAR, CHAR, INT, FLOAT, DATE, and BOOLEAN, and understand how to choose the appropriate data type for a column.17. String Functions: Learn key string functions like
CONCAT(), SUBSTRING(), REPLACE(), LENGTH(), TRIM(), and UPPER()/LOWER() to manipulate text data within queries.18. Date and Time Functions: Master date and time functions such as
NOW(), CURDATE(), DATEDIFF(), DATEADD(), and EXTRACT() to handle and manipulate date and time data effectively.19. INSERT, UPDATE, DELETE Statements: Understand how to use
INSERT to add new records, UPDATE to modify existing records, and DELETE to remove records from a table. Be aware of the implications of these operations, particularly in maintaining data integrity.20. Constraints: Know the role of constraints like
PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, and CHECK in maintaining data integrity and ensuring valid data entry in your database.Here you can find SQL Interview Resources๐
https://t.iss.one/DataSimplifier
Share with credits: https://t.iss.one/sqlspecialist
Hope it helps :)
โค3
โก๏ธ Understanding the 5 loops of JavaScript
๐ Loops offer a quick & easy way to do something repeatedly.
1. JavaScript For loop
Repeats a block of code as long as a certain condition is met.
Typically, used to loop through a block of code a specific amount of times.
2. JavaScript while loop
Loops through a block of code as long as the specified condition evaluates to true. As soon as the condition fails, the loop is stopped.
3. JavaScript doโฆwhile loop
The doโฆwhile loop is a variant of the while loop, which evaluates the condition at the END of each loop iteration.
With a doโฆwhile loop the block of code is executed ONCE, and THEN the condition is evaluated.
๐ Loops offer a quick & easy way to do something repeatedly.
The 5 loops in JavaScript essentially do the same thing: โ they repeat an action a certain number of times. However, they have important differences.
Letโs dive in!
1. JavaScript For loop
Repeats a block of code as long as a certain condition is met.
Typically, used to loop through a block of code a specific amount of times.
2. JavaScript while loop
Loops through a block of code as long as the specified condition evaluates to true. As soon as the condition fails, the loop is stopped.
3. JavaScript doโฆwhile loop
The doโฆwhile loop is a variant of the while loop, which evaluates the condition at the END of each loop iteration.
With a doโฆwhile loop the block of code is executed ONCE, and THEN the condition is evaluated.
โค4
Python Interview Questions โ Part 1
1. What is Python?
Python is a high-level, interpreted programming language known for its readability and wide range of libraries.
2. Is Python statically typed or dynamically typed?
Dynamically typed. You don't need to declare data types explicitly.
3. What is the difference between a list and a tuple?
List is mutable, can be modified.
Tuple is immutable, cannot be changed after creation.
4. What is indentation in Python?
Indentation is used to define blocks of code. Python strictly relies on indentation instead of brackets {}.
5. What is the output of this code?
x = [1, 2, 3]
print(x * 2)
Answer: [1, 2, 3, 1, 2, 3]
6. Write a Python program to check if a number is even or odd.
num = int(input("Enter number: "))
if num % 2 == 0:
print("Even")
else:
print("Odd")
7. What is a Python dictionary?
A collection of key-value pairs. Example:
person = {"name": "Alice", "age": 25}
8. Write a function to return the square of a number.
def square(n):
return n * n
Coding Interviews: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
ENJOY LEARNING ๐๐
1. What is Python?
Python is a high-level, interpreted programming language known for its readability and wide range of libraries.
2. Is Python statically typed or dynamically typed?
Dynamically typed. You don't need to declare data types explicitly.
3. What is the difference between a list and a tuple?
List is mutable, can be modified.
Tuple is immutable, cannot be changed after creation.
4. What is indentation in Python?
Indentation is used to define blocks of code. Python strictly relies on indentation instead of brackets {}.
5. What is the output of this code?
x = [1, 2, 3]
print(x * 2)
Answer: [1, 2, 3, 1, 2, 3]
6. Write a Python program to check if a number is even or odd.
num = int(input("Enter number: "))
if num % 2 == 0:
print("Even")
else:
print("Odd")
7. What is a Python dictionary?
A collection of key-value pairs. Example:
person = {"name": "Alice", "age": 25}
8. Write a function to return the square of a number.
def square(n):
return n * n
Coding Interviews: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
ENJOY LEARNING ๐๐
โค2
9 full-stack project ideas to build your portfolio:
๐๏ธ Online Store โ product listings, cart, checkout, and payment integration
๐๏ธ Event Booking App โ users can browse, book, and manage events
๐ Learning Platform โ courses, quizzes, progress tracking
๐ฅ Appointment Scheduler โ book and manage appointments with calendar UI
โ๏ธ Blogging System โ post creation, comments, likes, and user roles
๐ผ Job Board โ post and search jobs, apply with resumes
๐ Real Estate Listings โ search, filter, and view property details
๐ฌ Chat App โ real-time messaging with sockets or Firebase
๐ Admin Dashboard โ charts, user data, and analytics in one place
Like this post if you want me to cover the skills needed to build such projects โค๏ธ
Web Development Resources: https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
Like it if you need a complete tutorial on all these projects! ๐โค๏ธ
๐๏ธ Online Store โ product listings, cart, checkout, and payment integration
๐๏ธ Event Booking App โ users can browse, book, and manage events
๐ Learning Platform โ courses, quizzes, progress tracking
๐ฅ Appointment Scheduler โ book and manage appointments with calendar UI
โ๏ธ Blogging System โ post creation, comments, likes, and user roles
๐ผ Job Board โ post and search jobs, apply with resumes
๐ Real Estate Listings โ search, filter, and view property details
๐ฌ Chat App โ real-time messaging with sockets or Firebase
๐ Admin Dashboard โ charts, user data, and analytics in one place
Like this post if you want me to cover the skills needed to build such projects โค๏ธ
Web Development Resources: https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
Like it if you need a complete tutorial on all these projects! ๐โค๏ธ
โค5
๐๐ผ๐ ๐๐ผ ๐๐ฒ๐ฎ๐ฟ๐ป ๐ฃ๐๐๐ต๐ผ๐ป ๐๐ฎ๐๐ (๐๐๐ฒ๐ป ๐๐ณ ๐ฌ๐ผ๐'๐๐ฒ ๐ก๐ฒ๐๐ฒ๐ฟ ๐๐ผ๐ฑ๐ฒ๐ฑ ๐๐ฒ๐ณ๐ผ๐ฟ๐ฒ!)๐๐
Python is everywhereโweb dev, data science, automation, AIโฆ
But where should YOU start if you're a beginner?
Donโt worry. Hereโs a 6-step roadmap to master Python the smart way (no fluff, just action)๐
๐น ๐ฆ๐๐ฒ๐ฝ ๐ญ: Learn the Basics (Donโt Skip This!)
โ Variables, data types (int, float, string, bool)
โ Loops (for, while), conditionals (if/else)
โ Functions and user input
Start with:
Python.org Docs
YouTube: Programming with Mosh / CodeWithHarry
Platforms: W3Schools / SoloLearn / FreeCodeCamp
Spend a week here.
Practice > Theory.
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฎ: Automate Boring Stuff (Itโs Fun + Useful!)
โ Rename files in bulk
โ Auto-fill forms
โ Web scraping with BeautifulSoup or Selenium
Read: โAutomate the Boring Stuff with Pythonโ
Itโs beginner-friendly and practical!
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฏ: Build Mini Projects (Your Confidence Booster)
โ Calculator app
โ Dice roll simulator
โ Password generator
โ Number guessing game
These small projects teach logic, problem-solving, and syntax in action.
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฐ: Dive Into Libraries (Pythonโs Superpower)
โ Pandas and NumPy โ for data
โ Matplotlib โ for visualizations
โ Requests โ for APIs
โ Tkinter โ for GUI apps
โ Flask โ for web apps
Libraries are what make Python powerful. Learn one at a time with a mini project.
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฑ: Use Git + GitHub (Be a Real Dev)
โ Track your code with Git
โ Upload projects to GitHub
โ Write clear README files
โ Contribute to open source repos
Your GitHub profile = Your online CV. Keep it active!
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฒ: Build a Capstone Project (Level-Up!)
โ A weather dashboard (API + Flask)
โ A personal expense tracker
โ A web scraper that sends email alerts
โ A basic portfolio website in Python + Flask
Pick something that solves a real problemโbonus if it helps you in daily life!
๐ฏ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฃ๐๐๐ต๐ผ๐ป = ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฃ๐ผ๐๐ฒ๐ฟ๐ณ๐๐น ๐ฃ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ ๐ฆ๐ผ๐น๐๐ถ๐ป๐ด
You donโt need to memorize code. Understand the logic.
Google is your best friend. Practice is your real teacher.
Python Resources: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
ENJOY LEARNING ๐๐
Python is everywhereโweb dev, data science, automation, AIโฆ
But where should YOU start if you're a beginner?
Donโt worry. Hereโs a 6-step roadmap to master Python the smart way (no fluff, just action)๐
๐น ๐ฆ๐๐ฒ๐ฝ ๐ญ: Learn the Basics (Donโt Skip This!)
โ Variables, data types (int, float, string, bool)
โ Loops (for, while), conditionals (if/else)
โ Functions and user input
Start with:
Python.org Docs
YouTube: Programming with Mosh / CodeWithHarry
Platforms: W3Schools / SoloLearn / FreeCodeCamp
Spend a week here.
Practice > Theory.
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฎ: Automate Boring Stuff (Itโs Fun + Useful!)
โ Rename files in bulk
โ Auto-fill forms
โ Web scraping with BeautifulSoup or Selenium
Read: โAutomate the Boring Stuff with Pythonโ
Itโs beginner-friendly and practical!
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฏ: Build Mini Projects (Your Confidence Booster)
โ Calculator app
โ Dice roll simulator
โ Password generator
โ Number guessing game
These small projects teach logic, problem-solving, and syntax in action.
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฐ: Dive Into Libraries (Pythonโs Superpower)
โ Pandas and NumPy โ for data
โ Matplotlib โ for visualizations
โ Requests โ for APIs
โ Tkinter โ for GUI apps
โ Flask โ for web apps
Libraries are what make Python powerful. Learn one at a time with a mini project.
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฑ: Use Git + GitHub (Be a Real Dev)
โ Track your code with Git
โ Upload projects to GitHub
โ Write clear README files
โ Contribute to open source repos
Your GitHub profile = Your online CV. Keep it active!
๐น ๐ฆ๐๐ฒ๐ฝ ๐ฒ: Build a Capstone Project (Level-Up!)
โ A weather dashboard (API + Flask)
โ A personal expense tracker
โ A web scraper that sends email alerts
โ A basic portfolio website in Python + Flask
Pick something that solves a real problemโbonus if it helps you in daily life!
๐ฏ ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฃ๐๐๐ต๐ผ๐ป = ๐๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด ๐ฃ๐ผ๐๐ฒ๐ฟ๐ณ๐๐น ๐ฃ๐ฟ๐ผ๐ฏ๐น๐ฒ๐บ ๐ฆ๐ผ๐น๐๐ถ๐ป๐ด
You donโt need to memorize code. Understand the logic.
Google is your best friend. Practice is your real teacher.
Python Resources: https://whatsapp.com/channel/0029Vau5fZECsU9HJFLacm2a
ENJOY LEARNING ๐๐
โค5
๐๐ฅ ๐๐ฒ๐ฐ๐ผ๐บ๐ฒ ๐ฎ๐ป ๐๐ด๐ฒ๐ป๐๐ถ๐ฐ ๐๐ ๐๐๐ถ๐น๐ฑ๐ฒ๐ฟ โ ๐๐ฟ๐ฒ๐ฒ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐ฃ๐ฟ๐ผ๐ด๐ฟ๐ฎ๐บ
Master the most in-demand AI skill in todayโs job market: building autonomous AI systems.
In Ready Tensorโs free, project-first program, youโll create three portfolio-ready projects using ๐๐ฎ๐ป๐ด๐๐ต๐ฎ๐ถ๐ป, ๐๐ฎ๐ป๐ด๐๐ฟ๐ฎ๐ฝ๐ต, and vector databases โ and deploy production-ready agents that employers will notice.
Includes guided lectures, videos, and code.
๐๐ฟ๐ฒ๐ฒ. ๐ฆ๐ฒ๐น๐ณ-๐ฝ๐ฎ๐ฐ๐ฒ๐ฑ. ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ-๐ฐ๐ต๐ฎ๐ป๐ด๐ถ๐ป๐ด.
๐ Apply now: https://go.readytensor.ai/cert-548-agentic-ai-certification
Master the most in-demand AI skill in todayโs job market: building autonomous AI systems.
In Ready Tensorโs free, project-first program, youโll create three portfolio-ready projects using ๐๐ฎ๐ป๐ด๐๐ต๐ฎ๐ถ๐ป, ๐๐ฎ๐ป๐ด๐๐ฟ๐ฎ๐ฝ๐ต, and vector databases โ and deploy production-ready agents that employers will notice.
Includes guided lectures, videos, and code.
๐๐ฟ๐ฒ๐ฒ. ๐ฆ๐ฒ๐น๐ณ-๐ฝ๐ฎ๐ฐ๐ฒ๐ฑ. ๐๐ฎ๐ฟ๐ฒ๐ฒ๐ฟ-๐ฐ๐ต๐ฎ๐ป๐ด๐ถ๐ป๐ด.
๐ Apply now: https://go.readytensor.ai/cert-548-agentic-ai-certification
โค7
Python for Everything:
Python + Django = Web Development
Python + Matplotlib = Data Visualization
Python + Flask = Web Applications
Python + Pygame = Game Development
Python + PyQt = Desktop Applications
Python + TensorFlow = Machine Learning
Python + FastAPI = API Development
Python + Kivy = Mobile App Development
Python + Pandas = Data Analysis
Python + NumPy = Scientific Computing
Python + Django = Web Development
Python + Matplotlib = Data Visualization
Python + Flask = Web Applications
Python + Pygame = Game Development
Python + PyQt = Desktop Applications
Python + TensorFlow = Machine Learning
Python + FastAPI = API Development
Python + Kivy = Mobile App Development
Python + Pandas = Data Analysis
Python + NumPy = Scientific Computing
โค4
FREE RESOURCES TO LEARN MACHINE LEARNING
๐๐
Intro to ML by MIT Free Course
https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about
Machine Learning for Everyone FREE BOOK
https://buildmedia.readthedocs.org/media/pdf/pymbook/latest/pymbook.pdf
ML Crash Course by Google
https://developers.google.com/machine-learning/crash-course
Advanced Machine Learning with Python Github
https://github.com/PacktPublishing/Advanced-Machine-Learning-with-Python
Practical Machine Learning Tools and Techniques Free Book
https://vk.com/doc10903696_437487078?hash=674d2f82c486ac525b&dl=ed6dd98cd9d60a642b
Python Machine Learning for beginners
https://t.iss.one/datasciencefun/1177?single
ENJOY LEARNING ๐๐
๐๐
Intro to ML by MIT Free Course
https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about
Machine Learning for Everyone FREE BOOK
https://buildmedia.readthedocs.org/media/pdf/pymbook/latest/pymbook.pdf
ML Crash Course by Google
https://developers.google.com/machine-learning/crash-course
Advanced Machine Learning with Python Github
https://github.com/PacktPublishing/Advanced-Machine-Learning-with-Python
Practical Machine Learning Tools and Techniques Free Book
https://vk.com/doc10903696_437487078?hash=674d2f82c486ac525b&dl=ed6dd98cd9d60a642b
Python Machine Learning for beginners
https://t.iss.one/datasciencefun/1177?single
ENJOY LEARNING ๐๐
โค2
If-else in Python ๐
โค3