Coding Interview Resources

Data Structures You Should Know

𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗧𝗼 𝗘𝗻𝗿𝗼𝗹𝗹 𝗜𝗻 𝟮𝟬𝟮𝟱 😍 Learn Fundamental Skills with Free Online Courses & Earn Certificates - AI - GenAI - Data Science - BigData  - Python - UI/UX ,Cloud - Machine Learning - Cyber Security  𝐋𝐢𝐧𝐤 👇:-  https://pdlink.in/4ovjVWY Enroll for FREE & Get Certified 🎓

DSA Handwritten Notes

Data Science Roadmap | |-- Fundamentals | |-- Mathematics | | |-- Linear Algebra | | |-- Calculus | | |-- Probability and Statistics | | | |-- Programming | | |-- Python | | |-- R | | |-- SQL | |-- Data Collection and Cleaning | |-- Data Sources | | |-- APIs | | |-- Web Scraping | | |-- Databases | | | |-- Data Cleaning | | |-- Missing Values | | |-- Data Transformation | | |-- Data Normalization | |-- Data Analysis | |-- Exploratory Data Analysis (EDA) | | |-- Descriptive Statistics | | |-- Data Visualization | | |-- Hypothesis Testing | | | |-- Data Wrangling | | |-- Pandas | | |-- NumPy | | |-- dplyr (R) | |-- Machine Learning | |-- Supervised Learning | | |-- Regression | | |-- Classification | | | |-- Unsupervised Learning | | |-- Clustering | | |-- Dimensionality Reduction | | | |-- Reinforcement Learning | | |-- Q-Learning | | |-- Policy Gradient Methods | | | |-- Model Evaluation | | |-- Cross-Validation | | |-- Performance Metrics | | |-- Hyperparameter Tuning | |-- Deep Learning | |-- Neural Networks | | |-- Feedforward Networks | | |-- Backpropagation | | | |-- Advanced Architectures | | |-- Convolutional Neural Networks (CNN) | | |-- Recurrent Neural Networks (RNN) | | |-- Transformers | | | |-- Tools and Frameworks | | |-- TensorFlow | | |-- PyTorch | |-- Natural Language Processing (NLP) | |-- Text Preprocessing | | |-- Tokenization | | |-- Stop Words Removal | | |-- Stemming and Lemmatization | | | |-- NLP Techniques | | |-- Word Embeddings | | |-- Sentiment Analysis | | |-- Named Entity Recognition (NER) | |-- Data Visualization | |-- Basic Plotting | | |-- Matplotlib | | |-- Seaborn | | |-- ggplot2 (R) | | | |-- Interactive Visualization | | |-- Plotly | | |-- Bokeh | | |-- Dash | |-- Big Data | |-- Tools and Frameworks | | |-- Hadoop | | |-- Spark | | | |-- NoSQL Databases | |-- MongoDB | |-- Cassandra | |-- Cloud Computing | |-- Cloud Platforms | | |-- AWS | | |-- Google Cloud | | |-- Azure | | | |-- Data Services | |-- Data Storage (S3, Google Cloud Storage) | |-- Data Pipelines (Dataflow, AWS Data Pipeline) | |-- Model Deployment | |-- Serving Models | | |-- Flask/Django | | |-- FastAPI | | | |-- Model Monitoring | |-- Performance Tracking | |-- A/B Testing | |-- Domain Knowledge | |-- Industry-Specific Applications | | |-- Finance | | |-- Healthcare | | |-- Retail | |-- Ethical and Responsible AI | |-- Bias and Fairness | |-- Privacy and Security | |-- Interpretability and Explainability | |-- Communication and Storytelling | |-- Reporting | |-- Dashboarding | |-- Presentation Skills | |-- Advanced Topics | |-- Time Series Analysis | |-- Anomaly Detection | |-- Graph Analytics | |-- *PH4N745M* └-- Comments |-- # Single-line comment (Python) └-- /* Multi-line comment (Python/R) */

𝟓 𝐅𝐫𝐞𝐞 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐭𝐨 𝐁𝐮𝐢𝐥𝐝 𝐀𝐈 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧𝐬 & 𝐀𝐠𝐞𝐧𝐭𝐬 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐂𝐨𝐝𝐢𝐧𝐠😍 Want to Create AI Automations & Agents Without Writing a Single Line of Code?🧑‍💻 These 5 free YouTube tutorials will take you from complete beginner to automation expert in record time.🧑‍🎓✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4lhYwhn Just pure, actionable automation skills — for free.✅️

FREE COURSES TO LEARN CLOUD COMPUTING 👇👇 Intro to Cloud Computing FREE UDACITY COURSE https://imp.i115008.net/2rXxJM Introduction to Cloud Computing FREE UDEMY COURSE https://bit.ly/3sGKjkA Free AWS Certified Cloud Practitioner 2019 [4.5 star ratings out of 5] https://bit.ly/3GMG9wJ Handbook of Cloud Computing https://studytm.files.wordpress.com/2014/03/hand-book-of-cloud-computing.pdf Google Cloud Computing FREE COURSE https://inthecloud.withgoogle.com/cloud-learning-paths-22/register.html Cloud Computing for Dummies FREE BOOK https://github.com/manjunath5496/AWS-Books/blob/master/azw(12).pdf ENJOY LEARNING 👍👍

𝗔𝗜 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 🚀 AI is the future now & highly in demand  💼 Learn in-demand AI skills 📚 Beginner-friendly — No experience needed ✅ Get Certified & Boost Your Career 🎯 100% Free – Limited Time! 🔗 𝗘𝗻𝗿𝗼𝗹𝗹 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘 𝗡𝗼𝘄 👇:- https://pdlink.in/3U3eZuq 📌 Enroll today & start your AI journey!

Essential Topics to Master Data Analytics Interviews: 🚀 SQL: 1. Foundations - SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING - Basic JOINS (INNER, LEFT, RIGHT, FULL) - Navigate through simple databases and tables 2. Intermediate SQL - Utilize Aggregate functions (COUNT, SUM, AVG, MAX, MIN) - Embrace Subqueries and nested queries - Master Common Table Expressions (WITH clause) - Implement CASE statements for logical queries 3. Advanced SQL - Explore Advanced JOIN techniques (self-join, non-equi join) - Dive into Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, lead, lag) - Optimize queries with indexing - Execute Data manipulation (INSERT, UPDATE, DELETE) Python: 1. Python Basics - Grasp Syntax, variables, and data types - Command Control structures (if-else, for and while loops) - Understand Basic data structures (lists, dictionaries, sets, tuples) - Master Functions, lambda functions, and error handling (try-except) - Explore Modules and packages 2. Pandas & Numpy - Create and manipulate DataFrames and Series - Perfect Indexing, selecting, and filtering data - Handle missing data (fillna, dropna) - Aggregate data with groupby, summarizing data - Merge, join, and concatenate datasets 3. Data Visualization with Python - Plot with Matplotlib (line plots, bar plots, histograms) - Visualize with Seaborn (scatter plots, box plots, pair plots) - Customize plots (sizes, labels, legends, color palettes) - Introduction to interactive visualizations (e.g., Plotly) Excel: 1. Excel Essentials - Conduct Cell operations, basic formulas (SUMIFS, COUNTIFS, AVERAGEIFS, IF, AND, OR, NOT & Nested Functions etc.) - Dive into charts and basic data visualization - Sort and filter data, use Conditional formatting 2. Intermediate Excel - Master Advanced formulas (V/XLOOKUP, INDEX-MATCH, nested IF) - Leverage PivotTables and PivotCharts for summarizing data - Utilize data validation tools - Employ What-if analysis tools (Data Tables, Goal Seek) 3. Advanced Excel - Harness Array formulas and advanced functions - Dive into Data Model & Power Pivot - Explore Advanced Filter, Slicers, and Timelines in Pivot Tables - Create dynamic charts and interactive dashboards Power BI: 1. Data Modeling in Power BI - Import data from various sources - Establish and manage relationships between datasets - Grasp Data modeling basics (star schema, snowflake schema) 2. Data Transformation in Power BI - Use Power Query for data cleaning and transformation - Apply advanced data shaping techniques - Create Calculated columns and measures using DAX 3. Data Visualization and Reporting in Power BI - Craft interactive reports and dashboards - Utilize Visualizations (bar, line, pie charts, maps) - Publish and share reports, schedule data refreshes Statistics Fundamentals: - Mean, Median, Mode - Standard Deviation, Variance - Probability Distributions, Hypothesis Testing - P-values, Confidence Intervals - Correlation, Simple Linear Regression - Normal Distribution, Binomial Distribution, Poisson Distribution. Show some ❤️ if you're ready to elevate your data analytics journey! 📊 ENJOY LEARNING 👍👍

𝗠𝗮𝘀𝘁𝗲𝗿 𝗦𝗤𝗟 𝗶𝗻 𝗝𝘂𝘀𝘁 𝟳 𝗗𝗮𝘆𝘀: 𝗧𝗵𝗲 𝗨𝗹𝘁𝗶𝗺𝗮𝘁𝗲 𝗙𝗿𝗲𝗲 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝘁𝗼 𝗚𝗲𝘁 𝗝𝗼𝗯-𝗥𝗲𝗮𝗱𝘆😍 Want to learn SQL in just 7 days?🧑‍🎓 Whether you’re a complete beginner or prepping for interviews, this 7-day plan will take you from writing your first SELECT query to mastering JOINs, transactions, and even database design.🧑‍💻✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3Hs7Fps Perfect for students, freshers, and aspiring data analysts.✅️

How Coders Can Survive—and Thrive—in a ChatGPT World Artificial intelligence, particularly generative AI powered by large language models (LLMs), could upend many coders’ livelihoods. But some experts argue that AI won’t replace human programmers—not immediately, at least. “You will have to worry about people who are using AI replacing you,” says Tanishq Mathew Abraham, a recent Ph.D. in biomedical engineering at the University of California, Davis and the CEO of medical AI research center MedARC. Here are some tips and techniques for coders to survive and thrive in a generative AI world. Stick to Basics and Best Practices While the myriad AI-based coding assistants could help with code completion and code generation, the fundamentals of programming remain: the ability to read and reason about your own and others’ code, and understanding how the code you write fits into a larger system. Find the Tool That Fits Your Needs Finding the right AI-based tool is essential. Each tool has its own ways to interact with it, and there are different ways to incorporate each tool into your development workflow—whether that’s automating the creation of unit tests, generating test data, or writing documentation. Clear and Precise Conversations Are Crucial When using AI coding assistants, be detailed about what you need and view it as an iterative process. Abraham proposes writing a comment that explains the code you want so the assistant can generate relevant suggestions that meet your requirements. Be Critical and Understand the Risks Software engineers should be critical of the outputs of large language models, as they tend to hallucinate and produce inaccurate or incorrect code. “It’s easy to get stuck in a debugging rabbit hole when blindly using AI-generated code, and subtle bugs can be difficult to spot,” Vaithilingam says.

𝐏𝐚𝐲 𝐀𝐟𝐭𝐞𝐫 𝐏𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 - 𝗟𝗮𝗻𝗱 𝗬𝗼𝘂𝗿 𝗗𝗿𝗲𝗮𝗺 𝗧𝗲𝗰𝗵 𝗝𝗼𝗯😍 Curriculum designed and taught by Alumni from IITs & Leading Tech Companies. 60+ Hiring Drives Every Month 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:-  🌟 500+ Hiring Partners 🤝Trusted by 7500+ Students 💼 Avg. Rs. 7.4 LPA 🚀 41 LPA Highest Package Eligibility: BTech / BCA / BSc / MCA / MSc 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐍𝐨𝐰👇 :-  https://pdlink.in/4hO7rWY Hurry, limited seats available!🏃‍♀️

Data Analyst Interview Questions 👇 1.How to create filters in Power BI? Filters are an integral part of Power BI reports. They are used to slice and dice the data as per the dimensions we want. Filters are created in a couple of ways. Using Slicers: A slicer is a visual under Visualization Pane. This can be added to the design view to filter our reports. When a slicer is added to the design view, it requires a field to be added to it. For example- Slicer can be added for Country fields. Then the data can be filtered based on countries. Using Filter Pane: The Power BI team has added a filter pane to the reports, which is a single space where we can add different fields as filters. And these fields can be added depending on whether you want to filter only one visual(Visual level filter), or all the visuals in the report page(Page level filters), or applicable to all the pages of the report(report level filters) 2.How to sort data in Power BI? Sorting is available in multiple formats. In the data view, a common sorting option of alphabetical order is there. Apart from that, we have the option of Sort by column, where one can sort a column based on another column. The sorting option is available in visuals as well. Sort by ascending and descending option by the fields and measure present in the visual is also available. 3.How to convert pdf to excel? Open the PDF document you want to convert in XLSX format in Acrobat DC. Go to the right pane and click on the “Export PDF” option. Choose spreadsheet as the Export format. Select “Microsoft Excel Workbook.” Now click “Export.” Download the converted file or share it. 4. How to enable macros in excel? Click the file tab and then click “Options.” A dialog box will appear. In the “Excel Options” dialog box, click on the “Trust Center” and then “Trust Center Settings.” Go to the “Macro Settings” and select “enable all macros.” Click OK to apply the macro settings.

𝗧𝗼𝗽 𝗣𝘆𝘁𝗵𝗼𝗻 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗔𝘀𝗸𝗲𝗱 𝗯𝘆 𝗠𝗡𝗖𝘀😍 If you can answer these Python questions, you’re already ahead of 90% of candidates.🧑‍💻✨️ These aren’t your average textbook questions. These are real interview questions asked in top MNCs — designed to test how deeply you understand Python.📊📍 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4mu4oVx This is the smart way to prepare✅️

Interviewing soon? Avoid these common mistakes! Nail That Offer! In interviews, several behaviours can undermine your professionalism and candidacy. 📍 Lack of preparation: Failing to research the company, job role, and industry reflects a lack of interest and commitment. 📍 Arriving late or unprepared: Punctuality and readiness are key indicators of reliability and professionalism. 📍 Poor body language: Avoiding eye contact, slouching, or move restlessly can convey disinterest or nervousness. 📍 Overconfidence or arrogance: While confidence is valued, arrogance can be off-putting to employers. 📍 Speaking negatively about past employers or experiences: This reflects poorly on your attitude and professionalism. 📍 Lack of enthusiasm or passion: Demonstrating genuine interest in the role and company is essential for making a positive impression. By direct clear of these behaviours, you can present yourself as a polished and deserving candidate, increasing your chances of success in the interview process.

𝟭𝟬𝟬% 𝗙𝗥𝗘𝗘 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 😍 Master in-demand skills like Excel, SQL, Power BI & Data Visualization with 100% FREE Certification 💯 ✅ Industry-Relevant Curriculum ✅ No Cost – Lifetime Free Access ✅ Boost Your Resume & Job Readiness Perfect for Students, Freshers & Career Switchers! 𝐋𝐢𝐧𝐤 👇:-    https://pdlink.in/4lp7hXQ   🎓 Enroll Now & Get Certified

Step-by-Step Approach to Learn Python ➊ Learn the Basics → Syntax, Variables, Data Types (int, float, string, boolean) ↓ ➋ Control Flow → If-Else, Loops (For, While), List Comprehensions ↓ ➌ Data Structures → Lists, Tuples, Sets, Dictionaries ↓ ➍ Functions & Modules → Defining Functions, Lambda Functions, Importing Modules ↓ ➎ File Handling → Reading/Writing Files, CSV, JSON ↓ ➏ Object-Oriented Programming (OOP) → Classes, Objects, Inheritance, Polymorphism ↓ ➐ Error Handling & Debugging → Try-Except, Logging, Debugging Techniques ↓ ➑ Advanced Topics → Regular Expressions, Multi-threading, Decorators, Generators Free Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L ENJOY LEARNING 👍👍

𝗠𝗮𝘀𝘁𝗲𝗿 𝗦𝗼𝗳𝘁 𝗦𝗸𝗶𝗹𝗹𝘀 𝗳𝗼𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗦𝘂𝗰𝗰𝗲𝘀𝘀!😍 Want to stand out in your career? Soft skills are just as important as technical expertise! 🌟 Here are 3 FREE courses to help you communicate, negotiate, and present with confidence🧑‍💻✨️ 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/41V1Yqi Tag someone who needs this boost! 🚀

10 Simple Habits to Improve Your Coding Skills 🧠💻 🔥 Practice regularly, not just when you're stuck 🔥 Build small projects to apply what you learn 🔥 Review and refactor your old code 🔥 Join coding communities or forums 🔥 Follow coding channels and blogs 🔥 Take part in coding challenges (e.g., LeetCode, HackerRank) 🔥 Keep a code journal or notes 🔥 Learn version control (Git is your friend!) 🔥 Teach someone else — it deepens your understanding 🔥 Stay curious & never stop learning 💬 React "❤️" for more!

🐍 Master Python for Data Analytics! Python is a powerful tool for data analysis, automation, and visualization. Here’s the ultimate roadmap: 🔹 Basic Concepts: ➡️ Syntax, variables, and data types (integers, floats, strings, booleans) ➡️ Control structures (if-else, for and while loops) ➡️ Basic data structures (lists, dictionaries, sets, tuples) ➡️ Functions, lambda functions, and error handling (try-except) ➡️ Working with modules and packages 🔹 Pandas & NumPy: ➡️ Creating and manipulating DataFrames and arrays ➡️ Data filtering, aggregation, and reshaping ➡️ Handling missing values ➡️ Efficient data operations with NumPy 🔹 Data Visualization: ➡️ Creating visualizations using Matplotlib and Seaborn ➡️ Plotting line, bar, scatter, and heatmaps 💡 Python is your key to unlocking data-driven decision-making. Start learning today! #PythonForData