k 12 science curriculum

Students will learn how to evaluate the strategic environment, the strategic models that might be useful for their organization, and the implementation of a strategy. In the following years, students take advanced topics courses and seminars. In recognition of the significant disruptions caused by COVID-19, the Department of Statistics is not accepting GRE or General GRE scores for applications received for the academic year starting in Fall 2021. The course serves as the capstone project for the MSAA degree. Students are assumed to have had no previous exposure to statistics. Business decisions that leverage anomaly detection, which used to require intense human resource and capacity can now be completed in a short time through versatile models and automation. To explore the Python data analysis platform, we will focus on IPython (Interactive Python) and Jupyter Notebook. What are the business factors that influence decisions about how research is undertaken? The course assumes no prior programming experience with Python. In this course, students will learn how to find these unusual occurrences in the data. Online AAS in Technical Studies. Online: Every term. The purpose of this course is to learn programming concept and Object Oriented fundamentals using Java. Applied analytics is about the strategic use of data and analytics to inform decisions within an operating environment. Based on the context, these outliers can be detrimental and result in loss of resources, and time through errors, fraud, manipulation of stocks, and other such malicious activities. Completing this course will give you a fundamental basis for understanding ALM in financial organizations and further prepare you to apply these concepts in real-life situations under both generally accepted accounting principles (GAAP) and market consistent approaches. Find the latest information SPS's plans for the Spring and University resources. Research Interests: Statistical machine learning algorithms used for inference and optimization in applications such as communications and compressed sensing. This course is designed for individuals who currently work or plan to work as insurance and financial professionals such as actuaries, traders, and quants. Beginning in Summer 2019, the Capstone Project: Solving Real-World Problems with Analytics will be taught in fully online format only. Columbia University For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. Critically analyze ethical issues in accounting practices and discuss critical accounting theory and processes. To receive approval, the internship must: Provide an appropriate opportunity for students to apply course concepts, Fit into the planned future program-related career path of the student. The course further introduces neural networks and other specialized analytics frameworks. Students will learn the characteristics, conditions and dynamics of various large-scale collaborations, as well as how to design and lead them effectively. Our Python Programming certificate program is a great option if you have less experience. Additionally, you will be introduced to the concepts of value-based management and economic value of liabilities. This course will provide an overview of life insurance company structure, life insurance products, product development and pricing considerations, investments and the regulations and liabilities that drive life insurance company decisions. The following approved electives are available both face-to-face and online. By the end of the semester students will be able to: Perform fundamental analysis ("bottoms-up," firm-level, business and financial analysis). It is highly recommended that domestic students complete at least 12 credits prior to completing an internship. Together, we will manipulate large size data sets to extract meaning and generate visualizations. With the growth of the Internet in recent decades, there has been an exponential increase of unstructured textual data available from news and social media. The role of databases in data analytics cannot be overstated; databases facilitate efficient, secure and accurate information storage and retrieval across multiple users and platforms. It is the primary factor of input into regulatory reporting, business analytics, product innovation and process automation. This course will train students in a technology that is seen as an essential part of a data analyst's toolkit. The course also guides students in analyzing use cases, developing business cases, and designing high-level IOT architectures for analytics solutions that can drive business value. If you want to go far, go together." For your elective study, you will align the foundational skills you've developed in the two core areas with three courses you choose that are pertinent to your academic and professional goals. In addition, if studying on a student visa, you must enroll full-time (12 credits per term) and study on campus. can take more than 80% of the team’s time and resources, often forcing them to rush through the analyses in order to produce results. IPython is an enhanced interactive Python terminal specifically designed for scientific computing and data analysis; Jupyter Notebook is a graphical interface that combines code, text, equations, and plots in a unified interactive environment. Inherent in the concept of scalability are the notions of "appropriate scale" and also "at scale." This course serves as a foundational course in the Applied Analytics program. Advanced Analytics Capstone Course This course will study how companies map risks and set aside capital to provide for the uncertainties above and beyond those provided for by standard reserves, including an introduction to evolving uses of predictive analytics and enterprise risk management by insurance companies. By the end of this course students will understand: How to apply fundamental corporate finance tools to analysis of firms’ strategic financial decisions. Knowledge-Driven Digital Product Innovation: Idea to Profitability. Graduates! The course focuses on data and analytics within operational functions of different kinds of organizations across a range of industry sectors, and the overall ecosystem within which they operate. Data is a representation of “real things” within organizations (i.e. In the following years, students take advanced topics courses and seminars. This course introduces general principles of ratemaking and reserving as they relate to P&C insurance products. The first year of the program is devoted to training in theoretical statistics, applied statistics, and probability. And many organizations are challenged to stay the course in the face of operational disruption and conflicting stakeholder requirements. Students will learn actuarial conventions and terminology and structure insurance data accordingly. Additionally, students will be exposed to NoSQL database systems optimized for big data analytics and the techniques necessary for interacting with massive amounts of data. Fan, J., Feng, Y., Jiang, J. and Tong, X. Linda S. L. Tan, Aik Hui Chan, and Tian Zheng, 116th Street and Broadway, New York, NY 10027, Statistics: Undergraduate Course Schedule 20-21 Academic Year, Virtual Exam Planning Worksheet – AY20/21, Applied Probability and Risk Seminar Series, Pfizer/ASA/Columbia University Symposium on AI in Clinical Drug Development, Search: Lecturer in Discipline Position Starting Fall 2021, Congratulations to Professor Samory Kpotufe for being named a 2021 Sloan Fellow, New Book by Professor Demissie Alemayehu, Emir Birol and Michael Gaffney “Interface between Regulation and Statistics in Drug Development” available on Amazon, Congratulations! Assignments will give students the opportunity to use their technical and analytical skills while understanding the real world applications that will be important to their future professional work as planners, policymakers, advocates, architects, designers, and/or environmentalists. Integration projects such as business intelligence efforts, data lakes, and master data initiatives, require a consistent holistic view of concepts such as Customer, Account, and Product. Students who enrolled in the program prior to fall 2018 are required to follow the fall 2017–spring 2018 curriculum. Though one of the first assignments in this course will have students author their own set of learning objectives, students can also expect that after completing this course they will be able to: Discuss the application of program content and theory in a professional context (LO1), Define a plan for assessing and building their professional competencies (LO2), Describe an organization’s culture and assess their cultural “fit” (LO3), Make recommendations for the types of behaviors, structure, and culture they would want to see in a future workplace setting (LO4). Building upon the tools and foundational concepts from Frameworks and Methods I, this course introduces analytic techniques to handle less traditional forms of data, as well as more specialized analytic techniques to help organizations dig more deeply and comprehensively to create value from their data. Supervised learning techniques are being extensively used to make useful predictions and generate insights to tackle problems. Class sessions encompass a set of topics including purpose, planning, success measurement, and implementation of knowledge management initiatives and organizational learning techniques. 2970 Broadway, MC 4119 By the end of the course, students will be able to: In this course, students will gain an overview of major concepts of management and organization theory, concentrating on understanding human behavior in organizational contexts, with a heavy emphasis on the application of concepts to solve managerial problems. What are the key questions that strategic decision makers need to formulate and answer in order to inform their decisions? Columbia University For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. Data ownership and accountability are hard to implement. This course provides students with foundational context for managing data so that it can be leveraged and used with confidence. As technology and the network economy drive businesses to compete under continuously accelerating rates of change in technology, business leaders must incorporate knowledge management and learning into their organization’s activities in ways that support and propel their business goals. Research design provides both a coherent framework for collecting relevant evidence and strategies for evaluating that evidence. Negotiation is one of the most important strategies in conflict resolution and is used routinely by all humans to resolve conflict and potential conflict successfully. Working in teams with faculty, students critically assess a company’s data challenges and Students will review some of the most important academic research and business publications on change management and the implementation of analytics. In this course, students will develop analytical skills used to formulate and implement marketing-driven strategies for an organization. The statistics topics and examples have been chosen for their special relevance to environmental problems, including applications in environmental monitoring, impact assessment, environmental valuation techniques and econometric analyses of sustainable development. Machine Learning (Columbia University via edX) Columbia University’s Machine Learning is a relatively new offering that is part of their Artificial Intelligence MicroMasters on edX. Students have the opportunity to explore and create conceptual, logical, and physical data models. This course teaches cutting-edge tools and methods that drive investment decisions at quantitative trading firms, and, more generally, firms applying machine learning to big data. Great managers of analytic projects are more than mere data users; they are key decision makers and strategic owners in the underlying data processes. How to research consumer behavior and pricing strategies. This course takes students through the lifecycle of an analytical project from a communication perspective. As the starting point of the two-part Frameworks and Methods sequence, the course guides students through the data-wrangling process, starting with data exploration and other foundational approaches. In addition, certain federal taxation and reporting rules may apply. Add to address book Permanent link to this profile Students will be exposed to all the pressures and demands of real world start-ups by participating on teams tasked with creating deliverables required to launch a new business. To be successful in the field will require an understanding of these rules, reporting requirements, taxation rules and the government agencies (Internal Revenue Service, Department of Labor and Pension Benefit Guarantee Corporation) responsible for oversight of such arrangements. This leads to another important aspect of actuarial science, which is risk analysis and risk management. The course builds on concepts introduced in several of the program’s core courses and emphasizes the application of theories. This course will enable students to build advanced supervised and unsupervised machine learning models to find these anomalies. This course will expose students to foundational data principles, governance processes and organizational prerequisites needed to overcome challenges to ensure data quality. This course introduces the fundamental laws and principles governing businesses in the U.S. today. Advantages and disadvantages of various traditional pricing and reserving techniques will be discussed as well as classification of insureds and other important topics. Anomaly detection helps in the early detection of critical outliers in a system. Congratulations! Students will work extensively with case study projects. Students will work in a combination of conceptual and experiential activities, including case studies, discussions, lectures, simulations, videos, and small group exercises. Though it is newer and doesn’t have a large number of reviews, the ones that it does have are exceptionally strong. Please note that it is not permissible to enroll while in B-1/B-2 status. Students will be provided hands-on experience in multiple contexts with complex datasets that they must further manipulate through industry-specific data engineering. Students explore the motivations, obstacles and interventions of change, and learn to build alliances, facilitate difficult meetings and develop a transformation plan. It consists of over 200 chapters organized in six functional series: Agency Organization and Legal Affairs, Programming, Acquisition and Assistance, Human Resources, Management Services, and Budget and Finance. The world is generating data at an ever faster pace, including through business transactions, online searches, social media activities, and a variety of sensors. In recent years, machine learning techniques have made significant impact in a wide range of application areas in various industries. This course--the third in the sequence of analytics leadership core courses—is about changing the behavior and the culture of organizations, with particular emphasis on how to successfully introduce the methods and results of analytics. Prior to this, I did my Ph.D.... New Book by Professor Demissie Alemayehu, Emir Birol and Michael Gaffney “Interface between Regulation and Statistics in Drug Development” (Chapman & Hall/CRC Biostatistics Series) available on Amazon... Congratulations to our 2020 Ph.D. Construct a cash flow statement, balance sheet and decipher a 10K report. Which analytical methods might be helpful in answering the research question? There are many legacy repositories and business functions to unravel. This course will expose you to the data principles, governance processes and organizational prerequisites needed to manage data as a strategic asset – so that it can be leveraged and used with confidence. ... Carsten Chong This will include exploring various types of product designs. Blockchains have created a new paradigm in secure yet decentralized information management among various entities without requiring trusted intermediaries. The class will look at case studies from different cities around the world as well as New York City's efforts through PlaNYC while introducing the principles underlying sustainability indicators-including greenhouse gas inventory protocols-and how they are used to influence and shape policies and decisions, and will offer students hands-on experience with these tools. Establish professional interpersonal relationships, Corporate governance, compliance and ethics, Contracts, mergers and acquisitions and business transactions, Corporate finance - capital raising, IPOs. Before registering for this course, students must secure an appropriate graduate-level internship, complete the Internship Application Form and receive approval from the academic program.

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