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Useful Cheatsheets for Programmers 👇👇 Data Science Cheatsheet https://github.com/aaronwangy/Data-Science-Cheatsheet SQL Cheatsheet https://learnsql.com/blog/sql-basics-cheat-sheet/ https://t.me/programming_guide/299 https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf https://t.me/learndataanalysis/442?single Java Programming Cheatsheet https://introcs.cs.princeton.edu/java/11cheatsheet/ PHP and Ruby Cheatsheets https://t.me/programming_guide/300 https://t.me/programming_guide/301 Pandas in 5 minutes https://bit.ly/3EZgNgF Python Cheat sheet https://t.me/pythondevelopersindia/314 UML Cheat sheet https://www.guru99.com/uml-cheatsheet-reference-guide.html. GIT and Machine Learning Cheatsheet https://t.me/datasciencefun/714?single Javascript Cheat sheet https://t.me/programming_guide/623 HTML Cheatsheet https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf ENJOY LEARNING 👍👍

𝐅𝐑𝐄𝐄 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐈𝐧𝐭𝐞𝐫𝐧𝐬𝐡𝐢𝐩𝐬 😍 Struggling with no experience in data analytics? Don't worry! 💡 Check out these free virtual internships from top companies like BCG, TATA, and Accenture that you can do remotely.  𝐋𝐢𝐧𝐤👇:-  https://pdlink.in/409RHXN Enroll For FREE & Get Certified 🎓.

The world stands on a precipice, and the trends are not good. It was the United States whose economic wherewithal rescued Western civilisation in the Second World War and the Cold War. But whereas in 1945 the US accounted for half of all global manufacturing, it now accounts for roughly 16 per cent. America’s gross national debt stands at $36trn, and that debt is growing by $1trn annually. #US #Trump #Europe 👂 More on Trump's Ear

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30-days learning plan to master Data Structures and Algorithms (DSA) and prepare for coding interviews. ### Week 1: Foundations and Basic Data Structures Day 1-3: Arrays and Strings - Topics to Cover: - Array basics, operations (insertion, deletion, searching) - String manipulation - Two-pointer technique, sliding window technique - Practice Problems: - Two Sum - Maximum Subarray - Reverse a String - Longest Substring Without Repeating Characters Day 4-5: Linked Lists - Topics to Cover: - Singly linked list, doubly linked list, circular linked list - Common operations (insertion, deletion, reversal) - Practice Problems: - Reverse a Linked List - Merge Two Sorted Lists - Remove Nth Node From End of List Day 6-7: Stacks and Queues - Topics to Cover: - Stack operations (push, pop, top) - Queue operations (enqueue, dequeue) - Applications (expression evaluation, backtracking, breadth-first search) - Practice Problems: - Valid Parentheses - Implement Stack using Queues - Implement Queue using Stacks ### Week 2: Advanced Data Structures Day 8-10: Trees - Topics to Cover: - Binary Trees, Binary Search Trees (BST) - Tree traversal (preorder, inorder, postorder, level order) - Practice Problems: - Invert Binary Tree - Validate Binary Search Tree - Serialize and Deserialize Binary Tree Day 11-13: Heaps and Priority Queues - Topics to Cover: - Binary heap (min-heap, max-heap) - Heap operations (insert, delete, extract-min/max) - Applications (heap sort, priority queues) - Practice Problems: - Kth Largest Element in an Array - Top K Frequent Elements - Find Median from Data Stream Day 14: Hash Tables - Topics to Cover: - Hashing concept, hash functions, collision resolution (chaining, open addressing) - Applications (caching, counting frequencies) - Practice Problems: - Two Sum (using hash map) - Group Anagrams - Subarray Sum Equals K ### Week 3: Algorithms Day 15-17: Sorting and Searching Algorithms - Topics to Cover: - Sorting algorithms (quick sort, merge sort, bubble sort, insertion sort) - Searching algorithms (binary search, linear search) - Practice Problems: - Merge Intervals - Search in Rotated Sorted Array - Sort Colors - Find Peak Element Day 18-20: Recursion and Backtracking - Topics to Cover: - Basic recursion, tail recursion - Backtracking (N-Queens, Sudoku solver) - Practice Problems: - Permutations - Combination Sum - Subsets - Word Search Day 21: Divide and Conquer - Topics to Cover: - Basic concept, merge sort, quick sort, binary search - Practice Problems: - Median of Two Sorted Arrays - Pow(x, n) - Kth Largest Element in an Array (using divide and conquer) - Maximum Subarray (using divide and conquer) ### Week 4: Graphs and Dynamic Programming Day 22-24: Graphs - Topics to Cover: - Graph representations (adjacency list, adjacency matrix) - Traversal algorithms (DFS, BFS) - Shortest path algorithms (Dijkstra's, Bellman-Ford) - Practice Problems: - Number of Islands Day 25-27: Dynamic Programming - Topics to Cover: - Basic concept, memoization, tabulation - Common problems (knapsack, longest common subsequence) - Practice Problems: - Longest Increasing Subsequence - Maximum Product Subarray Day 28: Advanced Topics and Miscellaneous - Topics to Cover: - Bit manipulation - Greedy algorithms - Miscellaneous problems (trie, segment tree, disjoint set) - Practice Problems: - Single Number - Decode Ways - Minimum Spanning Tree ### Week 5: Review and Mock Interviews Day 29: Review and Weakness Analysis - Activities:   - Review topics you found difficult   - Revisit problems you struggled with Day 30: Mock Interviews and Practice - Activities:   - Conduct mock interviews with a friend or use online platforms   - Focus on communication and explaining your thought process Top DSA resources to crack coding interview 👉 GeekforGeeks 👉 Leetcode 👉 DSA Steps 👉 FreeCodeCamp 👉 Coding Interviews 👉 Best DSA Resources Join for more: https://t.me/free4unow_backup ENJOY LEARNING 👍👍

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Python Patters

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𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐓𝐨 𝐁𝐞𝐜𝐨𝐦𝐞 𝐒𝐤𝐢𝐥𝐥𝐞𝐝 𝗜𝗻 𝟐𝟎𝟐𝟓😍 Free lifetime access – Learn anytime, anywhere Get Completion Certificate 𝐋𝐢𝐧𝐤👇:-  https://bit.ly/3ZfT8U4 Enroll For FREE & Get Certified🎓

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Python Cheatsheet

𝐒𝐐𝐋 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 😍 🚀 Here are some top resources offering free courses to help you learn SQL from scratch or level up your skills. Whether you're preparing for interviews, aiming for a job in data analytics, or improving your database knowledge, these courses have got you covered! 𝐋𝐢𝐧𝐤 👇:-    https://pdlink.in/4iWv3tk   Enroll For FREE & Get Certified 🎓

𝗛𝗼𝘄 𝘁𝗼 𝗰𝗼𝗱𝗲 𝘄𝗶𝘁𝗵 𝗚𝗶𝘁𝗛𝘂𝗯 𝗖𝗼𝗽𝗶𝗹𝗼𝘁? A recent study by GitHub and Microsoft discovered that AI now authors 46% of new code. They also found that overall developer productivity surged by 55%, leading to more efficient coding processes. When we talk about AI-powered coding, we mainly talk about GitHub Copilot. But 𝗵𝗼𝘄 𝗚𝗶𝘁𝗛𝘂𝗯 𝗖𝗼𝗽𝗶𝗹𝗼𝘁 𝘄𝗼𝗿𝗸𝘀? The process goes in the following steps: 𝟭. 𝗦𝗲𝗰𝘂𝗿𝗲 𝗽𝗿𝗼𝗺𝗽𝘁 𝘁𝗿𝗮𝗻𝘀𝗺𝗶𝘀𝘀𝗶𝗼𝗻: Your prompts are securely sent to Copilot, ensuring data privacy. 𝟮. 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴: Copilot analyzes the code around your cursor, the file type, and other open files to offer relevant suggestions. 𝟯. 𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗳𝗶𝗹𝘁𝗲𝗿𝗶𝗻𝗴: It filters out personal data and inappropriate content, focusing solely on generating helpful code. 𝟰. 𝗖𝗼𝗱𝗲 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻: Based on the intent identified in your prompts, Copilot crafts code suggestions that align with your coding style and project standards. 𝟱. 𝗨𝘀𝗲𝗿 𝗶𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻: Here, we can decide whether to use, tweak, or reject Copilot's suggestions. 𝟲. 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗹𝗼𝗼𝗽: Copilot learns from your interactions, improving its suggestions. Every time you tweak or reject its ideas, he knows from it. It employs techniques like zero-shot (asking without examples), one-shot (asking with an example), and few-shot learning (providing multiple examples) to adapt to our instructions, whether you provide examples or not. 𝟳. 𝗣𝗿𝗼𝗺𝗽𝘁 𝗵𝗶𝘀𝘁𝗼𝗿𝘆 𝗿𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻: It remembers past prompts and interactions, making future suggestions more accurate.

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