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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
โค3
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โค2
SQL table interview questions:
1. What is a DUAL table and why do we need it?
- it is a special table which gets created automatically when we install Oracle database. It can be used to select pseudo columns, perform calculations and also as sequence generator etc.
2. How many columns and rows are present in DUAL table?
- one column & one row by default.
3. Can we insert more rows in to DUAL table?
- Yes.
4. What's the easiest way to backup a table / how can we create a table based on existing table?
- CREATE TABLE SALES_COPY AS SELECT * FROM SALES.
5. Can we drop all the columns from a table?
- No.
6. What is the difference between count(1) and count(*)?
- Both are same. Both consume same amount of resources, Both perform same operation
1. What is a DUAL table and why do we need it?
- it is a special table which gets created automatically when we install Oracle database. It can be used to select pseudo columns, perform calculations and also as sequence generator etc.
2. How many columns and rows are present in DUAL table?
- one column & one row by default.
3. Can we insert more rows in to DUAL table?
- Yes.
4. What's the easiest way to backup a table / how can we create a table based on existing table?
- CREATE TABLE SALES_COPY AS SELECT * FROM SALES.
5. Can we drop all the columns from a table?
- No.
6. What is the difference between count(1) and count(*)?
- Both are same. Both consume same amount of resources, Both perform same operation
โค3
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5 Algorithms you must know as a data scientist ๐ฉโ๐ป ๐งโ๐ป
1. Dimensionality Reduction
- PCA, t-SNE, LDA
2. Regression models
- Linesr regression, Kernel-based regression models, Lasso Regression, Ridge regression, Elastic-net regression
3. Classification models
- Binary classification- Logistic regression, SVM
- Multiclass classification- One versus one, one versus many
- Multilabel classification
4. Clustering models
- K Means clustering, Hierarchical clustering, DBSCAN, BIRCH models
5. Decision tree based models
- CART model, ensemble models(XGBoost, LightGBM, CatBoost)
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
Join our WhatsApp channel: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
Like if you need similar content ๐๐
1. Dimensionality Reduction
- PCA, t-SNE, LDA
2. Regression models
- Linesr regression, Kernel-based regression models, Lasso Regression, Ridge regression, Elastic-net regression
3. Classification models
- Binary classification- Logistic regression, SVM
- Multiclass classification- One versus one, one versus many
- Multilabel classification
4. Clustering models
- K Means clustering, Hierarchical clustering, DBSCAN, BIRCH models
5. Decision tree based models
- CART model, ensemble models(XGBoost, LightGBM, CatBoost)
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
Join our WhatsApp channel: https://whatsapp.com/channel/0029Va8v3eo1NCrQfGMseL2D
Like if you need similar content ๐๐
โค3
1: How would you preprocess and tokenize text data from tweets for sentiment analysis? Discuss potential challenges and solutions.
- Answer: Preprocessing and tokenizing text data for sentiment analysis involves tasks like lowercasing, removing stop words, and stemming or lemmatization. Handling challenges like handling emojis, slang, and noisy text is crucial. Tools like NLTK or spaCy can assist in these tasks.
2: Explain the collaborative filtering approach in building recommendation systems. How might Twitter use this to enhance user experience?
- Answer: Collaborative filtering recommends items based on user preferences and similarities. Techniques include user-based or item-based collaborative filtering and matrix factorization. Twitter could leverage user interactions to recommend tweets, users, or topics.
3: Write a Python or Scala function to count the frequency of hashtags in a given collection of tweets.
- Answer (Python):
4: How does graph analysis contribute to understanding user interactions and content propagation on Twitter? Provide a specific use case.
- Answer: Graph analysis on Twitter involves examining user interactions. For instance, identifying influential users or detecting communities based on retweet or mention networks. Algorithms like PageRank or Louvain Modularity can aid in these analyses.
- Answer: Preprocessing and tokenizing text data for sentiment analysis involves tasks like lowercasing, removing stop words, and stemming or lemmatization. Handling challenges like handling emojis, slang, and noisy text is crucial. Tools like NLTK or spaCy can assist in these tasks.
2: Explain the collaborative filtering approach in building recommendation systems. How might Twitter use this to enhance user experience?
- Answer: Collaborative filtering recommends items based on user preferences and similarities. Techniques include user-based or item-based collaborative filtering and matrix factorization. Twitter could leverage user interactions to recommend tweets, users, or topics.
3: Write a Python or Scala function to count the frequency of hashtags in a given collection of tweets.
- Answer (Python):
def count_hashtags(tweet_collection):
hashtags_count = {}
for tweet in tweet_collection:
hashtags = [word for word in tweet.split() if word.startswith('#')]
for hashtag in hashtags:
hashtags_count[hashtag] = hashtags_count.get(hashtag, 0) + 1
return hashtags_count
4: How does graph analysis contribute to understanding user interactions and content propagation on Twitter? Provide a specific use case.
- Answer: Graph analysis on Twitter involves examining user interactions. For instance, identifying influential users or detecting communities based on retweet or mention networks. Algorithms like PageRank or Louvain Modularity can aid in these analyses.
โค1
๐40 Windows Command Prompt commands you need to know๐
1. ipconfig
2. ipconfig /all
3. findstr
4. ipconfig /release
5. ipconfig /renew
6. ipconfig /displaydns
7. clip
8. ipconfig /flushdns
9. nslookup
10. cls
11. getmac /v
12. powercfg /energy
13. powercfg /batteryreport
14. assoc
15. chkdsk /f
16. chkdsk /r
17. Follow Coding Army
17. sfc /scannow
18. DISM /Online /Cleanup /CheckHealth
19. DISM /Online /Cleanup /ScanHealth
20. DISM /Online /Cleanup /RestoreHealth
21. tasklist
22. taskkill
23. netsh wlan show wlanreport
24. netsh interface show interface
25. netsh interface ip show address | findstr "IP Address"
26. netsh interface ip show dnsservers
27. netsh advfirewall set allprofiles state off
28. netsh advfirewall set allprofiles state on
29. ping
30. ping -t
31. tracert
32. tracert -d
33. netstat
34. netstat -af
35. netstat -o
36. netstat -e -t 5
37. route print
38. route add
39. route delete
40. shutdown /r /fw /f /t 0
Command 40:
*Details:*
The command
https://whatsapp.com/channel/0029VancSnGG8l5KQYOOyL1T
1. ipconfig
2. ipconfig /all
3. findstr
4. ipconfig /release
5. ipconfig /renew
6. ipconfig /displaydns
7. clip
8. ipconfig /flushdns
9. nslookup
10. cls
11. getmac /v
12. powercfg /energy
13. powercfg /batteryreport
14. assoc
15. chkdsk /f
16. chkdsk /r
17. Follow Coding Army
17. sfc /scannow
18. DISM /Online /Cleanup /CheckHealth
19. DISM /Online /Cleanup /ScanHealth
20. DISM /Online /Cleanup /RestoreHealth
21. tasklist
22. taskkill
23. netsh wlan show wlanreport
24. netsh interface show interface
25. netsh interface ip show address | findstr "IP Address"
26. netsh interface ip show dnsservers
27. netsh advfirewall set allprofiles state off
28. netsh advfirewall set allprofiles state on
29. ping
30. ping -t
31. tracert
32. tracert -d
33. netstat
34. netstat -af
35. netstat -o
36. netstat -e -t 5
37. route print
38. route add
39. route delete
40. shutdown /r /fw /f /t 0
Command 40:
*Details:*
The command
shutdown /r/fw/f/t 0 restarts the computer immediately and forces it to boot directly into the BIOS or UEFI firmware settings, bypassing the normal Windows startup process. It's a convenient way to access your firmware settings without having to repeatedly press a specific key during startup (like Del, F2, F10, F12, Esc, etc., which vary depending on the motherboard manufacturer.https://whatsapp.com/channel/0029VancSnGG8l5KQYOOyL1T
โค1
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โค1
๐ Web development project ideas for beginners
Personal Portfolio Website: Create a website showcasing your skills, projects, and resume. This will help you practice HTML, CSS, and potentially some JavaScript for interactivity.
To-Do List App: Build a simple to-do list application using HTML, CSS, and JavaScript. You can gradually enhance it by adding features like task priority, due dates, and local storage.
Blog Platform: Create a basic blog platform where users can create, edit, and delete posts. This will give you experience with user authentication, databases, and CRUD operations.
E-commerce Website: Design a mock e-commerce site to learn about product listings, shopping carts, and checkout processes. This project will introduce you to handling user input and creating dynamic content.
Weather App: Develop a weather app that fetches data from a weather API and displays current conditions and forecasts. This project will involve API integration and working with JSON data.
Recipe Sharing Site: Build a platform where users can share and browse recipes. You can implement search functionality and user authentication to enhance the project.
Social Media Dashboard: Create a simplified social media dashboard that displays metrics like followers, likes, and comments. This project will help you practice data visualization and working with APIs.
Online Quiz App: Develop an online quiz application that lets users take quizzes on various topics. You can include features like multiple-choice questions, timers, and score tracking.
Personal Blog: Start your own blog by developing a content management system (CMS) where you can create, edit, and publish articles. This will give you hands-on experience with database management.
Event Countdown Timer: Build a countdown timer for upcoming events. You can make it interactive by allowing users to set their own event names and dates.
Remember, the key is to start small and gradually add complexity to your projects as you become more comfortable with different technologies concepts. These projects will not only showcase your skills to potential employers but also help you learn and grow as a web developer.
Free Resources to learn web development https://t.iss.one/free4unow_backup/554
ENJOY LEARNING ๐๐
Personal Portfolio Website: Create a website showcasing your skills, projects, and resume. This will help you practice HTML, CSS, and potentially some JavaScript for interactivity.
To-Do List App: Build a simple to-do list application using HTML, CSS, and JavaScript. You can gradually enhance it by adding features like task priority, due dates, and local storage.
Blog Platform: Create a basic blog platform where users can create, edit, and delete posts. This will give you experience with user authentication, databases, and CRUD operations.
E-commerce Website: Design a mock e-commerce site to learn about product listings, shopping carts, and checkout processes. This project will introduce you to handling user input and creating dynamic content.
Weather App: Develop a weather app that fetches data from a weather API and displays current conditions and forecasts. This project will involve API integration and working with JSON data.
Recipe Sharing Site: Build a platform where users can share and browse recipes. You can implement search functionality and user authentication to enhance the project.
Social Media Dashboard: Create a simplified social media dashboard that displays metrics like followers, likes, and comments. This project will help you practice data visualization and working with APIs.
Online Quiz App: Develop an online quiz application that lets users take quizzes on various topics. You can include features like multiple-choice questions, timers, and score tracking.
Personal Blog: Start your own blog by developing a content management system (CMS) where you can create, edit, and publish articles. This will give you hands-on experience with database management.
Event Countdown Timer: Build a countdown timer for upcoming events. You can make it interactive by allowing users to set their own event names and dates.
Remember, the key is to start small and gradually add complexity to your projects as you become more comfortable with different technologies concepts. These projects will not only showcase your skills to potential employers but also help you learn and grow as a web developer.
Free Resources to learn web development https://t.iss.one/free4unow_backup/554
ENJOY LEARNING ๐๐
โค2
๐ง๐ผ๐ฝ ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐ ๐๐ถ๐ธ๐ฒ ๐๐ป๐ณ๐ผ๐๐๐ , ๐๐ฒ๐ป๐ฝ๐ฎ๐ฐ๐ ,๐&๐ง ,๐ฃ๐ต๐ถ๐น๐ถ๐ฝ๐ & ๐ข๐ฟ๐ฎ๐ฐ๐น๐ฒ ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐
Roles Hiring:- Data Analyst, Software Engineer & Associate
Job Location:- Across India/WFH
Qualification:- Graduate/Post Graduate
๐๐ฝ๐ฝ๐น๐ ๐ก๐ผ๐๐:-
https://bit.ly/44qMX2k
Select your experience & Complete The Registration Process
Select the company name & apply for the role that matches you
Roles Hiring:- Data Analyst, Software Engineer & Associate
Job Location:- Across India/WFH
Qualification:- Graduate/Post Graduate
๐๐ฝ๐ฝ๐น๐ ๐ก๐ผ๐๐:-
https://bit.ly/44qMX2k
Select your experience & Complete The Registration Process
Select the company name & apply for the role that matches you
โค1
Forwarded from Coding Projects
๐๐ฅ๐๐ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ ๐ง๐ผ ๐๐ฟ๐ฎ๐ฐ๐ธ ๐ฌ๐ผ๐๐ฟ ๐ก๐ฒ๐
๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐
Preparing for coding interviews? These free resources will help you crack your dream job! ๐
Ace Your Next Interview with These FREE Resources!๐จโ๐ป
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3FjrIVX
All The Best ๐
Preparing for coding interviews? These free resources will help you crack your dream job! ๐
Ace Your Next Interview with These FREE Resources!๐จโ๐ป
๐๐ข๐ง๐ค๐:-
https://pdlink.in/3FjrIVX
All The Best ๐
โค1
General tips for coding interviews
Always validate input first. Check for inputs that are invalid, empty, negative, or different. Never assume you are given the valid parameters. Alternatively, clarify with the interviewer whether you can assume valid input (usually yes), which can save you time from writing code that does input validation.
Are there any time and space complexities requirements or constraints?
Check for off-by-one errors.
In languages where there are no automatic type coercion, check that concatenation of values are of the same type: int,str, and list.
After you finish your code, use a few example inputs to test your solution.
Is the algorithm supposed to run multiple times, perhaps on a web server? If yes, the input can likely be pre-processed to improve the efficiency in each API call.
Use a mix of functional and imperative programming paradigms:
๐น Write pure functions as often as possible.
๐น Use pure functions because they are easier to reason with and can help reduce bugs in your implementation.
๐น Avoid mutating the parameters passed into your function, especially if they are passed by reference, unless you are sure of what you are doing.
๐น Achieve a balance between accuracy and efficiency. Use the right amount of functional and imperative code where appropriate. Functional programming is usually expensive in terms of space complexity because of non-mutation and the repeated allocation of new objects. On the other hand, imperative code is faster because you operate on existing objects.
๐น Avoid relying on mutating global variables. Global variables introduce state.
๐น Make sure that you do not accidentally mutate global variables, especially if you have to rely on them.
Always validate input first. Check for inputs that are invalid, empty, negative, or different. Never assume you are given the valid parameters. Alternatively, clarify with the interviewer whether you can assume valid input (usually yes), which can save you time from writing code that does input validation.
Are there any time and space complexities requirements or constraints?
Check for off-by-one errors.
In languages where there are no automatic type coercion, check that concatenation of values are of the same type: int,str, and list.
After you finish your code, use a few example inputs to test your solution.
Is the algorithm supposed to run multiple times, perhaps on a web server? If yes, the input can likely be pre-processed to improve the efficiency in each API call.
Use a mix of functional and imperative programming paradigms:
๐น Write pure functions as often as possible.
๐น Use pure functions because they are easier to reason with and can help reduce bugs in your implementation.
๐น Avoid mutating the parameters passed into your function, especially if they are passed by reference, unless you are sure of what you are doing.
๐น Achieve a balance between accuracy and efficiency. Use the right amount of functional and imperative code where appropriate. Functional programming is usually expensive in terms of space complexity because of non-mutation and the repeated allocation of new objects. On the other hand, imperative code is faster because you operate on existing objects.
๐น Avoid relying on mutating global variables. Global variables introduce state.
๐น Make sure that you do not accidentally mutate global variables, especially if you have to rely on them.
โค1
๐๐๐ฒ ๐๐๐ญ๐๐ซ ๐๐ฅ๐๐๐๐ฆ๐๐ง๐ญ - ๐๐๐ญ ๐๐ฅ๐๐๐๐ ๐๐ง ๐๐จ๐ฉ ๐๐๐'๐ฌ ๐
Learn Coding From Scratch - Lectures Taught By IIT Alumni
60+ Hiring Drives Every Month
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:-
๐ Trusted by 7500+ Students
๐ค 500+ Hiring Partners
๐ผ Avg. Rs. 7.4 LPA
๐ 41 LPA Highest Package
Eligibility: BTech / BCA / BSc / MCA / MSc
๐๐๐ ๐ข๐ฌ๐ญ๐๐ซ ๐๐จ๐ฐ๐ :-
https://pdlink.in/4hO7rWY
Hurry, limited seats available!๐โโ๏ธ
Learn Coding From Scratch - Lectures Taught By IIT Alumni
60+ Hiring Drives Every Month
๐๐ข๐ ๐ก๐ฅ๐ข๐ ๐ก๐ญ๐ฌ:-
๐ Trusted by 7500+ Students
๐ค 500+ Hiring Partners
๐ผ Avg. Rs. 7.4 LPA
๐ 41 LPA Highest Package
Eligibility: BTech / BCA / BSc / MCA / MSc
๐๐๐ ๐ข๐ฌ๐ญ๐๐ซ ๐๐จ๐ฐ๐ :-
https://pdlink.in/4hO7rWY
Hurry, limited seats available!๐โโ๏ธ
โค1
Here are some interview preparation tips ๐๐
Technical Interview
1. Review Core Concepts:
- Data Structures: Be comfortable with LinkedLists, Trees, Graphs, and their representations.
- Algorithms: Brush up on searching and sorting algorithms, time complexities, and common algorithms (like Dijkstraโs or A*).
- Programming Languages: Ensure you understand the language you are most comfortable with (e.g., C++, Java, Python) and know its standard library functions.
2. Practice Coding Problems:
- Utilize platforms like LeetCode, HackerRank, or CodeSignal to practice medium-level coding questions. Focus on common patterns and problem-solving strategies.
3. Mock Interviews: Conduct mock technical interviews with peers or mentors to build confidence and receive feedback.
Personal Interview
1. Prepare Your Story:
- Outline your educational journey, achievements, and any relevant projects. Emphasize experiences that demonstrate leadership, teamwork, and problem-solving skills.
- Be ready to discuss your challenges and how you overcame them.
2. Articulate Your Goals:
- Be clear about why you want to join the program and how it aligns with your career aspirations. Reflect on what you hope to gain from the experience.
- Focus on Fundamentals:
Be thorough with basic subjects like Operating Systems, Networking, OOP, and Databases. Clear concepts are key for technical interviews.
2. Common Interview Questions:
DSA:
- Implement various data structures like Linked Lists, Trees, Graphs, Stacks, and Queues.
- Understand searching and sorting algorithms: Binary Search, Merge Sort, Quick Sort, etc.
- Solve problems involving HashMaps, Sets, and other collections.
Sample DSA Questions
- Reverse a linked list.
- Find the first non-repeating character in a string.
- Detect a cycle in a graph.
- Implement a queue using two stacks.
- Find the lowest common ancestor in a binary tree.
3. Key Topics to Focus On
DSA:
- Arrays, Strings, Linked Lists, Trees, Graphs
- Recursion, Backtracking, Dynamic Programming
- Sorting and Searching Algorithms
- Time and Space Complexity
Core Subjects
- Operating Systems: Concepts like processes, threads, deadlocks, concurrency, and memory management.
- Database Management Systems (DBMS): Understanding SQL, Normalization, and database design.
- Object-Oriented Programming (OOP): Know about inheritance, polymorphism, encapsulation, and design patterns.
5. Tips
- Optimize Your Code: Write clean, optimized code. Discuss time and space complexities during interviews.
- Review Your Projects: Be ready to explain your past projects, the challenges you faced, and the technologies you used.....
Best Programming Resources: https://topmate.io/coding/898340
All the best ๐๐
Technical Interview
1. Review Core Concepts:
- Data Structures: Be comfortable with LinkedLists, Trees, Graphs, and their representations.
- Algorithms: Brush up on searching and sorting algorithms, time complexities, and common algorithms (like Dijkstraโs or A*).
- Programming Languages: Ensure you understand the language you are most comfortable with (e.g., C++, Java, Python) and know its standard library functions.
2. Practice Coding Problems:
- Utilize platforms like LeetCode, HackerRank, or CodeSignal to practice medium-level coding questions. Focus on common patterns and problem-solving strategies.
3. Mock Interviews: Conduct mock technical interviews with peers or mentors to build confidence and receive feedback.
Personal Interview
1. Prepare Your Story:
- Outline your educational journey, achievements, and any relevant projects. Emphasize experiences that demonstrate leadership, teamwork, and problem-solving skills.
- Be ready to discuss your challenges and how you overcame them.
2. Articulate Your Goals:
- Be clear about why you want to join the program and how it aligns with your career aspirations. Reflect on what you hope to gain from the experience.
- Focus on Fundamentals:
Be thorough with basic subjects like Operating Systems, Networking, OOP, and Databases. Clear concepts are key for technical interviews.
2. Common Interview Questions:
DSA:
- Implement various data structures like Linked Lists, Trees, Graphs, Stacks, and Queues.
- Understand searching and sorting algorithms: Binary Search, Merge Sort, Quick Sort, etc.
- Solve problems involving HashMaps, Sets, and other collections.
Sample DSA Questions
- Reverse a linked list.
- Find the first non-repeating character in a string.
- Detect a cycle in a graph.
- Implement a queue using two stacks.
- Find the lowest common ancestor in a binary tree.
3. Key Topics to Focus On
DSA:
- Arrays, Strings, Linked Lists, Trees, Graphs
- Recursion, Backtracking, Dynamic Programming
- Sorting and Searching Algorithms
- Time and Space Complexity
Core Subjects
- Operating Systems: Concepts like processes, threads, deadlocks, concurrency, and memory management.
- Database Management Systems (DBMS): Understanding SQL, Normalization, and database design.
- Object-Oriented Programming (OOP): Know about inheritance, polymorphism, encapsulation, and design patterns.
5. Tips
- Optimize Your Code: Write clean, optimized code. Discuss time and space complexities during interviews.
- Review Your Projects: Be ready to explain your past projects, the challenges you faced, and the technologies you used.....
Best Programming Resources: https://topmate.io/coding/898340
All the best ๐๐
โค3
๐๐ผ๐ผ๐๐ ๐ฌ๐ผ๐๐ฟ ๐ฅ๐ฒ๐๐๐บ๐ฒ ๐๐ถ๐๐ต ๐ง๐ต๐ฒ๐๐ฒ ๐๐ฎ๐ป๐ฑ๐-๐ข๐ป ๐ฃ๐๐๐ต๐ผ๐ป ๐ฃ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐๐ (๐๐ฟ๐ฒ๐ฒ ๐ฌ๐ผ๐๐ง๐๐ฏ๐ฒ ๐ง๐๐๐ผ๐ฟ๐ถ๐ฎ๐น๐)๐
Want to stand out with real Python experience?๐จโ๐ป๐ก
These full-length YouTube tutorials walk you through resume-worthy projects โ perfect for beginners aiming to move beyond theory.๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/456I3Yl
Here are 5 projects you can start today๐โ ๏ธ
Want to stand out with real Python experience?๐จโ๐ป๐ก
These full-length YouTube tutorials walk you through resume-worthy projects โ perfect for beginners aiming to move beyond theory.๐๐
๐๐ข๐ง๐ค๐:-
https://pdlink.in/456I3Yl
Here are 5 projects you can start today๐โ ๏ธ
โค2