Statistical Methods for Computer Science
About this Specialization
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.Created by: Johns Hopkins University
Related Online Courses
This capstone course in the Health Informatics Specialization will allow learners to create a comprehensive plan for an informatics intervention of their choosing, and that will demonstrate to... more
Course four of the Anthos series prepares students to consider multiple approaches for modernizing applications and services within Anthos environments. Topics include optimizing workloads on... more
This course analyzes the tax treatment, issues, planning techniques and underlying government policies involved in doing business internationally. The course incorporates concepts learned in all of... more
Embark on a transformative journey that merges Generative AI tools with PHP in the \'PHP Development with Generative AI\' project, an intermediate-level initiative that blends PHP programming with... more
This course is best suited for individuals who have a technical background in mathematics/statistics/computer science/engineering pursuing a career change to jobs or industries that are data-driven... more