Artificial Intelligence and Computer Science BSc

  • Categoria do post:Generative AI

Computer Science with Artificial Intelligence with a Foundation Year BSc Hons 2023 24 Entry Birmingham City University

ai engineer degree

You will gain experience in web-based technologies that enable the implementation of multi-layered and interactive information visualisations, supported through lab work that introduces specific features of these technologies. The topic can be any area of the subject which is of mutual interest to both the student and supervisor, but should involve a substantial software development component. If you want to learn how to design and implement your own interactive information visualisation, you should also take the linked module G53IVP (Information Visualisation Project). To address the issue of efficiency we cover the use of mathematical descriptions of the computational resources needed to support algorithm design decisions. The emphasis is upon understanding data structures and algorithms so as to be able to design and select them appropriately for solving a given problem.

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This online artificial intelligence programme will give you the skills needed to develop, design and evaluate intelligent systems for a wide range of purposes. You will study topics such as machine learning in practice, deep learning and natural language processing, that will equip you with the practical skills and programming techniques needed to succeed within this complex field. In this year you learn about theories of mind and techniques for generating intelligent behaviour.

Career support

The computer science curriculum includes highly sought-after skills in cyber security, software design, object-oriented programming, databases, and web application development. The topics on artificial intelligence are machine learning, and machine learning operations. In the second year, you will consolidate your learning with four computer science modules and two artificial intelligence specific modules.

Topics include database management systems architecture, data modelling and database design, query languages, recent developments and future prospects. Mathematical reasoning underpins many aspects of computer science and this module aims ai engineer degree to provide the skills needed for other modules on the degree programme; we are not teaching mathematics for its own sake. Topics will include algebra, reasoning and proof, set theory, functions, statistics and computer arithmetic.

What you’ll study

This online artificial intelligence programme can lead to a wide range of careers in IT, particularly with respect to the design and development of intelligent systems. Job roles may include data scientist, AI developer, AI consultant, machine learning engineer, research scientist and information strategy manager. The course operates on a modular basis with all of your study modules being worth 30 academic credits (our preferred size in order that you move rapidly from the basics to being an expert at the end of any module you study). Total study time includes scheduled teaching, independent study and assessment activity. All students take a total of 120 credits per level and 360 credits for the degree as a whole.

Can an average student become AI engineer?

However, with the right training, practice, and dedication, anyone can learn and become proficient in AI engineering. It requires a strong foundation in computer science, knowledge of machine learning algorithms, proficiency in programming languages like Python, and experience in data management and analysis.

You will spend five hours per week in tutorials, lectures and computer classes. Our staff are research active and experts in their field; their knowledge and expertise directly inform our curriculum and the content delivered to students. The increasing capture of data by companies and organisations is driving demand for graduates able to analyse, transform and explore data to meet the needs of businesses. Discussing options with specialist advisers helps to clarify plans through exploring options and refining skills of job-hunting.

Programme Fees

When not attending lectures, seminars and other timetabled sessions, we encourage you to continue learning independently through self-study. In this module you will develop your skills and understanding of Tokenisation, Stemming, and Segmentation, and Maximum Entropy Models, Semantics, Text classification and Neural Network Architectures for NLP. The module content covers topics such as convolutional neural networks, recurrent neural networks, sequential networks, transformers and their applications. Work-based learning module placements are normally one day a week for either one or two terms depending on the number of credits available from the module. Designed to fill a skills gap and meet a growing need for talented graduates, our BSc (Hons) Artificial Intelligence degree is supported by the Intel AI Academy.

We will use the process calculi to model and reason about complex systems, studying both its formal semantics and its many uses, via a number of examples. From May of the year of entry, formal programme regulations will be available in our Programme Regulations Finder. Through a two hour lecture ai engineer degree each week, you’ll be introduced to concepts and techniques for software testing and will be given an insight into the use of artificial and computational intelligence for automated software testing. You’ll also review recent industry trends on software quality assurance and testing.

In addition, graduates with knowledge of artificial intelligence and machine learning are become more sought after as more industries seek to introduce these techniques into their product lines, design and manufacturing processes. Holders of the Apolytirion of Lykeion with a minimum overall score of 18+/20 plus 2 GCE A levels will be considered for entry to the first year of our undergraduate degree programmes. The Apolytirio + 1 A level may be considered at the discretion of departments, if high grades and required subjects are offered. You will be taught by staff who are passionate about student learning and development. The programme team are specialists in computing and active researchers in areas including artificial intelligence, machine learning, intelligent systems, mobile computing and distributed systems. Academic staff are regular contributors to conferences and journals, engaging with the wider business and academic environment in disseminating knowledge and delivering impact.

The annual fee for your course includes a number of items in addition to your tuition. If an item or activity is classed as a compulsory element for your course, it will normally be included in your tuition fee. Spending time abroad during your degree is a great way to explore different cultures, gain a new perspective and experience a life-changing opportunity that you will never forget. The aim of this module is to set out a strong theoretical basis for the analysis and design of concurrent, distributed and mobile systems.

This module will provide you with an introduction to digital media technology and will allow you to explore technology-driven change in the media industry. International and part-time students can apply online as normal using the links above. This course includes project work that requires you to develop and produce a portfolio or collection. You’ll be expected to provide the materials for use in your individual major projects; costs will vary depending on the materials selected. EU/EEA and Swiss students who have settled or pre-settled status under the EU Settlement Scheme may be eligible to apply for financial support. Irish nationals can ordinarily apply to Student Universal Support Ireland (SUSI).

ai engineer degree

Following the Foundation Year, the first year of the BSc (Hons) Computer Science with Artificial Intelligence course equips you with a solid foundation in key topics in Computer Science and introduces artificial intelligence. Your practice is supported by presentations, seminar discussions of key topics and ideas, and collaborative practices with other students in the school or faculty. After this year, you will have covered a broad range of topics in Computer Science that will upskill you to understand the key industrial skills and prepare you to take advanced topics in the subsequent years. This module aims to prepare students to apply modern machine learning techniques to solve various real-world challenges as well as exploring state-of-the- art deep learning technology. This self-contained module will introduce conventional machine learning methods and new deep neural network development.

In this module, you will explore the full data mining lifecycle, from data pre-processing and exploratory data analysis to the application and evaluation of supervised and unsupervised machine learning algorithms. Through practical, hands-on workshops using Python and Microsoft Azure Machine Learning, you will gain experience at using machine learning and data mining tools and techniques to extract https://www.metadialog.com/ insights from data. The degree provides a firm grasp of the science underpinning computer and software systems. Modules include Artificial Intelligence Applications, Natural Computing and Machine Learning. You will gain practical experience of developing systems using the latest technologies and techniques, as well as exposure to the latest trends that will shape the future of computer science.

  • Students are assessed through a combination of assessment methods depending on the modules chosen.
  • The primary focus is on building a working application, and so existing strong programming ability is required.
  • This module will provide insight into some of those techniques, algorithms and their development through history.
  • You will gain experience with cutting-edge tools such as Deep Neural Networks (DNN), Recurrent Neural Networks (RNN), and Deep Reinforcement Learning (Deep RL), via regular exercises and practical labs.
  • You will also study data analysis techniques, including causal inference, correlation, classification, regression, and clustering.

While some people are concerned about what that means for their jobs, AI holds great potential for anyone who chooses to study it. Even the most advanced tools still need people to design and look after them, and with a degree in AI, one of those people could be you. We also have many open access areas where students can study together and even hire out laptops for use in these spaces and others within the university. Birmingham City University is a vibrant and multicultural university in the heart of a modern and diverse city. We welcome many international students every year – there are currently students from more than 80 countries among our student community. Knowledge and understanding are acquired though a mixture of formal lectures, tutor-led seminars and practical activities, with other independent learning activities at all stages.

ai engineer degree

Most of our graduates go into the field of IT/Computing, followed by Financial Services, some undertake further study (eg PhD) and others go straight into industry (for example working for IBM, BAE Systems). Get a taste of university-level study on one of York’s free short courses, including our subject course, ‘Intelligent systems’. For more information about tuition fees, any reduced fees for study abroad and work placement years, scholarships, tuition fee loans, maintenance loans and living costs see undergraduate fees and funding. This module covers some of the essential skills and knowledge which will help you to study independently and produce work of a high academic standard which is vital for success at York. SQA applicants who are eligible for our Widening Participation programmes are encouraged to participate in one or more of these programmes, including Summer School, to support your application and the transition to higher education.

ai engineer degree

Speculation about the potential for AI to replace humans in the workplace has gone on for many years, but given its rapid development, it is understandable that concern is increasing. Voice-activated assistants such as Alexa and Siri can articulately answer questions in seconds. Facial recognition technology is used to secure phones, laptops and bank accounts. Self-parking vehicles, meanwhile, can make life easier for even the most experienced drivers.

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Take one of our four-year MComp degrees and you can participate in Genesys as part of your course. Genesys was the first student-led software development organisation in the UK and will give you the opportunity to gain real industrial experience with a great deal of personal responsibility. This module provides you with an understanding of the significance of projects as an instrument of business success in engineering organisations. You will learn a range of project management tools, techniques and methodologies throughout the project life cycle. You will develop skills in defining, planning, delivering, and controlling engineering projects. You will also learn the roles and responsibilities of people within engineering projects and understand how to manage teams in engineering projects.

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By familiarising yourself with the main areas of AI that are already being used in industry you will be primed to push this learning even further. With each module acting as a building block that allows you to work towards a themed research project. You will appreciate the growing demand for AI in the world and would seek to use these skills to further your career in this exciting and expanding area. Ideally, you will be a Computing graduate with strong programming skills and a solid background in mathematics. The module aims to strengthen students’ skills in data technologies ranging from database and data warehousing to Big Data. First, it will provide students with good understanding of database concepts and database management systems in reference to modern enterprise-level database development.

Is AI engineering hard?

AI engineering can be challenging to study due to its multidisciplinary nature, which combines concepts from computer science, mathematics, statistics, and domain-specific knowledge. It requires a solid foundation in programming, algorithms, machine learning, and deep learning.