This specialization provides a comprehensive understanding of advanced statistical techniques used in data science. Learners will explore linear regression, model diagnostics, variable selection, Bayesian statistics, and data preparation. The courses are designed to equip data scientists and researchers with the skills needed to analyze complex data sets and draw meaningful conclusions.
Advanced Statistical Techniques for Data Science Specialization
Advanced Statistical Techniques for Data Science Specialization
Master Advanced Statistical Techniques for Data. Gain deep insights into data through advanced statistical methods and practical applications.
Instructors: Ming-Long Lam
Included with 
Get in-depth knowledge of a subject
(7 reviews)
Intermediate level
Recommended experience
4 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(7 reviews)
Intermediate level
Recommended experience
4 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
How to perform linear and nonlinear regression analysis using R.
Techniques for diagnosing and remediating issues in regression models.
Bayesian statistical methods for data analysis and inference.
Overview
Skills you'll gain
- Regression Analysis
- Bayesian Statistics
- Statistical Inference
- Data Manipulation
- Data Visualization
- Exploratory Data Analysis
- Data Validation
- Data Cleansing
- Machine Learning
- Statistical Programming
- Analytics
- Data Science
- Statistical Analysis
- Statistical Modeling
- Statistical Methods
- Data Analysis
- Machine Learning Algorithms
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
May 2025
102 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
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- Develop a deep understanding of key concepts
- Earn a career certificate from Illinois Tech
Specialization - 5 course series
What you'll learn
Describe the assumptions of the linear regression models.
Use R to fit a linear regression model to a given data set.
Interpret and draw conclusions on the linear regression model.
Skills you'll gain
Regression Analysis, R Programming, Statistical Inference, R (Software), Probability & Statistics, Statistical Analysis, Data Manipulation, Linear Algebra, Data Analysis, and Statistical Modeling
What you'll learn
Describe the assumptions of the linear regression models.
Use diagnostic plots to detect violations of the assumptions of a linear regression model.
Perform variable selections and model validations.
Skills you'll gain
Data Transformation, Statistical Modeling, Statistical Methods, Regression Analysis, Exploratory Data Analysis, Statistical Analysis, Statistical Inference, R Programming, Linear Algebra, Predictive Modeling, Correlation Analysis, Verification And Validation, Mathematical Modeling, Plot (Graphics), and Data Validation
What you'll learn
Skills you'll gain
Regression Analysis, R Programming, Statistical Modeling, Data Validation, Mathematical Modeling, Statistical Analysis, Statistical Hypothesis Testing, Probability, Probability Distribution, Predictive Modeling, and Statistical Inference
What you'll learn
Skills you'll gain
Bayesian Statistics, Statistical Inference, Numerical Analysis, Regression Analysis, Simulations, Data Analysis, Statistical Software, Statistical Methods, Probability Distribution, Sampling (Statistics), R Programming, Statistical Modeling, Statistical Programming, Probability, and Markov Model
What you'll learn
1. Apply appropriate techniques for generating insights from data.
2. Present actionable solutions with confidence to the business stakeholders.
Skills you'll gain
Data Mining, Regression Analysis, Classification And Regression Tree (CART), Python Programming, Decision Tree Learning, Data Analysis, Feature Engineering, Statistical Modeling, Machine Learning, Exploratory Data Analysis, Data Cleansing, Analytics, Data Manipulation, Machine Learning Algorithms, Scikit Learn (Machine Learning Library), Statistical Analysis, Data Science, and Data Visualization
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Build toward a degree
This Specialization is part of the following degree program(s) offered by Illinois Tech. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
Instructors
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Frequently asked questions
No, it’s not required—but it is recommended that you follow the course sequence listed on the specialization landing page. This order is designed to help you build your skills progressively, from foundational concepts to more advanced topics.
No, this specialization is open to all MOOC learners. You do not need to be an admitted degree-seeking student to complete the specialization and receive a Coursera–IIT co-branded non-credit certificate.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
More questions
Financial aid available,