Essential Topics to Master Data Science Interviews

Deepshika

Essential Topics to Master Data Science Interviews

Here is a list of all the Essential Topics to Master Data Science Interviews:

SQL:

1. Foundations

– Craft SELECT statements with WHERE, ORDER BY, GROUP BY, HAVING

– Embrace 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.