7 Beginner Machine Learning Projects To Complete This Weekend
π 1. Predicting Titanic Survival
Predict who survived using age, gender & class. Learn data cleaning + logistic regression basics. Click here
π 2. Predicting Stock Prices
Forecast stock trends with ARIMA or LSTM. Practice feature engineering & MSE evaluation. click here
π§ 3. Email Spam Classifier
Build an NLP model to detect spam. Use TF-IDF + Naive Bayes/SVM for accuracy. Click here
π’ 4. Handwritten Digit Recognition
Train a CNN on MNIST to identify digits (0β9). Explore image preprocessing & deep learning. Click here
π¬ 5. Movie Recommendation System
Suggest movies using collaborative filtering (SVD) & MovieLens dataset. Measure with RMSE. Click here
π 6. Customer Churn Prediction
Find which customers may leave. Handle imbalanced data & use logistic regression/random forest. Click here
π€ 7. Face Detection
Use OpenCV Haar cascades to detect faces in images/videos. Learn filtering & edge detection. Find here
π 1. Predicting Titanic Survival
Predict who survived using age, gender & class. Learn data cleaning + logistic regression basics. Click here
π 2. Predicting Stock Prices
Forecast stock trends with ARIMA or LSTM. Practice feature engineering & MSE evaluation. click here
π§ 3. Email Spam Classifier
Build an NLP model to detect spam. Use TF-IDF + Naive Bayes/SVM for accuracy. Click here
π’ 4. Handwritten Digit Recognition
Train a CNN on MNIST to identify digits (0β9). Explore image preprocessing & deep learning. Click here
π¬ 5. Movie Recommendation System
Suggest movies using collaborative filtering (SVD) & MovieLens dataset. Measure with RMSE. Click here
π 6. Customer Churn Prediction
Find which customers may leave. Handle imbalanced data & use logistic regression/random forest. Click here
π€ 7. Face Detection
Use OpenCV Haar cascades to detect faces in images/videos. Learn filtering & edge detection. Find here
β€7
Coding and Aptitude Round before interview
Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.
Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.
Resources for Prep:
For algorithms and data structures prep,Leetcode and Hackerrank are good resources.
For aptitude prep, you can refer to IndiaBixand Practice Aptitude.
With respect to data science challenges, practice well on GLabs and Kaggle.
Brilliant is an excellent resource for tricky math and statistics questions.
For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.
Things to Note:
Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!
In case, you are finished with the test before time, recheck your answers and then submit.
Sometimes these rounds donβt go your way, you might have had a brain fade, it was not your day etc. Donβt worry! Shake if off for there is always a next time and this is not the end of the world.
Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking.
Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round.
Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you.
Resources for Prep:
For algorithms and data structures prep,Leetcode and Hackerrank are good resources.
For aptitude prep, you can refer to IndiaBixand Practice Aptitude.
With respect to data science challenges, practice well on GLabs and Kaggle.
Brilliant is an excellent resource for tricky math and statistics questions.
For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself.
Things to Note:
Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do!
In case, you are finished with the test before time, recheck your answers and then submit.
Sometimes these rounds donβt go your way, you might have had a brain fade, it was not your day etc. Donβt worry! Shake if off for there is always a next time and this is not the end of the world.
β€7
Web Development Project Ideas
Beginner-Level Projects
(Focus: HTML, CSS, basic JavaScript)
1. Calculator
2. Quiz App
3. Rock Paper Scissors
4. Note App
5. Stopwatch App
6. QR Code Reader
7. Weather App
8. Landing Page
9. Password Generator
10. Tic Tac Toe Game
11. Drawing App
12. Meme Generator
13. To-Do List App
14. Typing Speed Test
15. Random User API
Intermediate-Level Projects
(Focus: JavaScript, basic backend, APIs, local storage, UI/UX)
1. Link Shortener Website
2. Portfolio Website
3. Food Order Website
4. Movie App
5. Chat App
6. Twitter Clone
7. Survey App
8. E-Book Site
9. File Sharing App
10. Parallax Website
11. Tracker App
12. Memory App
13. Giphy Clone
14. Chess Game
15. Music Player
Advanced-Level Projects
(Focus: Full Stack, authentication, real-time, complex logic, deployment)
1. Ecommerce Website
2. Instagram Clone
3. Whatsapp Clone
4. Netflix Clone
5. Job Search App
6. Pinterest Clone
7. Dating App
8. Social Media Dashboard
9. User Activity Tracker
10. Stock-Trading App
React β€οΈ for more
Join our WhatsApp channel for more: https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
Beginner-Level Projects
(Focus: HTML, CSS, basic JavaScript)
1. Calculator
2. Quiz App
3. Rock Paper Scissors
4. Note App
5. Stopwatch App
6. QR Code Reader
7. Weather App
8. Landing Page
9. Password Generator
10. Tic Tac Toe Game
11. Drawing App
12. Meme Generator
13. To-Do List App
14. Typing Speed Test
15. Random User API
Intermediate-Level Projects
(Focus: JavaScript, basic backend, APIs, local storage, UI/UX)
1. Link Shortener Website
2. Portfolio Website
3. Food Order Website
4. Movie App
5. Chat App
6. Twitter Clone
7. Survey App
8. E-Book Site
9. File Sharing App
10. Parallax Website
11. Tracker App
12. Memory App
13. Giphy Clone
14. Chess Game
15. Music Player
Advanced-Level Projects
(Focus: Full Stack, authentication, real-time, complex logic, deployment)
1. Ecommerce Website
2. Instagram Clone
3. Whatsapp Clone
4. Netflix Clone
5. Job Search App
6. Pinterest Clone
7. Dating App
8. Social Media Dashboard
9. User Activity Tracker
10. Stock-Trading App
React β€οΈ for more
Join our WhatsApp channel for more: https://whatsapp.com/channel/0029VaiSdWu4NVis9yNEE72z
β€10
Here are some project ideas to Practice C++ Programming -
1. Calculator Application: Create a command-line calculator with support for basic arithmetic operations and more advanced features like square roots and trigonometric functions.
2. Student Record System: Build a program to manage student records, including details like names, grades, and attendance.
3. Task Tracker: Create a task tracker application that allows users to add, view, and complete tasks. Use file handling to store task data.
4. Simple Game: Develop a text-based or console-based game like Tic-Tac-Toe, Hangman, or a simple maze solver.
5. Inventory Management System: Build an inventory management system for a small store. Track product details, prices, and stock levels.
6. Chat Application: Create a basic command-line chat application that allows users to send messages to each other using sockets for networking.
1. Calculator Application: Create a command-line calculator with support for basic arithmetic operations and more advanced features like square roots and trigonometric functions.
2. Student Record System: Build a program to manage student records, including details like names, grades, and attendance.
3. Task Tracker: Create a task tracker application that allows users to add, view, and complete tasks. Use file handling to store task data.
4. Simple Game: Develop a text-based or console-based game like Tic-Tac-Toe, Hangman, or a simple maze solver.
5. Inventory Management System: Build an inventory management system for a small store. Track product details, prices, and stock levels.
6. Chat Application: Create a basic command-line chat application that allows users to send messages to each other using sockets for networking.
β€3
Web Development Mastery: From Basics to Advanced π
Start with the fundamentals:
- HTML
- CSS
- JavaScript
- Responsive Design
- Basic DOM Manipulation
- Git and Version Control
You can grasp these essentials in just a week.
Once you're comfortable, dive into intermediate topics:
- AJAX
- APIs
- Frameworks like React, Angular, or Vue
- Front-end Build Tools (Webpack, Babel)
- Back-end basics with Node.js, Express, or Django
Take another week to solidify these skills.
Ready for the advanced level? Explore:
- Authentication and Authorization
- RESTful APIs
- GraphQL
- WebSockets
- Docker and Containerization
- Testing (Unit, Integration, E2E)
These advanced concepts can be mastered in a couple of weeks.
Remember, mastery comes with practice:
- Create a simple web project
- Tackle an intermediate-level project
- Challenge yourself with an advanced project involving complex features
Consistent practice is the key to becoming a web development pro.
Best platforms to learn:
- FreeCodeCamp
- Web Development Free Courses
- Web Development Roadmap
- Projects
- Bootcamp
Share your progress and learnings with others in the community. Enjoy the journey! π©βπ»π¨βπ»
Join @free4unow_backup for more free resources.
Like this post if it helps πβ€οΈ
ENJOY LEARNING ππ
Start with the fundamentals:
- HTML
- CSS
- JavaScript
- Responsive Design
- Basic DOM Manipulation
- Git and Version Control
You can grasp these essentials in just a week.
Once you're comfortable, dive into intermediate topics:
- AJAX
- APIs
- Frameworks like React, Angular, or Vue
- Front-end Build Tools (Webpack, Babel)
- Back-end basics with Node.js, Express, or Django
Take another week to solidify these skills.
Ready for the advanced level? Explore:
- Authentication and Authorization
- RESTful APIs
- GraphQL
- WebSockets
- Docker and Containerization
- Testing (Unit, Integration, E2E)
These advanced concepts can be mastered in a couple of weeks.
Remember, mastery comes with practice:
- Create a simple web project
- Tackle an intermediate-level project
- Challenge yourself with an advanced project involving complex features
Consistent practice is the key to becoming a web development pro.
Best platforms to learn:
- FreeCodeCamp
- Web Development Free Courses
- Web Development Roadmap
- Projects
- Bootcamp
Share your progress and learnings with others in the community. Enjoy the journey! π©βπ»π¨βπ»
Join @free4unow_backup for more free resources.
Like this post if it helps πβ€οΈ
ENJOY LEARNING ππ
β€3
Master Javascript :
The JavaScript Tree π
|
|ββ Variables
| βββ var
| βββ let
| βββ const
|
|ββ Data Types
| βββ String
| βββ Number
| βββ Boolean
| βββ Object
| βββ Array
| βββ Null
| βββ Undefined
|
|ββ Operators
| βββ Arithmetic
| βββ Assignment
| βββ Comparison
| βββ Logical
| βββ Unary
| βββ Ternary (Conditional)
||ββ Control Flow
| βββ if statement
| βββ else statement
| βββ else if statement
| βββ switch statement
| βββ for loop
| βββ while loop
| βββ do-while loop
|
|ββ Functions
| βββ Function declaration
| βββ Function expression
| βββ Arrow function
| βββ IIFE (Immediately Invoked Function Expression)
|
|ββ Scope
| βββ Global scope
| βββ Local scope
| βββ Block scope
| βββ Lexical scope
||ββ Arrays
| βββ Array methods
| | βββ push()
| | βββ pop()
| | βββ shift()
| | βββ unshift()
| | βββ splice()
| | βββ slice()
| | βββ concat()
| βββ Array iteration
| βββ forEach()
| βββ map()
| βββ filter()
| βββ reduce()|
|ββ Objects
| βββ Object properties
| | βββ Dot notation
| | βββ Bracket notation
| βββ Object methods
| | βββ Object.keys()
| | βββ Object.values()
| | βββ Object.entries()
| βββ Object destructuring
||ββ Promises
| βββ Promise states
| | βββ Pending
| | βββ Fulfilled
| | βββ Rejected
| βββ Promise methods
| | βββ then()
| | βββ catch()
| | βββ finally()
| βββ Promise.all()
|
|ββ Asynchronous JavaScript
| βββ Callbacks
| βββ Promises
| βββ Async/Await
|
|ββ Error Handling
| βββ try...catch statement
| βββ throw statement
|
|ββ JSON (JavaScript Object Notation)
||ββ Modules
| βββ import
| βββ export
|
|ββ DOM Manipulation
| βββ Selecting elements
| βββ Modifying elements
| βββ Creating elements
|
|ββ Events
| βββ Event listeners
| βββ Event propagation
| βββ Event delegation
|
|ββ AJAX (Asynchronous JavaScript and XML)
|
|ββ Fetch API
||ββ ES6+ Features
| βββ Template literals
| βββ Destructuring assignment
| βββ Spread/rest operator
| βββ Arrow functions
| βββ Classes
| βββ let and const
| βββ Default parameters
| βββ Modules
| βββ Promises
|
|ββ Web APIs
| βββ Local Storage
| βββ Session Storage
| βββ Web Storage API
|
|ββ Libraries and Frameworks
| βββ React
| βββ Angular
| βββ Vue.js
||ββ Debugging
| βββ Console.log()
| βββ Breakpoints
| βββ DevTools
|
|ββ Others
| βββ Closures
| βββ Callbacks
| βββ Prototypes
| βββ this keyword
| βββ Hoisting
| βββ Strict mode
|
| END __
The JavaScript Tree π
|
|ββ Variables
| βββ var
| βββ let
| βββ const
|
|ββ Data Types
| βββ String
| βββ Number
| βββ Boolean
| βββ Object
| βββ Array
| βββ Null
| βββ Undefined
|
|ββ Operators
| βββ Arithmetic
| βββ Assignment
| βββ Comparison
| βββ Logical
| βββ Unary
| βββ Ternary (Conditional)
||ββ Control Flow
| βββ if statement
| βββ else statement
| βββ else if statement
| βββ switch statement
| βββ for loop
| βββ while loop
| βββ do-while loop
|
|ββ Functions
| βββ Function declaration
| βββ Function expression
| βββ Arrow function
| βββ IIFE (Immediately Invoked Function Expression)
|
|ββ Scope
| βββ Global scope
| βββ Local scope
| βββ Block scope
| βββ Lexical scope
||ββ Arrays
| βββ Array methods
| | βββ push()
| | βββ pop()
| | βββ shift()
| | βββ unshift()
| | βββ splice()
| | βββ slice()
| | βββ concat()
| βββ Array iteration
| βββ forEach()
| βββ map()
| βββ filter()
| βββ reduce()|
|ββ Objects
| βββ Object properties
| | βββ Dot notation
| | βββ Bracket notation
| βββ Object methods
| | βββ Object.keys()
| | βββ Object.values()
| | βββ Object.entries()
| βββ Object destructuring
||ββ Promises
| βββ Promise states
| | βββ Pending
| | βββ Fulfilled
| | βββ Rejected
| βββ Promise methods
| | βββ then()
| | βββ catch()
| | βββ finally()
| βββ Promise.all()
|
|ββ Asynchronous JavaScript
| βββ Callbacks
| βββ Promises
| βββ Async/Await
|
|ββ Error Handling
| βββ try...catch statement
| βββ throw statement
|
|ββ JSON (JavaScript Object Notation)
||ββ Modules
| βββ import
| βββ export
|
|ββ DOM Manipulation
| βββ Selecting elements
| βββ Modifying elements
| βββ Creating elements
|
|ββ Events
| βββ Event listeners
| βββ Event propagation
| βββ Event delegation
|
|ββ AJAX (Asynchronous JavaScript and XML)
|
|ββ Fetch API
||ββ ES6+ Features
| βββ Template literals
| βββ Destructuring assignment
| βββ Spread/rest operator
| βββ Arrow functions
| βββ Classes
| βββ let and const
| βββ Default parameters
| βββ Modules
| βββ Promises
|
|ββ Web APIs
| βββ Local Storage
| βββ Session Storage
| βββ Web Storage API
|
|ββ Libraries and Frameworks
| βββ React
| βββ Angular
| βββ Vue.js
||ββ Debugging
| βββ Console.log()
| βββ Breakpoints
| βββ DevTools
|
|ββ Others
| βββ Closures
| βββ Callbacks
| βββ Prototypes
| βββ this keyword
| βββ Hoisting
| βββ Strict mode
|
| END __
β€9π2
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
- Dijkstraβs algorithm for shortest path
- Kruskalβs and Primβs 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.me/free4unow_backup
ENJOY LEARNING ππ
### 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
- Dijkstraβs algorithm for shortest path
- Kruskalβs and Primβs 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.me/free4unow_backup
ENJOY LEARNING ππ
β€14π2