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 and
ential 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
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