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Coding Projects

Coding Projects

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Channel specialized for advanced concepts and projects to master: * Python programming * Web development * Java programming * Artificial Intelligence * Machine Learning Managed by: @love_data

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๐Ÿ“ˆ Analytical overview of Telegram channel Coding Projects

Channel Coding Projects (@programming_experts) in the English language segment is an active participant. Currently, the community unites 65 988 subscribers, ranking 1 981 in the Technologies & Applications category and 5 219 in the India region.

๐Ÿ“Š Audience metrics and dynamics

Since its creation on ะฝะตะฒั–ะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 65 988 subscribers.

According to the latest data from 10 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 718 over the last 30 days and by 27 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 3.94%. Within the first 24 hours after publication, content typically collects 1.25% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 599 views. Within the first day, a publication typically gains 822 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 8.
  • Thematic interests: Content is focused on key topics such as |--, algorithm, array, framework, javascript.

๐Ÿ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
โ€œChannel specialized for advanced concepts and projects to master: * Python programming * Web development * Java programming * Artificial Intelligence * Machine Learning Managed by: @love_dataโ€

Thanks to the high frequency of updates (latest data received on 11 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

65 988
Subscribers
+2724 hours
+1467 days
+71830 days
Posts Archive
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Essential Python Libraries to build your career in Data Science ๐Ÿ“Š๐Ÿ‘‡ 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. Seaborn: - Statistical data visualization built on top of Matplotlib. 5. Scikit-learn: - Machine learning toolkit for classification, regression, clustering, etc. 6. TensorFlow: - Open-source machine learning framework for building and deploying ML models. 7. PyTorch: - Deep learning library, particularly popular for neural network research. 8. SciPy: - Library for scientific and technical computing. 9. Statsmodels: - Statistical modeling and econometrics in Python. 10. NLTK (Natural Language Toolkit): - Tools for working with human language data (text). 11. Gensim: - Topic modeling and document similarity analysis. 12. Keras: - High-level neural networks API, running on top of TensorFlow. 13. Plotly: - Interactive graphing library for making interactive plots. 14. Beautiful Soup: - Web scraping library for pulling data out of HTML and XML files. 15. OpenCV: - Library for computer vision tasks. As a beginner, you can start with Pandas and NumPy for data manipulation and analysis. For data visualization, Matplotlib and Seaborn are great starting points. As you progress, you can explore machine learning with Scikit-learn, TensorFlow, and PyTorch. Free Notes & Books to learn Data Science: https://t.me/datasciencefree Python Project Ideas: https://t.me/dsabooks/85 Best Resources to learn Python & Data Science ๐Ÿ‘‡๐Ÿ‘‡ Python Tutorial Data Science Course by Kaggle Machine Learning Course by Google Best Data Science & Machine Learning Resources Interview Process for Data Science Role at Amazon Python Interview Resources Join @free4unow_backup for more free courses Like for more โค๏ธ ENJOY LEARNING๐Ÿ‘๐Ÿ‘

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Complete DSA Roadmap |-- Basic_Data_Structures | |-- Arrays | |-- Strings | |-- Linked_Lists | |-- Stacks | โ””โ”€ Queues | |-- Advanced_Data_Structures | |-- Trees | | |-- Binary_Trees | | |-- Binary_Search_Trees | | |-- AVL_Trees | | โ””โ”€ B-Trees | | | |-- Graphs | | |-- Graph_Representation | | | |- Adjacency_Matrix | | | โ”” Adjacency_List | | | | | |-- Depth-First_Search | | |-- Breadth-First_Search | | |-- Shortest_Path_Algorithms | | | |- Dijkstra's_Algorithm | | | โ”” Bellman-Ford_Algorithm | | | | | โ””โ”€ Minimum_Spanning_Tree | | |- Prim's_Algorithm | | โ”” Kruskal's_Algorithm | | | |-- Heaps | | |-- Min_Heap | | |-- Max_Heap | | โ””โ”€ Heap_Sort | | | |-- Hash_Tables | |-- Disjoint_Set_Union | |-- Trie | |-- Segment_Tree | โ””โ”€ Fenwick_Tree | |-- Algorithmic_Paradigms | |-- Brute_Force | |-- Divide_and_Conquer | |-- Greedy_Algorithms | |-- Dynamic_Programming | |-- Backtracking | |-- Sliding_Window_Technique | |-- Two_Pointer_Technique | โ””โ”€ Divide_and_Conquer_Optimization | |-- Merge_Sort_Tree | โ””โ”€ Persistent_Segment_Tree | |-- Searching_Algorithms | |-- Linear_Search | |-- Binary_Search | |-- Depth-First_Search | โ””โ”€ Breadth-First_Search | |-- Sorting_Algorithms | |-- Bubble_Sort | |-- Selection_Sort | |-- Insertion_Sort | |-- Merge_Sort | |-- Quick_Sort | โ””โ”€ Heap_Sort | |-- Graph_Algorithms | |-- Depth-First_Search | |-- Breadth-First_Search | |-- Topological_Sort | |-- Strongly_Connected_Components | โ””โ”€ Articulation_Points_and_Bridges | |-- Dynamic_Programming | |-- Introduction_to_DP | |-- Fibonacci_Series_using_DP | |-- Longest_Common_Subsequence | |-- Longest_Increasing_Subsequence | |-- Knapsack_Problem | |-- Matrix_Chain_Multiplication | โ””โ”€ Dynamic_Programming_on_Trees | |-- Mathematical_and_Bit_Manipulation_Algorithms | |-- Prime_Numbers_and_Sieve_of_Eratosthenes | |-- Greatest_Common_Divisor | |-- Least_Common_Multiple | |-- Modular_Arithmetic | โ””โ”€ Bit_Manipulation_Tricks | |-- Advanced_Topics | |-- Trie-based_Algorithms | | |-- Auto-completion | | โ””โ”€ Spell_Checker | | | |-- Suffix_Trees_and_Arrays | |-- Computational_Geometry | |-- Number_Theory | | |-- Euler's_Totient_Function | | โ””โ”€ Mobius_Function | | | โ””โ”€ String_Algorithms | |-- KMP_Algorithm | โ””โ”€ Rabin-Karp_Algorithm | |-- OnlinePlatforms | |-- LeetCode | |-- HackerRank

2 VERY IMPORTANT MISAKES to avoid for job seekers Trying or struggling to get Interview Calls Let me summarise. Many job applicants for analytics roles (also applicable for other roles) often get frustrated with receiving no interview calls DESPITE putting a lot of good projects, certifications and even their prior experience. There are probably 2 key yet common mistakes you could be making during your application: ๐Ÿ. ๐˜๐จ๐ฎ๐ซ ๐‘๐ž๐ฌ๐ฎ๐ฆ๐ž ๐ˆ๐ฌ๐ง'๐ญ ๐“๐š๐ข๐ฅ๐จ๐ซ๐ž๐ ๐…๐จ๐ซ ๐“๐ก๐ž ๐‘๐จ๐ฅ๐ž - Companies use an ATS to scan for relevant profiles amongst 100 of applications based on finding relevant key words. - Ensure you update your resume to include the skills they're looking for. - This will increase the chance of the ATS picking up on your resume. ๐Ÿ. ๐๐ฎ๐ข๐ฅ๐ ๐˜๐จ๐ฎ๐ซ ๐‹๐ข๐ง๐ค๐ž๐๐ˆ๐ง ๐๐ซ๐จ๐Ÿ๐ข๐ฅ๐ž & ๐€๐œ๐ญ๐ข๐ฏ๐ข๐ญ๐ฒ- - - - - If your resume reaches the technical/hiring team - they'll want to get more information about you. - Their Next Stop - YOUR LINKEDIN PROFILE - Update your certifications/skills & upload your key projects. - Be Active and Share Your Learnings. - This builds your credibility in their eyes Remember.... You're competing against large pool of equally or more talented individuals like yourself. On A Technical And Accomplishment level, you might on par with others. Then it goes down to who can stand out from the rest. Luck can play a huge role, but so can being strategic in your application. Leave no stone unturned. Join our WhatsApp channel: https://whatsapp.com/channel/0029VaI5CV93AzNUiZ5Tt226

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Core data science concepts you should know: ๐Ÿ”ข 1. Statistics & Probability Descriptive statistics: Mean, median, mode, standard deviation, variance Inferential statistics: Hypothesis testing, confidence intervals, p-values, t-tests, ANOVA Probability distributions: Normal, Binomial, Poisson, Uniform Bayes' Theorem Central Limit Theorem ๐Ÿ“Š 2. Data Wrangling & Cleaning Handling missing values Outlier detection and treatment Data transformation (scaling, encoding, normalization) Feature engineering Dealing with imbalanced data ๐Ÿ“ˆ 3. Exploratory Data Analysis (EDA) Univariate, bivariate, and multivariate analysis Correlation and covariance Data visualization tools: Matplotlib, Seaborn, Plotly Insights generation through visual storytelling ๐Ÿค– 4. Machine Learning Fundamentals Supervised Learning: Linear regression, logistic regression, decision trees, SVM, k-NN Unsupervised Learning: K-means, hierarchical clustering, PCA Model evaluation: Accuracy, precision, recall, F1-score, ROC-AUC Cross-validation and overfitting/underfitting Bias-variance tradeoff ๐Ÿง  5. Deep Learning (Basics) Neural networks: Perceptron, MLP Activation functions (ReLU, Sigmoid, Tanh) Backpropagation Gradient descent and learning rate CNNs and RNNs (intro level) ๐Ÿ—ƒ๏ธ 6. Data Structures & Algorithms (DSA) Arrays, lists, dictionaries, sets Sorting and searching algorithms Time and space complexity (Big-O notation) Common problems: string manipulation, matrix operations, recursion ๐Ÿ’พ 7. SQL & Databases SELECT, WHERE, GROUP BY, HAVING JOINS (inner, left, right, full) Subqueries and CTEs Window functions Indexing and normalization ๐Ÿ“ฆ 8. Tools & Libraries Python: pandas, NumPy, scikit-learn, TensorFlow, PyTorch R: dplyr, ggplot2, caret Jupyter Notebooks for experimentation Git and GitHub for version control ๐Ÿงช 9. A/B Testing & Experimentation Control vs. treatment group Hypothesis formulation Significance level, p-value interpretation Power analysis ๐ŸŒ 10. Business Acumen & Storytelling Translating data insights into business value Crafting narratives with data Building dashboards (Power BI, Tableau) Knowing KPIs and business metrics React โค๏ธ for more

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Complete DSA Roadmap |-- Basic_Data_Structures | |-- Arrays | |-- Strings | |-- Linked_Lists | |-- Stacks | โ””โ”€ Queues | |-- Advanced_Data_Structures | |-- Trees | | |-- Binary_Trees | | |-- Binary_Search_Trees | | |-- AVL_Trees | | โ””โ”€ B-Trees | | | |-- Graphs | | |-- Graph_Representation | | | |- Adjacency_Matrix | | | โ”” Adjacency_List | | | | | |-- Depth-First_Search | | |-- Breadth-First_Search | | |-- Shortest_Path_Algorithms | | | |- Dijkstra's_Algorithm | | | โ”” Bellman-Ford_Algorithm | | | | | โ””โ”€ Minimum_Spanning_Tree | | |- Prim's_Algorithm | | โ”” Kruskal's_Algorithm | | | |-- Heaps | | |-- Min_Heap | | |-- Max_Heap | | โ””โ”€ Heap_Sort | | | |-- Hash_Tables | |-- Disjoint_Set_Union | |-- Trie | |-- Segment_Tree | โ””โ”€ Fenwick_Tree | |-- Algorithmic_Paradigms | |-- Brute_Force | |-- Divide_and_Conquer | |-- Greedy_Algorithms | |-- Dynamic_Programming | |-- Backtracking | |-- Sliding_Window_Technique | |-- Two_Pointer_Technique | โ””โ”€ Divide_and_Conquer_Optimization | |-- Merge_Sort_Tree | โ””โ”€ Persistent_Segment_Tree | |-- Searching_Algorithms | |-- Linear_Search | |-- Binary_Search | |-- Depth-First_Search | โ””โ”€ Breadth-First_Search | |-- Sorting_Algorithms | |-- Bubble_Sort | |-- Selection_Sort | |-- Insertion_Sort | |-- Merge_Sort | |-- Quick_Sort | โ””โ”€ Heap_Sort | |-- Graph_Algorithms | |-- Depth-First_Search | |-- Breadth-First_Search | |-- Topological_Sort | |-- Strongly_Connected_Components | โ””โ”€ Articulation_Points_and_Bridges | |-- Dynamic_Programming | |-- Introduction_to_DP | |-- Fibonacci_Series_using_DP | |-- Longest_Common_Subsequence | |-- Longest_Increasing_Subsequence | |-- Knapsack_Problem | |-- Matrix_Chain_Multiplication | โ””โ”€ Dynamic_Programming_on_Trees | |-- Mathematical_and_Bit_Manipulation_Algorithms | |-- Prime_Numbers_and_Sieve_of_Eratosthenes | |-- Greatest_Common_Divisor | |-- Least_Common_Multiple | |-- Modular_Arithmetic | โ””โ”€ Bit_Manipulation_Tricks | |-- Advanced_Topics | |-- Trie-based_Algorithms | | |-- Auto-completion | | โ””โ”€ Spell_Checker | | | |-- Suffix_Trees_and_Arrays | |-- Computational_Geometry | |-- Number_Theory | | |-- Euler's_Totient_Function | | โ””โ”€ Mobius_Function | | | โ””โ”€ String_Algorithms | |-- KMP_Algorithm | โ””โ”€ Rabin-Karp_Algorithm | |-- OnlinePlatforms | |-- LeetCode | |-- HackerRank Best DSA RESOURCES: https://topmate.io/coding/886874 Credits: https://t.me/free4unow_backup All the best ๐Ÿ‘๐Ÿ‘

๐Ÿš€ ๐—œ๐—œ๐—ง ๐—ฅ๐—ผ๐—ผ๐—ฟ๐—ธ๐—ฒ๐—ฒ ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ & ๐—”๐—œ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป Placement Assistance With 5000+ companies.
๐Ÿš€ ๐—œ๐—œ๐—ง ๐—ฅ๐—ผ๐—ผ๐—ฟ๐—ธ๐—ฒ๐—ฒ ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ & ๐—”๐—œ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป Placement Assistance With 5000+ companies. โœ… Open to everyone โœ… 100% Online | 6 Months โœ… Industry-ready curriculum โœ… Taught By IIT Roorkee Professors ๐Ÿ”ฅ Companies are actively hiring candidates with Data Science & AI skills. โณ Deadline: 31st January 2026 ๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฒ๐—ฟ ๐—ก๐—ผ๐˜„ ๐Ÿ‘‡ :-  https://pdlink.in/49UZfkX โœ… Limited seats only

20 Frontend Project Ideas๐Ÿ”ฅ๐Ÿ‘จ๐Ÿปโ€๐Ÿ’ป ๐Ÿ”นPortfolio Website ๐Ÿ”นResponsive Blog Page ๐Ÿ”นRecipe Finder ๐Ÿ”นWeather Dashboard ๐Ÿ”นE-commerce Product Page ๐Ÿ”นMusic Player ๐Ÿ”นTask Management App UI ๐Ÿ”นInteractive To-Do List ๐Ÿ”นPersonal Finance Tracker ๐Ÿ”นMovie/TV Show Finder ๐Ÿ”นSocial Media Dashboard UI ๐Ÿ”นLanding Page for a Product ๐Ÿ”นPhoto Gallery ๐Ÿ”นQuiz App ๐Ÿ”นTravel Booking UI ๐Ÿ”นMarkdown Editor ๐Ÿ”นFitness Tracker Dashboard ๐Ÿ”นReal-time Chat UI ๐Ÿ”นRestaurant Menu Page ๐Ÿ”นOnline Quiz Generator Do not forget to React โค๏ธ to this Message for More Content Like this #techinfo

FREE Resources for HTML, CSS, and JavaScript: 1. Documentation and Tutorials: - [MDN Web Docs](https://developer.mozilla.org/en-US/) - [W3Schools](https://www.w3schools.com/) 2. Interactive Learning: - [Codecademy](https://www.codecademy.com/) - [freeCodeCamp](https://www.freecodecamp.org/) 3. Web Design Community: - [CSS-Tricks](https://css-tricks.com/) 4. Open Source Projects: - [GitHub](https://github.com/) 5. Problem-solving: - [Stack Overflow](https://stackoverflow.com/) 6. Images for Projects: - [Unsplash](https://unsplash.com/) - [Pexels](https://www.pexels.com/) Credits: https://t.me/free4unow_backup Like if you need similar content ๐Ÿ˜„๐Ÿ‘

๐—™๐˜‚๐—น๐—น ๐—ฆ๐˜๐—ฎ๐—ฐ๐—ธ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—บ๐—ฒ๐—ป๐˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ ๐Ÿ˜ * JAVA- Full Stack Development With G
๐—™๐˜‚๐—น๐—น ๐—ฆ๐˜๐—ฎ๐—ฐ๐—ธ ๐——๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—บ๐—ฒ๐—ป๐˜ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฃ๐—ฟ๐—ผ๐—ด๐—ฟ๐—ฎ๐—บ ๐Ÿ˜ * JAVA- Full Stack Development With Gen AI * MERN- Full Stack Development With Gen AI Highlightes:- * 2000+ Students Placed * Attend FREE Hiring Drives at our Skill Centres * Learn from India's Best Mentors ๐‘๐ž๐ ๐ข๐ฌ๐ญ๐ž๐ซ ๐๐จ๐ฐ๐Ÿ‘‡ :-  https://pdlink.in/4hO7rWY Hurry, limited seats available!

๐Ÿš€JavaScript Project Ideas ๐Ÿš€ ๐ŸŽฏ To-Do List App ๐ŸŽฏ Interactive Quiz App ๐ŸŽฏ Stopwatch and Timer ๐ŸŽฏ Weather Forecast Application ๐ŸŽฏ Expense Tracker ๐ŸŽฏ Image Carousel ๐ŸŽฏ Random Quote Generator ๐ŸŽฏ Music Player Interface ๐ŸŽฏ Password Generator ๐ŸŽฏ Note-Taking App ๐ŸŽฏ BMI Calculator ๐ŸŽฏ Live Search Filter โœจ Join my telegram for coding tips and tricks! ๐ŸŽฏ๐Ÿ’ก

๐Ÿš€ ๐Ÿฐ ๐—™๐—ฅ๐—˜๐—˜ ๐—ง๐—ฒ๐—ฐ๐—ต ๐—–๐—ผ๐˜‚๐—ฟ๐˜€๐—ฒ๐˜€ ๐—ง๐—ผ ๐—˜๐—ป๐—ฟ๐—ผ๐—น๐—น ๐—œ๐—ป ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ ๐Ÿ˜ ๐Ÿ“ˆ Upgrade your career with in-demand tech skills &
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Backend vs Frontend Development: Quick Comparison โœ… Backend Development - Works behind the scenes - Handles logic, databases, security, APIs - No direct user interaction - Core skills: Java, Python, Node.js, C#, MySQL, PostgreSQL, MongoDB - Best fields: Enterprise systems, Fintech, SaaS platforms - Job titles: Backend Developer, Software Engineer, API Engineer - India salary range: Fresher (4-8 LPA), Mid-level (10-22 LPA) Frontend Development - Works on what users see - Builds UI and UX - Runs in the browser - Core skills: HTML, CSS, JavaScript, React, Angular, Vue - Best fields: Consumer apps, Startups, Product companies - Job titles: Frontend Developer, UI Developer, Web Developer - India salary range: Fresher (3-7 LPA), Mid-level (8-18 LPA) Quick Comparison - Visibility: Frontend visible, backend invisible - Complexity: Backend logic-heavy, frontend UI-heavy - Tools: Backend uses servers and DBs, frontend uses browsers Which one do you prefer? - Love logic and systems? Backend ๐Ÿ‘ - Love design and UI? Frontend โค๏ธ - Want full control? Learn both (Full Stack ๐Ÿ™) Frontend Development: https://whatsapp.com/channel/0029VaxfCpv2v1IqQjv6Ke0r Backend Development: https://whatsapp.com/channel/0029VazSFWNG8l596hsThw2b

๐—œ๐—ป๐—ฑ๐—ถ๐—ฎโ€™๐˜€ ๐—•๐—ถ๐—ด๐—ด๐—ฒ๐˜€๐˜ ๐—›๐—ฎ๐—ฐ๐—ธ๐—ฎ๐˜๐—ต๐—ผ๐—ป | ๐—”๐—œ ๐—œ๐—บ๐—ฝ๐—ฎ๐—ฐ๐˜ ๐—•๐˜‚๐—ถ๐—น๐—ฑ๐—ฎ๐˜๐—ต๐—ผ๐—ป๐Ÿ˜ Participate in the national AI hac
๐—œ๐—ป๐—ฑ๐—ถ๐—ฎโ€™๐˜€ ๐—•๐—ถ๐—ด๐—ด๐—ฒ๐˜€๐˜ ๐—›๐—ฎ๐—ฐ๐—ธ๐—ฎ๐˜๐—ต๐—ผ๐—ป | ๐—”๐—œ ๐—œ๐—บ๐—ฝ๐—ฎ๐—ฐ๐˜ ๐—•๐˜‚๐—ถ๐—น๐—ฑ๐—ฎ๐˜๐—ต๐—ผ๐—ป๐Ÿ˜ Participate in the national AI hackathon under the India AI Impact Summit 2026 Submission deadline: 5th February 2026 Grand Finale: 16th February 2026, New Delhi ๐—ฅ๐—ฒ๐—ด๐—ถ๐˜€๐˜๐—ฒ๐—ฟ ๐—ก๐—ผ๐˜„๐Ÿ‘‡:-  https://pdlink.in/4qQfAOM a flagship initiative of the Government of India ๐Ÿ‡ฎ๐Ÿ‡ณ

Datasets for Data Science Projects
+5
Datasets for Data Science Projects

๐—ง๐—ผ๐—ฝ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ฑ ๐—•๐˜† ๐—œ๐—œ๐—ง ๐—ฅ๐—ผ๐—ผ๐—ฟ๐—ธ๐—ฒ๐—ฒ & ๐—œ๐—œ๐—  ๐— ๐˜‚๐—บ๐—ฏ๐—ฎ๐—ถ๐Ÿ˜ Placement Assistance Wi
๐—ง๐—ผ๐—ฝ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ข๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ฑ ๐—•๐˜† ๐—œ๐—œ๐—ง ๐—ฅ๐—ผ๐—ผ๐—ฟ๐—ธ๐—ฒ๐—ฒ & ๐—œ๐—œ๐—  ๐— ๐˜‚๐—บ๐—ฏ๐—ฎ๐—ถ๐Ÿ˜ Placement Assistance With 5000+ Companies  Deadline: 25th January 2026 ๐——๐—ฎ๐˜๐—ฎ ๐—ฆ๐—ฐ๐—ถ๐—ฒ๐—ป๐—ฐ๐—ฒ & ๐—”๐—œ :- https://pdlink.in/49UZfkX ๐—ฆ๐—ผ๐—ณ๐˜๐˜„๐—ฎ๐—ฟ๐—ฒ ๐—˜๐—ป๐—ด๐—ถ๐—ป๐—ฒ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด:- https://pdlink.in/4pYWCEK ๐——๐—ถ๐—ด๐—ถ๐˜๐—ฎ๐—น ๐— ๐—ฎ๐—ฟ๐—ธ๐—ฒ๐˜๐—ถ๐—ป๐—ด & ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜๐—ถ๐—ฐ๐˜€ :- https://pdlink.in/4tcUPia Hurry..Up Only Limited Seats Available