Statistical Methods for Computer Science

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

• Gain proficiency in advanced statistical techniques and probability models for complex data analysis
• Develop practical skills in simulation methods, network analysis, and probabilistic graphical models
• Master hypothesis testing, regression analysis, and network modeling to extract insights and support innovation

• Basic familiarity with probability and statistics concepts
• Readiness to engage in applied exercises and case studies