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Essential Topics to Master Data Science Interviews: 🚀 SQL: 1. Foundations - Master SELECT statements with WHERE,Essential ToEssential ToEssential - Basic JOINS (INNER, LEFT, RIGHT, FULL) - Understand simple databases and table structures 2. Intermediate SQL - Aggregate functions (COUNT, SUM, AVG, MAX, MIN) - Subqueries & nested queries - Common Table Expressions (WITH clause) - CASE statements for logical operations 3. Advanced SQL - Advanced JOIN techniques (self-join, non-equi join) - Window functions (OVER, PARTITION BY, ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG) - Query optimization with indexing - Data manipulation (INSERT, UPDATE, DELETE) Python: 1. Python Basics - Syntax, variables, and data types - Control structures (`if-else`, for andential Toloops) - Data structures (lists, dictionaries, sets, tuples) - Functions, lambda functions, error handling (try-except) - Modules and packages 2. Pandas & Numpy - Create and manipulate DataFrames & Series - Indexing, selecting, and filtering data - Handle missing data (`fillna`, `dropna`) - Aggregate data with groupby - Merge, join, and concatenate datasets 3. Data Visualization with Python - Plot with Matplotlib (line, bar, histograms) - Visualize with Seaborn (scatter, box, pair plots) - Customize plots (sizes, labels, legends, color palettes) - Intro to interactive visualizations (e.g., Plotly) Excel: 1. Excel Essentials - Basic formulas (`SUMIFS`, COUNTIFS,Essent etc.) - Charts and basic data visualization - Sort, filter, and conditional formatting 2. Intermediate Excel - Advanced formulas (`V/XLOOKUP`, INDEX-MATCH, nested IF) - PivotTables & PivotCharts - Data validation and What-if analysis 3. Advanced Excel - Array formulas and advanced functions - Power Pivot & Data Model - Advanced Filter, Slicers, Timelines - Dynamic charts & interactive dashboards Power BI: 1. Data Modeling in Power BI - Import data from multiple sources - Manage relationships between datasets - Data modeling basics (star, snowflake schemas) 2. Data Transformation in Power BI - Data cleaning with Power Query - Advanced data shaping techniques - Calculated columns & measures with DAX 3. Data Visualization & Reporting in Power BI - Interactive reports & dashboards - Visualizations (bar, line, pie charts, maps) - Publish, share, & schedule data refreshes Statistics Fundamentals: - Mean, Median, Mode - Standard Deviation & Variance - Probability Distributions, Hypothesis Testing - P-values & Confidence Intervals - Correlation & Simple Linear Regression - Normal, Binomial, Poisson Distributions Show some ❤️ if you're ready to elevate your data science journey! 📊 Join @coderslearning for more! ✅ ENJOY LEARNING! 👍👍

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