Team Edition For Database Professionals Day 2017
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Concentration in Database & Knowledge Management . Python Dict Switch Keys Values Quotes. The course concludes with an overview of basic network security and management concepts.
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Prereq: MET CS 2. This course may not be taken in conjunction with MET CS 4. MET CS 5. 35. Only one of these courses can be counted towards degree requirements. Students gain extensive hands- on experience using Oracle or Microsoft SQL Server as they learn the Structured Query Language (SQL) and design and implement databases. Restrictions: Only for MS CIS. This course may not be taken in conjunction with MET CS 4. MET CS 5. 79. Only one of these courses can be counted towards degree requirements.
System feasibility; requirements analysis; database utilization; Unified Modeling Language; software system architecture, design, and implementation, management; project control; and systems- level testing. Students learn how to identify information technologies of strategic value to their organizations and how to manage their implementation. The course highlights the application of I. T. CS 7. 82 is at the advanced Masters (7. IT systems at the level of CS 6. Systems Analysis and Design. Students who haven't completed CS 6.
Prereq: MET CS 6. It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, applets, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, interfaces, creating user interfaces, exceptions, and streams. Upon completion of this course the students will be able to apply software engineering criteria to design and implement Java applications that are secure, robust, and scalable. Prereq: MET CS 2. MET CS 3. 00 or Instructor's Consent. Not recommended for students without a programming background.
It includes a detailed discussion of programming concepts starting with the fundamentals of data types, control structures methods, classes, arrays and strings, and proceeding to advanced topics such as inheritance and polymorphism, creating user interfaces, exceptions and streams. Upon completion of this course students will be capable of applying software engineering principles to design and implement Python applications that can be used in conjunction with analytics and big data. Prerequisite: MET CS 2. Fundamentals of Information Technology or MET CS 3.
Foundations of Modern Computing or instructor's Consent. Not recommended for students without a programming background. Please refer to the MET CS Academic Policies Manual for further details. In addition to the MS in Computer Information Systems core curriculum (2.
Database Management & Business Intelligence must also satisfy the following requirements: MET CS 5. Quantitative Methods for Information Systems Summer . The first part of the course introduces the mathematical prerequisites for understanding probability and statistics. Topics include combinatorial mathematics, functions, and the fundamentals of differentiation and integration.
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The second part of the course concentrates on the study of elementary probability theory, discrete and continuous distributions. Prereq: Academic background that includes the material covered in a standard course on college algebra or instructor's consent. The topics include data preparation, classification, performance evaluation, association rule mining, and clustering. We will discuss basic data mining algorithms in the class and students will practice data mining techniques using data mining software. Students will use Weka and SQL Server or Oracle. Prereq: MS CS Prerequisites: MET CS 5. There is extensive coverage of SQL and database instance tuning.
Students learn about the advanced object- relational features in DBMS such as Oracle, including navigational query, BLOBs, abstract data types, and methods. Prereq: MET CS 5.
MET CS 6. 69; or instructor's consent. This course utilizes Oracle scenarios and step- by- step examples. The following topics are covered: security, profiles, password policies, privileges and roles, Virtual Private Databases, and auditing. The course also covers advanced topics such as SQL injection, database management security issues such as securing the DBMS, enforcing access controls, and related issues. Prereq: MET CS 5. MET CS 6. 69; or instructor's consent. It describes logical, physical and semantic foundation of modern DW infrastructure.
Students will create a cube using OLAP and implement decision support benchmarks on Hadoop/Spark vs Vertica database. Upon successful completion, students will be familiar with tradeoffs in DW design and architecture.
Prereq: MET CS 5. MET CS 6. 69 and either MET CS 5. MET CS 5. 21. Or instructor's consent. Programming in C# encompassing the following topics: Device I/O handling, . NET Framework application development classes such as window forms, splitters, views, controls, dialogs, resources, such as menus, tool bars, bitmaps, and status bars.
Custom controls, visual inheritance, SDI, MDI, and extending the Visual Studio . NET interface. File I/O for reading and storing binary and textual information. Data services for manipulating SQL- databases using ADO. NET. Graphics Services (GDI+) for 2.
D- vector graphics, imaging, and text rendering, including the new features of gradients, anti- aliasing, double buffering techniques, zooming, off- screen image processing and rendering. Utilizing idle time processing, timers, and threading for building responsive GUI applications. Laboratory course. Prereq: MET CS 3. MET CS 3. 42; or instructor's consent. At the end of the course you can expect to be able to write programs to model, transform and display 3- dimensional objects on a 2- dimensional display.
The course starts with a brief survey of graphics devices and graphics software. Attributes of the primitives are studied as well as filtering and aliasing. Hierarchical graphics modeling is briefly studied. The graphics user interface is introduced and various input functions and interaction modes are examined. This is followed by 3- d transformations and the 3- d viewing pipeline.
The course ends with a study of algorithms to detect the visible surfaces of a 3- d object in both the object space and the image space. Laboratory Course. Prereq: MET CS 2. MET CS 3. 41 or MET CS 3. Or instructor's consent. Starting with an introduction to probability and statistics, the R tool is introduced for statistical computing and graphics. Different types of data are investigated along with data summarization techniques and plotting.
Data populations using discrete, continuous, and multivariate distributions are explored. Errors during measurements and computations are analyzed in the course. Confidence intervals and hypothesis testing topics are also examined. The concepts covered in the course are demonstrated using R.
Laboratory Course. Prereq: MET CS 5. Topics include simple linear regression, multiple regression, logistic regression, analysis of variance, and survival analysis.
These topics are explored using the statistical package R, with a focus on understanding how to use and interpret output from this software as well as how to visualize results. In each topic area, the methodology, including underlying assumptions and the mechanics of how it all works along with appropriate interpretation of the results, are discussed. Recommended Prerequisite: MET CS 5. The course covers theoretical background on probabilistic methods used for financial decision making and their application in number of fields such as financial modeling, venture capital decision making, operational risk measurement and investment science.
Number of financial applications and algorithms are being presented for portfolio risk analysis, modeling real options, venture capital decision making, etc. The course concludes with algorithms for financial risk assessment and presents the security concepts and challenges of financial information systems.
SQL Server Central. Microsoft SQL Server tutorials, training & forum.
It can be a daunting job to ensure that the whole team has the latest database build when there is a proliferation of copies, and the database is big. Phil illustrates a solution by taking a set of Redgate tools to show how they can be used together, via Power. Shell, to build a database from object- level source, stock it with data, document it, and then provision any number of test and development servers with the database build, taking care to save any DDL changes to the existing copies of the database.