Introduction To Computing Using Python An Application Development Focus Pdf Download __EXCLUSIVE__
Perkovic's Introduction to Computing Using Python: An Application Development Focus, 2nd Edition is more than just an introduction to programming. It is an inclusive introduction to Computer Science that takes the pedagogical approach of "the right tool for the job at the right moment," and focuses on application development. The approach is hands-on and problem-oriented, with practice problems and solutions appearing throughout the text. The text is imperative-first, but does not shy away from discussing objects early where appropriate. Discussions of user-defined classes and Object-Oriented Programming appear later in the text, when students have more background and concepts can be motivated. Chapters include an introduction to problem solving techniques and classical algorithms, problem-solving and programming and ways to apply core skills to application development. This edition also includes examples and practice problems provided within a greater variety of domains. It also includes case studies integrated into additional chapters, providing students with real life applications using the concepts and tools covered in the chapters.
introduction to computing using python an application development focus pdf download
Perkovic's Introduction to Programming Using Python provides an imperative-first introduction to Python focusing on computer applications and the process of developing them. The text helps develop computational thinking skills by covering patterns of how problems can be broken down and constructively solved to produce an algorithmic solution. The approach is hands-on and problem oriented. The book also introduces a subset of the Python language early on to help write small functions. Chapters include an introduction to problem solving techniques and classical algorithms, problem-solving and programming and ways to apply core skills to application development.
Q# is hardware agnostic, meaning that it provides the means to express and leverage powerful quantum computing concepts independently of how hardware evolves in the future. To be useable across a wide range of applications, Q# allows you to build reusable components and layers of abstractions. To achieve performance with growing quantum hardware size, the Q# quantum programming language ensures the scalability of both applications and development effort. Even though the full complexity of such computations requires further hardware development, Q# programs can be targeted to run on various quantum hardware backends in Azure Quantum.
This course introduces students to the fundamentals of developing native applications for Apple platforms such as iOS. Students will learn details of Apple mobile platforms and programming languages and develop programs using Apple specific development environments. Emphasis will be placed on building apps intended for distribution on phones or tablets.
As an introduction to relational database management systems and database programming for computers using modern enterprise database servers, this course covers fundamental concepts in database design, database modeling techniques, and Structured Query Language (SQL) programming techniques while providing hands-on exercises in which students apply these concepts and techniques to real-world problems. The course introduces the Structured Query Language (SQL database language), Data Manipulation Language (DML), Data Definition Language (DDL), Data Control Language (DCL), and store procedure programming. It also includes concepts for building frameworks for high performance web applications in multi-tier environments. Students will implement a relational database from initial requirements and conceptual design (ER Diagram) to the physical database in a modern enterprise relational database management system (RDMS).
This course exposes students to the ideas of web application development using server-side programming languages. Concepts such as dynamic web page creation, authentication, database integration, security, and data processing will be covered. Students will apply these concepts to solve real-world problems by building functioning web-based applications that can be accessed via a web browser.
This course provides an introduction to System Analysis and Design. Topics include analyzing the business case, requirements modeling, data and process modeling, and development strategies, with an increased focus on object modeling and project management. Students will also learn about output and user interface design, data design, system architecture and implementation, and system operation, support, and security.
This course teaches the fundamental concepts of cloud computing using hands-on, lab-based exercises. Students will learn to provision servers using automation tools, develop and deploy web applications to cloud-based services and to virtualized infrastructure. Students will be presented with a survey of existing cloud providers and infrastructure and will plan the deployment of an application as a final project.
The goal is to introduce students to modern and extremely useful topics in computational statistics. It focuses on computational aspects and provides a hands-on introduction to fundamental concepts of data analysis. The course offers a foundation for further courses in data mining, machine learning, artificial intelligence, robotics, computer vision, and in general in computational statistics and scientific computing.
This is an introductory course in database management systems (DBMS) and file management systems. The course covers data modeling concepts, various file management techniques, data definition and manipulation using SQL, issues in data management, development and implementation of database applications, and a perspective on emerging issues in database systems. Students work in the Lab on various assignments including prototyping and SQL, utilizing state of the art DBMS and CASE tools. NOTE: (1) Duplicate Course: No credit for students who have completed CIS 4331 (0331). (2) Prior to fall 2016, the course title was "Database and File Management Systems."
This course emphasizes component-based software development using a modern object-oriented programming (OOP) language (currently C#). Students are introduced to software development techniques applicable in a component (class)-based, integrated software development environment (IDE). Students will learn (and practice using) the OOP language, object-oriented software design techniques, and the principles of good user interface design. Students will also learn how to navigate in, and take full advantage of, an IDE in building quality software, including user interfaces to databases, sequential files, and graphics tools. Object-oriented concepts such as inheritance, polymorphism, static and dynamic binding, and interface (abstract class) components will be covered. The primary focus is on windows-based software products, but the use of ASP.NET for client-server systems development is also introduced. NOTE: (1) Duplicate Course: Students may not get credit for both CIS 4309 and 3309. (2) For Information Science and Technology Majors.
The objective of this course is to teach the principles and development of multi-tiered distributed systems. It is introduced with a basic review of internet communications and the architecture of client and server sites, including the functions of and relationships among the browser, web server, operating and file systems, middle-ware, database server, and application servers. Concepts involving various types of client/server side processing and remote connectivity methodologies are reviewed, including scripting languages, HTML, Dynamic HTML, XML, ASP, CGI, and DCOM. About 30% of the course is devoted to the above-described theory. The remainder of the course will be devoted to putting some of these principles and techniques into practice using the DCOM technology. A series of progressively sophisticated problems will be studied and programmed in the lab. NOTE: For Computer Science Majors.
This course will expose students to recently emerged and fast moving technology of big data and cloud computing. It will cover a spectrum of topics from core techniques in data management and analysis to highly-scalable data processing using parallel database systems. Students will be introduced to big data ecosystems such as Hadoop, Spark, Storm and MapReduce; cloud technologies such as Amazon EC2, Microsoft Azure and Google Cloud; data management tailored to cloud and big data such as NoSQL, Google Big Table/Apache HBase, and introductory applications to big data and cloud environment. Students will work directly with a selected set of these platforms, compare and contrast their relative strengths and weaknesses, and characterize the problems they are designed to solve. Note: Students may not receive credit for both CIS 4517 and CIS 5517. 350c69d7ab