Statistical Methods for Computer Science
Learn advanced statistics and probability for CS. Master modeling, simulation, and network analysis techniques.
Learn advanced statistics and probability for CS. Master modeling, simulation, and network analysis techniques.
This specialization offers comprehensive training in advanced statistical methods for computer science professionals. Through three intensive courses, students master probability theory, statistical modeling, and computational techniques. The program covers essential topics from joint probability distributions to exponential random graph models, preparing learners for real-world data analysis and decision-making. With hands-on projects using R in Jupyter Notebooks, students develop practical skills in hypothesis testing, regression analysis, and network modeling. The curriculum combines theoretical foundations with applied learning, making it ideal for both academic and industry applications.
English
Powered by
What you'll learn
Master combinatorial techniques and probability axioms, analyze discrete and continuous random variables, learn joint probability distributions and statistical inference, apply Markov chains and limit theorems, develop skills in network analysis and graphical models, implement simulation techniques using R programming, conduct advanced statistical hypothesis testing.
Skills you'll gain
This course includes:
49 Hours PreRecorded video
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 3 courses in this program
Foundations of Probability and Random Variables
Course 1 · 49 Hours to complete · 6 modules
Advanced Probability and Statistical Methods
Course 2 · 47 Hours to complete · 6 modules
Computational and Graphical Models in Probability
Course 3 · 15 Hours to complete · 4 modules
Fee Structure
Payment options
Financial Aid
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.