Statistical Methods for Computer Science

$49
ENROLL NOWCourse Overview
This Specialization is intended for students and professionals in computer science and data science seeking to develop advanced skills in probability and statistical modeling. Through three comprehensive courses, you will cover essential topics such as joint probability distributions, expectation, simulation techniques, exponential random graph models, and probabilistic graphical models. These courses will prepare you to analyze complex data structures, conduct hypothesis testing, and implement statistical methods in real-world scenarios. By the end of the Specialization, you will be equipped with the practical tools and theoretical knowledge needed to make informed decisions based on data analysis, enhancing your capabilities in both academic and industry settings. Additionally, you will gain hands-on experience with programming tools like R, which is widely used in the industry for statistical computing and graphics, making you a competitive candidate for roles that require data analysis, modeling, and interpretation skills in technology-driven environments.
Course FAQs
What are the prerequisites for 'Statistical Methods for Computer Science'?
Prerequisites for this continuing education class are set by Johns Hopkins University. Most professional development online classes benefit from some prior knowledge. Please check the provider's page for specific requirements.
Will I receive a certificate for this CE class?
Yes, upon successful completion, Johns Hopkins University typically offers a shareable certificate to showcase your new skills and fulfill your continuing education requirements.
How long does this online course take to complete?
Completion times for online continuing education courses vary. The provider's website will have the most accurate estimate of the time commitment needed.





