Ugc Net Computer Science Syllabus 2022 Pdf Download

Cambridge IGCSE Computer Science helps learners develop an interest in computational thinking and an understanding of the principles of problem-solving using computers. They apply this understanding to create computer-based solutions to problems using algorithms and a high-level programming language. Learners also develop a range of technical skills, and the ability to effectively test and evaluate computing solutions.

We revise our qualifications regularly to make sure that they continue to meet the needs of learners, schools and higher education institutions around the world and reflect current thinking. Please see the 2023-2025 syllabus document for full details on the changes.

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Please note that if you make an entry for the A*-G grading scale, it is not then possible to switch to the 9-1 grading scale once the entries deadline has passed. If you find that you have accidentally made an entry for the A*-G syllabus, you must withdraw and re-enter before the entries deadline.

We provide a wide range of support so that teachers can give their learners the best possible preparation for Cambridge programmes and qualifications. For teachers at registered Cambridge schools, support materials for specific syllabuses are available from the School Support Hub (username and password required).

Computer science is a fast-moving field that brings together disciplines including mathematics, engineering, the natural sciences, psychology and linguistics. Our course provides you with skills highly prized in industry and for research.

You take four papers, including three compulsory Computer Science papers - covering topics such as foundations of computer science (taught in OCaml), Java and object-oriented programming, operating systems, digital electronics, graphics, and interaction design - and the Mathematics paper from Part IA of Natural Sciences.

You choose from a large selection of topics which allows you to concentrate on an area of interest to you, such as computer architecture, applications (including bioinformatics and natural language processing) or theory. New topics inspired by current research interests include computer architecture, data science and robotics.

All students also work on a substantial project demonstrating their computer science skills, writing a 10,000-12,000 word dissertation on it. Projects are often connected with current Cambridge research and many utilise cutting-edge technology.

The fourth year is designed for students considering a career in academic or industrial research. You explore issues at the very forefront of computer science and undertake a substantial research project.

Students, regardless of specialization, are required to fulfill their computer science upper level course requirements from at least 3 areas. Courses that fall within each area are listed in the General Track degree requirements. The five areas are: Area 1: Systems, Area 2: Information Processing, Area 3: Software Engineering and Programming Languages, Area 4: Theory, Area 5: Numerical Analysis.

With the Data Science, Artificial Intelligence and Blockchain booming, the syllabus for Computer Science Engineering in NON - HIGH profile colleges is not updating and thus puts the engineers graduating at risk of not getting jobs. Infact, I feel the courses in colleges should be more aligned to the job you want to pursue because that is all needed for you to get a job and be satisfied what you learnt was useful, for e.g.

AP Computer Science A is an introductory college-level computer science course. Students cultivate their understanding of coding through analyzing, writing, and testing code as they explore concepts like modularity, variables, and control structures.

Based on the Understanding by Design (Wiggins and McTighe) model, this course framework provides a description of the course requirements necessary for student success, with a focus on big ideas that encompass core principles, theories, and processes of the discipline. The framework also encourages instruction that prepares students for advanced computer science coursework and its integration into a wide array of STEM-related fields.

At the Khoury College of Computer Sciences, we are inspired by an increasingly interconnected society, informed by a rapidly changing job market, and focused on addressing the challenges of a complex world. Our goal is to equip students with knowledge as diverse as it is deep. Our programs provide a strong technical foundation and an essential understanding of computing concepts while integrating computer and data sciences across disciplines and industries.

Our research-driven doctoral programs offer students an opportunity to engage in exciting projects, a vibrant community, and a challenging curriculum that offers breadth and depth in areas both within computer science and across disciplines throughout Northeastern University.

Khoury College of Computer Sciences and the Department of Electrical and Computer Engineering jointly offer an interdisciplinary Master of Science program in data science. This program is designed to give students a comprehensive framework for reasoning about data. Students will engage in extensive coursework intended to develop depth in data collection, storage, retrieval, manipulation, visualization, modeling, and interpretation. Students will also be able to choose elective courses from a variety of offerings in Khoury, the College of Engineering , and throughout the campus to explore areas that generate data or specialized data science applications. Students in the MS program in data science will complete a capstone course, working with real-world data and applying what they have learned during the program. Successful program graduates will be well positioned to attain data scientist and data engineer positions in a fast-growing field or to progress into doctoral degrees in related disciplines.

Students in the Align MS-DS program come from a variety of backgrounds, where they merge their existing knowledge with data science skills. Students will learn theoretical foundations and gain extensive experience with practical problems in the discipline, including data acquisition, storage, analysis, probabilistic modeling, model deployment, and presentation.

The Master of Science in Robotics program, offered jointly by the College of Engineering and the Khoury College of Computer Sciences at Northeastern, looks at this fundamentally interdisciplinary field from three connected angles: mechanical engineering, electrical engineering, and computer science.

The postbaccalaureate certificate is designed to give students a solid foundation in the mathematical and theoretical underpinnings of computer science, including the areas of discrete mathematics, basic programming, data structures, object-oriented programming, algorithms, and computer systems. The goal of the certificate is to provide foundational knowledge in computer science that is valuable in both the workplace for career advancement as well as to those looking to move into graduate programs within the discipline.

Computers and the programs they run are among the most complex products ever created; designing and using them effectively presents immense challenges. Facing these challenges is the aim of computer science as a practical discipline, and this leads to some fundamental questions:

The theories that are now emerging to answer these kinds of questions can be immediately applied to design new computers, programs, networks and systems that are transforming science, business, culture and all other aspects of life.

We are looking for students with strong mathematical ability, which you will develop into skills that can be used both for reasoning rigorously about the behaviour of programs and computer systems, and for applications such as scientific computing.

Common roles for graduates include computer programmer, software designer and engineer, financial analyst and scientific researcher. According to figures compiled by The Times, our students earn an average of 52,000 straight out of university.

Students who have completed courses on core curriculum subjects as part of their undergraduate degree program or have relevant work-related experience may request permission from the Department of Computer Science to replace the corresponding core courses with graduate-level computer science electives. Please refer to the MET CS Academic Policies Manual for further details.

Students majoring in computer science may elect a thesis option, to be completed within 12 months. This option is available to MS in Computer Science candidates who have completed at least seven courses toward their degree and have a grade point average (GPA) of 3.7 or higher. Students are responsible for finding a thesis advisor and a principal reader within the department. The advisor must be a full-time faculty member; the principal reader may be part-time faculty with a PhD (unless waived by department).

The Concentration in Computer Networks offers a broad foundation of information technology, along with an in-depth exploration of computer data communication and modern networking. The computer networks concentration provides a comprehensive examination of network design and implementation, network performance analysis and management, network security, and the latest networking technology. The program is designed to empower students with extensive hands-on experience in order to analyze, design, procure, manage, and implement cutting-edge computer networking solutions and technologies.

Data AnalyticsThe Concentration in Data Analytics will explore the intricacies of data analytics and expose students to various topics and tools related to data processing, analysis, and visualization. Students will learn probability theory, statistical analysis methods and tools, generating relevant visual presentations of data, and concepts and techniques for data mining, text mining, and web mining. Individuals who complete this program will have a solid knowledge of concepts and techniques in data analytics as well as a solid exposure to the methods and tools for data mining and knowledge discovery in addition to the broad background in the theory of practice of computer science from the core courses. 006ab0faaa