Computer Architecture, IIT Delhi
🆓 Free Online Course
💻 Video Lectures
⏰ 18 Modules
🏃♂️ Self paced
Teacher 👨🏫 : Prof. Anshul Kumar
🔗 https://nptel.ac.in/courses/106102062
#Computer_Architecture #IIT
➖➖➖➖➖➖➖➖➖➖➖➖➖➖
👉Join @coderslearning for more👈
🆓 Free Online Course
💻 Video Lectures
⏰ 18 Modules
🏃♂️ Self paced
Teacher 👨🏫 : Prof. Anshul Kumar
🔗 https://nptel.ac.in/courses/106102062
#Computer_Architecture #IIT
➖➖➖➖➖➖➖➖➖➖➖➖➖➖
👉Join @coderslearning for more👈
Complete DSA Roadmap
|-- Basic_Data_Structures
| |-- Arrays
| |-- Strings
| |-- Linked_Lists
| |-- Stacks
| └─ Queues
|
|-- Advanced_Data_Structures
| |-- Trees
| | |-- Binary_Trees
| | |-- Binary_Search_Trees
| | |-- AVL_Trees
| | └─ B-Trees
| |
| |-- Graphs
| | |-- Graph_Representation
| | | |- Adjacency_Matrix
| | | └ Adjacency_List
| | |
| | |-- Depth-First_Search
| | |-- Breadth-First_Search
| | |-- Shortest_Path_Algorithms
| | | |- Dijkstra's_Algorithm
| | | └ Bellman-Ford_Algorithm
| | |
| | └─ Minimum_Spanning_Tree
| | |- Prim's_Algorithm
| | └ Kruskal's_Algorithm
| |
| |-- Heaps
| | |-- Min_Heap
| | |-- Max_Heap
| | └─ Heap_Sort
| |
| |-- Hash_Tables
| |-- Disjoint_Set_Union
| |-- Trie
| |-- Segment_Tree
| └─ Fenwick_Tree
|
|-- Algorithmic_Paradigms
| |-- Brute_Force
| |-- Divide_and_Conquer
| |-- Greedy_Algorithms
| |-- Dynamic_Programming
| |-- Backtracking
| |-- Sliding_Window_Technique
| |-- Two_Pointer_Technique
| └─ Divide_and_Conquer_Optimization
| |-- Merge_Sort_Tree
| └─ Persistent_Segment_Tree
|
|-- Searching_Algorithms
| |-- Linear_Search
| |-- Binary_Search
| |-- Depth-First_Search
| └─ Breadth-First_Search
|
|-- Sorting_Algorithms
| |-- Bubble_Sort
| |-- Selection_Sort
| |-- Insertion_Sort
| |-- Merge_Sort
| |-- Quick_Sort
| └─ Heap_Sort
|
|-- Graph_Algorithms
| |-- Depth-First_Search
| |-- Breadth-First_Search
| |-- Topological_Sort
| |-- Strongly_Connected_Components
| └─ Articulation_Points_and_Bridges
|
|-- Dynamic_Programming
| |-- Introduction_to_DP
| |-- Fibonacci_Series_using_DP
| |-- Longest_Common_Subsequence
| |-- Longest_Increasing_Subsequence
| |-- Knapsack_Problem
| |-- Matrix_Chain_Multiplication
| └─ Dynamic_Programming_on_Trees
|
|-- Mathematical_and_Bit_Manipulation_Algorithms
| |-- Prime_Numbers_and_Sieve_of_Eratosthenes
| |-- Greatest_Common_Divisor
| |-- Least_Common_Multiple
| |-- Modular_Arithmetic
| └─ Bit_Manipulation_Tricks
|
|-- Advanced_Topics
| |-- Trie-based_Algorithms
| | |-- Auto-completion
| | └─ Spell_Checker
| |
| |-- Suffix_Trees_and_Arrays
| |-- Computational_Geometry
| |-- Number_Theory
| | |-- Euler's_Totient_Function
| | └─ Mobius_Function
| |
| └─ String_Algorithms
| |-- KMP_Algorithm
| └─ Rabin-Karp_Algorithm
|
|-- OnlinePlatforms
| |-- LeetCode
| |-- HackerRank
|-- Basic_Data_Structures
| |-- Arrays
| |-- Strings
| |-- Linked_Lists
| |-- Stacks
| └─ Queues
|
|-- Advanced_Data_Structures
| |-- Trees
| | |-- Binary_Trees
| | |-- Binary_Search_Trees
| | |-- AVL_Trees
| | └─ B-Trees
| |
| |-- Graphs
| | |-- Graph_Representation
| | | |- Adjacency_Matrix
| | | └ Adjacency_List
| | |
| | |-- Depth-First_Search
| | |-- Breadth-First_Search
| | |-- Shortest_Path_Algorithms
| | | |- Dijkstra's_Algorithm
| | | └ Bellman-Ford_Algorithm
| | |
| | └─ Minimum_Spanning_Tree
| | |- Prim's_Algorithm
| | └ Kruskal's_Algorithm
| |
| |-- Heaps
| | |-- Min_Heap
| | |-- Max_Heap
| | └─ Heap_Sort
| |
| |-- Hash_Tables
| |-- Disjoint_Set_Union
| |-- Trie
| |-- Segment_Tree
| └─ Fenwick_Tree
|
|-- Algorithmic_Paradigms
| |-- Brute_Force
| |-- Divide_and_Conquer
| |-- Greedy_Algorithms
| |-- Dynamic_Programming
| |-- Backtracking
| |-- Sliding_Window_Technique
| |-- Two_Pointer_Technique
| └─ Divide_and_Conquer_Optimization
| |-- Merge_Sort_Tree
| └─ Persistent_Segment_Tree
|
|-- Searching_Algorithms
| |-- Linear_Search
| |-- Binary_Search
| |-- Depth-First_Search
| └─ Breadth-First_Search
|
|-- Sorting_Algorithms
| |-- Bubble_Sort
| |-- Selection_Sort
| |-- Insertion_Sort
| |-- Merge_Sort
| |-- Quick_Sort
| └─ Heap_Sort
|
|-- Graph_Algorithms
| |-- Depth-First_Search
| |-- Breadth-First_Search
| |-- Topological_Sort
| |-- Strongly_Connected_Components
| └─ Articulation_Points_and_Bridges
|
|-- Dynamic_Programming
| |-- Introduction_to_DP
| |-- Fibonacci_Series_using_DP
| |-- Longest_Common_Subsequence
| |-- Longest_Increasing_Subsequence
| |-- Knapsack_Problem
| |-- Matrix_Chain_Multiplication
| └─ Dynamic_Programming_on_Trees
|
|-- Mathematical_and_Bit_Manipulation_Algorithms
| |-- Prime_Numbers_and_Sieve_of_Eratosthenes
| |-- Greatest_Common_Divisor
| |-- Least_Common_Multiple
| |-- Modular_Arithmetic
| └─ Bit_Manipulation_Tricks
|
|-- Advanced_Topics
| |-- Trie-based_Algorithms
| | |-- Auto-completion
| | └─ Spell_Checker
| |
| |-- Suffix_Trees_and_Arrays
| |-- Computational_Geometry
| |-- Number_Theory
| | |-- Euler's_Totient_Function
| | └─ Mobius_Function
| |
| └─ String_Algorithms
| |-- KMP_Algorithm
| └─ Rabin-Karp_Algorithm
|
|-- OnlinePlatforms
| |-- LeetCode
| |-- HackerRank
👍37
SQL From Basic to Advanced level
Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, <=, >=, <> etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.
Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.
Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all
- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -
Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.
This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.
Join @coderslearning for more free resources.
Like this post if it helps 😄❤️
Enjoy Learning 👍
Basic SQL is ONLY 7 commands:
- SELECT
- FROM
- WHERE (also use SQL comparison operators such as =, <=, >=, <> etc.)
- ORDER BY
- Aggregate functions such as SUM, AVERAGE, COUNT etc.
- GROUP BY
- CREATE, INSERT, DELETE, etc.
You can do all this in just one morning.
Once you know these, take the next step and learn commands like:
- LEFT JOIN
- INNER JOIN
- LIKE
- IN
- CASE WHEN
- HAVING (undertstand how it's different from GROUP BY)
- UNION ALL
This should take another day.
Once both basic and intermediate are done, start learning more advanced SQL concepts such as:
- Subqueries (when to use subqueries vs CTE?)
- CTEs (WITH AS)
- Stored Procedures
- Triggers
- Window functions (LEAD, LAG, PARTITION BY, RANK, DENSE RANK)
These can be done in a couple of days.
Learning these concepts is NOT hard at all
- what takes time is practice and knowing what command to use when. How do you master that?
- First, create a basic SQL project
- Then, work on an intermediate SQL project (search online) -
Lastly, create something advanced on SQL with many CTEs, subqueries, stored procedures and triggers etc.
This is ALL you need to become a badass in SQL, and trust me when I say this, it is not rocket science. It's just logic.
Join @coderslearning for more free resources.
Like this post if it helps 😄❤️
Enjoy Learning 👍
👍38
12 incredible AI tools that can revolutionize your productivity and streamline your workflow.
1. ChatGPT: Your AI-powered problem-solver, ready to tackle any task with interactive conversations.
2. Writesonic: Unleash your creativity with this versatile AI writing tool, generating compelling content for every need.
3. Midjourney: Explore the boundless realm of imagination with this AI art generator, creating stunning visuals that bring your ideas to life.
4. Replit: Coding enthusiasts rejoice! This AI code generator simplifies programming tasks and accelerates your development process.
5. Synthesia: Elevate your video production with this AI video generator, crafting engaging and personalized videos with ease.
6. Soundraw: Discover the magic of AI music composition with this innovative tool, generating melodies and soundtracks that perfectly capture your mood.
7. Fliki: Unleash your inner content creator with this AI TikTok generator, producing captivating and trendy short-form videos in no time.
8. Starrytars: Capture your unique essence with this AI avatar generator, creating personalized digital avatars that reflect your personality.
9. Slides AI: Transform your presentations into masterpieces with this AI presentation tool, crafting visually stunning and impactful slides.
10. Remini: Enhance your photos with this AI photo editor, restoring old images and bringing life back to your cherished memories.
11. Pictory: Elevate your video editing skills with this AI video editor, adding creative elements and enhancing the visual appeal of your videos.
12. Wordtune: Express your thoughts with clarity and precision with this AI writing assistant, summarizing notes and rewording sentences for maximum impact. Harness the power of AI and experience the transformative impact it can have on your productivity, creativity, and overall success. Embrace the future of technology and unlock the endless possibilities that await you.
Join @coderslearning for more free resources.
Like this post if it helps ❤️
1. ChatGPT: Your AI-powered problem-solver, ready to tackle any task with interactive conversations.
2. Writesonic: Unleash your creativity with this versatile AI writing tool, generating compelling content for every need.
3. Midjourney: Explore the boundless realm of imagination with this AI art generator, creating stunning visuals that bring your ideas to life.
4. Replit: Coding enthusiasts rejoice! This AI code generator simplifies programming tasks and accelerates your development process.
5. Synthesia: Elevate your video production with this AI video generator, crafting engaging and personalized videos with ease.
6. Soundraw: Discover the magic of AI music composition with this innovative tool, generating melodies and soundtracks that perfectly capture your mood.
7. Fliki: Unleash your inner content creator with this AI TikTok generator, producing captivating and trendy short-form videos in no time.
8. Starrytars: Capture your unique essence with this AI avatar generator, creating personalized digital avatars that reflect your personality.
9. Slides AI: Transform your presentations into masterpieces with this AI presentation tool, crafting visually stunning and impactful slides.
10. Remini: Enhance your photos with this AI photo editor, restoring old images and bringing life back to your cherished memories.
11. Pictory: Elevate your video editing skills with this AI video editor, adding creative elements and enhancing the visual appeal of your videos.
12. Wordtune: Express your thoughts with clarity and precision with this AI writing assistant, summarizing notes and rewording sentences for maximum impact. Harness the power of AI and experience the transformative impact it can have on your productivity, creativity, and overall success. Embrace the future of technology and unlock the endless possibilities that await you.
Join @coderslearning for more free resources.
Like this post if it helps ❤️
❤23
Essential Python Libraries 😄👇
1. NumPy:
- Efficient numerical operations and array manipulation.
2. Pandas:
- Data manipulation and analysis with powerful data structures (DataFrame, Series).
3. Matplotlib:
- 2D plotting library for creating visualizations.
4. Scikit-learn:
- Machine learning toolkit for classification, regression, clustering, etc.
5. TensorFlow:
- Open-source machine learning framework for building and deploying ML models.
6. PyTorch:
- Deep learning library, particularly popular for neural network research.
7. Django:
- High-level web framework for building robust, scalable web applications.
8. Flask:
- Lightweight web framework for building smaller web applications and APIs.
9. Requests:
- HTTP library for making HTTP requests.
10. Beautiful Soup:
- Web scraping library for pulling data out of HTML and XML files.
As a beginner, you can start with Pandas and Numpy libraries for Data Science. You can start applying ML libraries like Scikit-learn, Tensorflow, Pytorch, etc. in your data projects.
Join @coderslearning for more!!
Hope it helps :)
1. NumPy:
- Efficient numerical operations and array manipulation.
2. Pandas:
- Data manipulation and analysis with powerful data structures (DataFrame, Series).
3. Matplotlib:
- 2D plotting library for creating visualizations.
4. Scikit-learn:
- Machine learning toolkit for classification, regression, clustering, etc.
5. TensorFlow:
- Open-source machine learning framework for building and deploying ML models.
6. PyTorch:
- Deep learning library, particularly popular for neural network research.
7. Django:
- High-level web framework for building robust, scalable web applications.
8. Flask:
- Lightweight web framework for building smaller web applications and APIs.
9. Requests:
- HTTP library for making HTTP requests.
10. Beautiful Soup:
- Web scraping library for pulling data out of HTML and XML files.
As a beginner, you can start with Pandas and Numpy libraries for Data Science. You can start applying ML libraries like Scikit-learn, Tensorflow, Pytorch, etc. in your data projects.
Join @coderslearning for more!!
Hope it helps :)
👍35