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.
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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Python Cheatsheet
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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.iss.one/free4unow_backup
ENJOY LEARNING 👍👍
### 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.iss.one/free4unow_backup
ENJOY LEARNING 👍👍
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Python Important Star Patterns.
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