The later sessions are project based and will focus on developing end-to-end analytical solutions in the following areas: Finance and trading, blockchains and crypto-currencies, image recognition, and video surveillance systems. The University of Chicago's rigorous two-year Master of Science in Computational Analysis and Public Policy (MSCAPP) program is among the first in the US. We study bias in algorithms, machine learning, and artificial intelligence. The UIC Business Master of Science in Business Analytics program is designed to prepare you to meet the growing demand for business analytics professionals by providing an education based on data analysis and technology that integrates functional applications from accounting, finance and marketing. MScA is committed to staying current by engaging projects withand drawing instructors fromtechnologically savvy businesses in the Chicagoland region, one of the countrys top hubs for data-intensive industries and forward-thinking companies. 75% of students found a new job by the time they graduated. This course covers the analytics research process from the translation of business problems into researchable questions that can be addressed by using analytics, development of data sources to address each key researchable issue, to the translation of research results back to business implications. . This course teaches students how to approach Big Data and large-scale machine learning applications. Restricted to MScA students completing the 12-course program curriculum. 100 Units. Analytics Practicum. Teams submit the report to the program as well as the client partner and present their findings in the MScA Capstone Showcase at the end of the quarter. The methods that belong to this class include liner programming, quadratic programming and mixed-integer programming. Winter MScA Electives (subject to instructor availability): *Optional core courses may be taken as electives. Master's Program in Computer Science (MPCS) The Masters Program in Computer Science (MPCS) offers a comprehensive and professionally-oriented computer science education that combines the foundations of computer science with the applied and in-demand skills necessary for careers in technology. University of Cincinnati's 100% . This course concentrates on the following topics: Review of statistical inference based on linear model, extension to the linear model by removing the assumption of Gaussian distribution for the output (Generalized Linear Model), extension to the linear model by allowing a correlation structure for the model residuals (mixed effect models), and extension of the linear model by relaxing the requirement that inputs are combined linearly (nonparametric regression, regime switches). Students who complete this tutorial course will acquire skills to be able to take further studies in Big Data and Text Analytics course. Spring By completing this course, students will gain an understanding of the motivations behind data collection and analysis methods used by marketing professionals; learn to evaluate and choose appropriate web analytics tools and techniques; understand frameworks and approaches to measuring consumers' digital actions; earn familiarity with the unique measurement opportunities and challenges presented by New Media; gain hands-on, working knowledge of a step-by-step approach to planning, collecting, analyzing, and reporting data; utilize tools to collect data using today's most important online techniques: performing bulk downloads, tapping APIs, and scraping webpages; and understand approaches to visualizing data effectively. **Optional core courses may be taken as electives. We couple academic theory and business knowledge with practical, real-world application. It has influenced our political life and generated enormous corporate profit. Spring Data science and analyst jobs are among the most challenging to fill, taking five days longer to find qualified candidates than the market average. Combining specializations in business . Prerequisite(s): Required Prerequisites: MSCA 31009: Machine Learning & Predictive Analytics Are there limits to its commercial and public policy use? Instructor(s): Gizem AydinTerms Offered: Autumn 30% of employers provide tuition assistance. This course will focus on professional development needs of the data scientist as they work to advance in their career through this masters program. In the area of credit risk, students at the end of the course should be able to: Understand the business problems and their challenges in the consumer credit risk analytics, design and apply analytical approaches tailored to each problem, and identify and address the underlying assumptions in the designed approaches. MSCA31015. A transformative graduate degree that will expand your horizons, advance your leadership, and prepare you for what's next. Furthermore, students get exposure to state-of-the-art MLOps platforms such as allegro (https://allegro.ai/), xpresso https://abzooba.com/xpresso-ai), Dataiku (https://www.dataiku.com/), LityxIQ (https://lityx.com/), DataRobot (https://www.datarobot.com/), AWS Sagemaker (https://aws.amazon.com/sagemaker/), and technologies such as gitHub, Jenkins, slack, docker, and kubernetes. MSCA32009. The following career data is compiled from a quarterly survey answered by our students: The MScA program offers dedicated guidance to students on their career journey, from internships to full-time positions, through a variety of resources: The program provides the training and develops the skill set required to solve complex problems at the intersection of statistics, computer science, and business expertise. Students will also learn the statistical programming language used to construct examples and homework exercises. Master of Science focused in Data Analytics from The Quinlan School of Business, Loyola University Chicago.Skilled in Analytics techniques such as data mining, time-series forecasting, applied . The Division of the Biological Sciences and the Pritzker School of Medicine, Master of Science Program in Analytics-Online, Master of Science Program in Computer Science, Master of Science Program in Financial Mathematics, Master of Science Program in the Physical Sciences, Committee on Computational and Applied Mathematics, The William B. and Catherine V. Graham School of Continuing Liberal and Professional Studies, The University of Chicago Booth School of Business, The Pritzker School of Molecular Engineering, The Irving B. Harris Graduate School of Public Policy Studies, The Crown Family School of Social Work, Policy, and Practice, Program structure, courses, requirements, and application, Location: Gleacher Center and Cityfront Center (NBC Tower), Full-time: weekdays, weekday evenings, and Saturday classes available, Part-time: weekday evenings and Saturday classes available, Only courses with a grade of B- or better will count toward degree requirements, One transcript from each prior academic institution, Satisfy English language proficiency requirement, Foundational Skills courses (non-credit courses, 4 6 depending on test waivers), Based on results of a linear algebra pre-test, students may also be required to take the following non-credit course, Linear Algebra (online course required prior to program start). The first step is by letting students manage and solve a real data science project with real clients and real problems. Spring MSCA31000. Recommended: MSCA 37011 Deep Learning & Image Recognition. Designed for professionals with backgrounds in technical fields who want to become data scientists. Hadoop Workshop. Summer During the course students will gain hands-on expertise leveraging Hive, Pig, Python and PySpark for Big Data applications in client-server environment. 100 Units. Moreover, with its foundations rooted in statistics, psychology, and computer science, data visualization shows you how to better understand the data, present clear evidence of your findings to your intended audience and tell engaging data stories through charts and graphics. Mark Oreglia; Program Description *Please note: The program will not be accepting applications for Autumn 2023 entry. 000 Units. Applicants who attended an international university must also: 12 courses curriculum (Academic Year 2022-23 entering students). Statistical Analysis Review. Programs tailored to your company's needs and timeframe. Linear Algebra and Matrix Analysis. Instructor(s): Yuri BalasanovTerms Offered: Autumn This course focuses on modern data visualization technologies, tools, and techniques to convert raw data into actionable information. Analytics Master of Science Physical Sciences Anthropology Master of Arts Program in the Social Sciences Ph.D. Social Sciences Anthropology and Sociology of Religion Master of Arts Master of Arts in Religious Studies Ph.D. Divinity Art History Master of Arts Program in the Humanities Ph.D. Humanities Astronomy and Astrophysics Students who complete this introductory course should be able to write and execute simple Python scripts and take further studies in Big Data and Text Analytics course. The course also addresses the importance of quality control and reproducibility when conducting research and developing work product. MSCA32017. Capstone Project Writing. A comprehensive knowledge of time series analysis is essential to the modern data scientist/analyst. (Data Science for Algorithmic Marketing) This course focuses on data science methods and algorithms for that are used to develop marketing strategies, and create a link between marketing, customer behavior and business outcome. Innovative technologies such as open source projects MapReduce, Hadoop, Spark, Storm, Kafka, TensorFlow, H2O, etc. Winter Prerequisite(s): MSCA 31000: Introduction to Statistical Concepts 100 Units. The curriculum provides a strong foundation in the areas of applied statistics, geospatial applications, and data visualization, but balanced with traditional core subjects in public affairs. Students should also understand how to harness the powerful dynamics of a team to achieve excellence in the world of data analytics. Topics are illustrated by data analysis projects using R. Basic familiarity with R is a requirement. This course focuses on marketing science methods and algorithms. Supply Chain Optimization. This class explores Data Science methodologies used within the Fintech industry. * Students may take 18 months for a summer internship. MSCA32018. The course contains large number of interactive demonstrations, workshops with examples through which the lecturer shares his own hands-on experience with the students. 2 years. allowed us to look at depths of data unseen before. Second, data analysis methods had to be reviewed, selected and modified to work in distributed computational environments like combinations of in-house clusters of servers and cloud. Our program supports every stage of the recruitment cycle for internships and full-time careers; while placement is not guaranteed, the majority of our students receive job offers within one to three months of completing the program. 100 Units. Prerequisite(s): MSCA 31007: Statistical Analysis. This course in advanced data mining will provide a practical, hands-on set of lectures surrounding modern predictive analytics and machine learning algorithms and techniques. Winter MSCA31003. It methodically builds up the learner's experience from the level of simple python statements and expressions to writing succinct, efficient and fast Python expressions and package the code in methods and classes.