Data science analyst for beginner

Data Science Analyst Study
(Beginner Level)
1. Introduction to Data Science Analysis
• Definition: Data Science Analysis involves extracting insights
from data to support decision-making.
• Role of a Data Analyst: Data cleaning, visualization, reporting,
and statistical analysis.
• Applications: Business analytics, healthcare, marketing, finance,
etc.

2. Essential Mathematics & Statistics
• Descriptive Statistics: Mean, Median, Mode, Standard Deviation,
Variance.
• Probability Basics: Probability distributions (Normal, Binomial),
Sampling techniques.
• Inferential Statistics: Hypothesis testing, Confidence intervals,
Correlation & Regression.

3. Programming for Data Analysis

• Python Basics: Variables, Data Types, Lists, Dictionaries, Loops,
Functions.
• Essential Libraries:
o NumPy: Numerical operations
o Pandas: Data manipulation
o Matplotlib & Seaborn: Data visualization


4. Data Preprocessing & Cleaning

• Handling Missing Data: Removing or imputing missing values.