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Master Statistics for Data Science & Analytics
Statistics for Data Science & Analytics
Unlock the power of statistics for data science and analytics. This beginner-friendly course covers essential topics like descriptive statistics, probability, data visualization, and hypothesis testing—designed to help you analyze
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Course outline
Industry focussed curriculum designed by experts
Introduction to Statistics
3 items
0.30 hr
- Role of Statistics in Data Science
- Basic Concepts in Statistics
- Types and Sources of Data
Probability
3 items
0.40 hr
- Introduction to Probability Concepts
- Key Principles and Theorems in Probability
- Understanding Probability Distributions
- Coding Exercises Probability - Beginner
Descriptive Statistics
4 items
1.10 hr
- Introduction to Probability Concepts (Complete)
- Key Principles and Theorems in Probability
- Understanding Probability Distributions
- Coding Exercises Probability - Beginner
Statistical Inference
4 items
1.15 hr
- Understanding Sampling
- Estimation Techniques
- Hypothesis Testing Frameworks
- Testing Methods
- Coding Exercises Statistical Inference - Beginner
- Coding Exercises Statistical Inference - Intermediate
Guided Projects
Solve real-world projects with a step-by-step guide, starter code templates, and access to model solutions to boost your skills and build a standout resume.
- GUIDED PROJECT 1
- Analyzing Call Center Efficiency
- As a data analyst for a telecommunications company, you’ll analyze customer support call center data to uncover probabilistic patterns and operational insights. Using probability distributions, sampling, estimation, and hypothesis testing, your goal is to assess call arrival behavior, service efficiency across shifts, and average wait times—enabling data-driven improvements in call center performance.
- GUIDED PROJECT 2
- Analyzing Factors Influencing Student Academic Performance
- In this project, you’ll step into the role of a Data Analyst for an educational consulting firm. Using real-world student performance data, your task is to perform a comprehensive statistical analysis to identify key factors affecting academic success. You'll apply descriptive and inferential statistical techniques to uncover insights and support data-driven recommendations—without using machine learning. Descriptive Statistics Data Visualization Correlation Analysis Hypothesis Testing Confidence Interval Estimation
- GUIDED PROJECT 3
- Customer Purchase Behavior Analysis
- As a junior data analyst at a retail company, your job is to analyze online customer transaction data to uncover patterns in purchase behavior. Through descriptive statistics and data visualization, you’ll explore spending habits, product quantity trends, and segment-based differences—providing actionable insights for marketing and sales teams. Descriptive Statistics Measures of Dispersion Data Visualization Customer Segmentation Analysis Correlation Analysis
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