Computer Science (Artificial Intelligence) with an Industrial Placement Year (2023)

Computer Science (Artificial Intelligence) with an Industrial Placement Year (1)

Department of Computer Science

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Explore this course:

    You are viewing this course for 2023-24 entry.

    Key details

    • A Levels AAA; AAB
      Other entry requirements
    • UCAS code GG75
    • 4 years / Full-time
    • September start
    • Accredited
    • Find out the course fee
    • Industry placement

    Course description

    Computer Science (Artificial Intelligence) with an Industrial Placement Year (2)

    Our degrees will help you to become more than just a programmer - you will also develop skills in teamwork, communication, systems design and entrepreneurship.

    This course is about biologically inspired algorithms, their relationship to living biological intelligence and the nature of consciousness itself.

    Some modules overlap with the main Computer Science degree, so you get the same solid grounding in the fundamentals. You can specialise in speech recognition, language processing or learn about robotics.

    You'll also have the chance to arrange a year in industry. This will put your academic studies into context, improve your skills and enhance your employment prospects. As well as being paid a salary during your placement you will pay reduced tuition fees for that year.

    This course is accredited by the British Computer Society. The courses fully meet the requirements for Chartered Information Technology Professional and partially meet the requirements for Chartered Engineer.

    Computer Science (Artificial Intelligence) with an Industrial Placement Year (4)

    Modules

    A selection of modules are available each year - some examples are below. There may be changes before you start your course. From May of the year of entry, formal programme regulations will be available in our Programme Regulations Finder.

    Choose a year to see modules for a level of study:

    Title: Computer Science (Artificial Intelligence) with a Year in Industry BSc (nee Artificial Intelligence and Computer Science with a Year in Industry) course structure
    UCAS code: GG75
    Years: 2022, 2023

    First year

    Core modules:

    Introduction to Software Engineering

    This module introduces the Software Engineering concepts that are needed to develop software systems that can meet basic functional requirements within a given problem domain. It covers the main steps in the process of developing such systems, from requirements analysis through to their implementation and testing. A major part of the module involves students working in teams to develop a web-based software system, which gives practical experience in teamwork and managing software projects and their products.

    20 credits

    Foundations of Computer Science

    The course consists of (around) 10 blocks of 2-3 weeks work each. Each block develops mathematical concepts and techniques that are of foundational importance to computing. Lectures and problem classes will be used. The intention is to enthuse about these topics, to demonstrate why they are important to us, to lay the foundations of their knowledge and prepare students for future computing courses. It is not expected that the course will cover ALL of the maths that is needed later either in terms of depth or scope.

    20 credits

    Java Programming

    This module introduces programming concepts through the Java programming language. Program design and the use of testing to drive program creation are also covered. Initial focus is placed on the structured aspects typical of many programming languages: the ideas of a sequence, selection and repetition. The object-oriented approach to building large software systems from components is then presented. Throughout the module, emphasis is placed on the practice of writing well-structured and readable programs to solve problems.

    20 credits

    Machines and Intelligence

    This module provides an introduction to Artificial Intelligence, and to key concepts and problems in the field, such as whether a computer is capable of understanding, and whether humans should themselves be viewed as machines. It also provides a brief historical overview of the subject and reviews the state-of-the-art and open questions in some of the major sub-areas of AI, pointing out connections to research work in the Department. As well as providing a first encounter with the main issues that underlie attempts to create Artificial Intelligence, the module also has a more practical component that introduces algorithms and data structures for AI problem solving through practical programming examples, as well as hands-on experience with simple programming of robots. The emphasis here is on identifying the abstract nature of the problem that is to be solved, matching this to an appropriate algorithm or technique and implementing a solution. It also serves as an introduction to programming for research rather than for software engineering.

    20 credits

    Devices and Networks

    This module runs throughout the academic year, starting in Autumn and ending in Spring. The module consists of two parts. In the first, important elements of computer architecture are covered including digital logic, computer arithmetic and instruction set architecture. The approach in the module is to show how the basic elements of a computer are constructed and combined to give sophisticated architectures that support accelerated performance via cache memory and pipelining. The second half of the module shows how computing devices can be connected into networks, and covers the principles of layered protocols, error detection/correction and reliable transmission over networks.

    20 credits

    Web and Internet Technology

    This module is for students studying Computer Science as a main subject. The Web and the Internet are now pervasive in modern life, providing an information resource, and promoting novel, interactive solutions to computing-related activities. The main focus of the module is on practical use of HTML, CSS and JavaScript in front-end development of interactive websites. As part of this, the module covers responsive web design, accessibility and legal issues when creating websites and an introduction to information security.

    10 credits

    Introduction to Algorithms and Data Structures

    Algorithms and algorithmic problem solving are at the heart of computer science. This module introduces students to the design and analysis of efficient algorithms and data structures. Students learn how to quantify the efficiency of an algorithm and what algorithmic solutions are efficient. Techniques for designing efficient algorithms are taught, including efficient data structures for storing and retrieving data. This is done using illustrative and fundamental problems: searching, sorting, graph algorithms, and combinatorial problems such as finding the shortest paths in networks.

    10 credits

    Global Engineering Challenge Week

    The Faculty-wide Global Engineering Challenge Week is a compulsory part of the first-year programme. The project has been designed to develop student academic, transferable and employability skills as well as widen their horizons as global citizens. Working in multi-disciplinary groups of 5-6, for a full week, all students in the Faculty choose from a number of projects arranged under a range of themes including Water, Waste Management, Energy and Digital with scenarios set in an overseas location facing economic challenge. Some projects are based on the Engineers Without Borders Engineering for people design challenge*.

    *The EWB challenge provides students with the opportunity to learn about design, teamwork and communication through real, inspiring, sustainable and cross-cultural development projects identified by EWB with its community-based partner organisations.

    (Video) Harsh Reality of AI Jobs No one Tells You|

    The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption. We are no longer offering unrestricted module choice. If your course included unrestricted modules, your department will provide a list of modules from their own and other subject areas that you can choose from.

    Learning and assessment

    Learning

    Learning will be delivered through a combination of lectures, practical sessions, tutorials and seminars. You will also learn important group work skills and will have the opportunity to work with clients to solve real-world problems. As well as formal teaching you will be expected to undertake independent study.

    At the end of your third year you will submit a written dissertation and present your findings during a poster session. Your dissertation project could be supervised by one of our research staff or an external supervisor from industry.

    (Video) Computer Science: Year in Industry

    We invest to create the right environment for you. That means outstanding facilities, study spaces and support, including 24/7 online access to our online library service.

    Study spaces and computers are available to offer you choice and flexibility for your study. Our five library sites give you access to over 1.3 million books and periodicals. You can access your library account and our rich digital collections from anywhere on or off campus. Other library services include study skills training to improve your grades, and tailored advice from experts in your subject.

    Learning support facilities and library opening hours

    Our courses are designed to challenge you and prepare you for a career in industry, research, or teaching. Our inspirational staff are experts in their fields of research and we are ranked 5th out of 89 computer science departments in the UK for research excellence (REF 2014). This means what we teach you is relevant today and tomorrow.

    Assessment

    You will be assessed using a mixture of exams/tests, coursework and practical sessions.

    Programme specification

    This tells you the aims and learning outcomes of this course and how these will be achieved and assessed.

    Find programme specification for this course

    Entry requirements

    With Access Sheffield, you could qualify for additional consideration or an alternative offer - find out if you're eligible

    Standard offer

    The A Level entry requirements for this course are:
    AAA; AAB
    AAA, including Maths; AAB, including A in Maths and B in Computer Science

    A Levels + additional qualifications AAB, including A in Maths + B in a relevant EPQ; ABB, including A in Maths and B in Computer Science + B in a relevant EPQ; AAB including A in Maths + A in AS or B in A Level Further Maths; ABB, including A in Maths and B in Computer Science + A in AS or B in A Level Further Maths

    International Baccalaureate 36, with 6 in Higher Level Maths; 34, with 6 in Higher Level Maths and 5 in Computer Science

    BTEC Extended Diploma DDD in Engineering, Applied Science, IT or Computing + A in A Level Maths

    BTEC Diploma DD in Engineering, Applied Science, IT or Computing + A in A Level Maths

    T Level Distinction in the T Level in Digital Production Design and Development, including grade A in the core component + A in A Level Maths

    Scottish Highers + 1 Advanced Higher AAAAB + A in Maths

    Welsh Baccalaureate + 2 A Levels A + AA, including Maths; B + AA in Maths and Computer Science

    Access to HE Diploma Award of Access to HE Diploma in a relevant subject, with 45 credits at Level 3, including 39 at Distinction (to include 18 credits in Maths) and 6 at Merit

    Routes for mature students

    Access Sheffield offer

    The A Level entry requirements for this course are:
    AAB; ABB
    AAB, including A in Maths; ABB, including A in Maths and B in Computer Science

    A Levels + additional qualifications AAB, including A in Maths + B in a relevant EPQ; ABB, including A in Maths and B in Computer Science + B in a relevant EPQ; AAB including A in Maths + A in AS or B in A Level Further Maths; ABB, including A in Maths and B in Computer Science + A in AS or B in A Level Further Maths

    International Baccalaureate 34, with 6 in Higher Level Maths; 33, with 6 in Higher Level Maths and 5 in Computer Science

    BTEC Extended Diploma DDD in Engineering, Applied Science, IT or Computing + B in A Level Maths

    BTEC Diploma DD in Engineering, Applied Science, IT or Computing + B in A Level Maths

    T Level Distinction in the T Level in Digital Production Design and Development, including grade A in the core component + A in A Level Maths

    Scottish Highers + 1 Advanced Higher AAABB + A in Maths

    Welsh Baccalaureate + 2 A Levels B + AA, including Maths; B + AB, including A in Maths and B in Computer Science

    (Video) Studying Computer Science and Artificial Intelligence at Bath

    Access to HE Diploma Award of Access to HE Diploma in a relevant subject, with 45 credits at Level 3, including 36 at Distinction (to include 18 credits in Maths) and 9 at Merit

    Routes for mature students

    English language requirements |

    You must demonstrate that your English is good enough for you to successfully complete your course. For this course we require: GCSE English Language at grade 4/C; IELTS grade of 6.5 with a minimum of 6.0 in each component; or an alternative acceptable English language qualification

    Equivalent English language qualifications

    Visa and immigration requirements

    Other qualifications | UKand EU/international

    Pathway programme for international students

    If you're an international student who does not meet the entry requirements for this course, you have the opportunity to apply for an International Foundation Year in Science and Engineering at the University of Sheffield International College. This course is designed to develop your English language and academic skills. Upon successful completion, you can progress to degree level study at the University of Sheffield.

    If you have any questions about entry requirements, please contact the department.

    Department of Computer Science

    Computer Science (Artificial Intelligence) with an Industrial Placement Year (5)

    We're the first computer science department in the UK to launch its own student-run software company, Genesys. Choose Sheffield and you'll develop skills in programming, teamwork, communication, systems design, problem solving, and learn about current software engineering industry practices.

    Our courses are designed to challenge you and prepare you for a career in industry, commerce, research, teaching or management. Our inspirational staff are experts in their fields of research and we are ranked 5th out of 89 computer science departments in the UK for research excellence. What we teach you is relevant today and tomorrow.

    During your degree you'll work on real projects for real clients as part of core and optional modules.

    As well as lots of practical experience, we'll give you the first-rate scientific grounding you'd expect from a leading Russell Group research university. You can specialise in areas including computer security, web development and mobile apps, robotics and machine learning, speech and language technology, or 3D graphics and virtual reality.

    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.

    Your lectures, practical classes, tutorials and seminars are usually held on the University campus. The Diamond is a world-class building, home to all engineering undergraduates and where most of your practical sessions will take place. Our investment of £81m in the building and £20m for lab equipment is helping us to develop innovative teaching and learning experiences.

    Dedicated teaching staff will support you and assist your development into a computer scientist of the future. We regularly host guest lectures from industry, with recent guests including Microsoft, Google, GitHub, IBM and ARM.

    Facilities

    You will have access to cutting edge facilities in The Diamond including virtual reality facilities, high-spec graphics PCs and a robot arena. Our computer suites are equipped with the latest hardware, software and operating systems.

    Department of Computer Science

    Why choose Sheffield?

    The University of Sheffield

    A top 100 university
    QS World University Rankings 2023

    92 per cent of our research is rated in the highest two categories
    Research Excellence Framework 2021

    No 1 Students' Union in the UK
    Whatuni Student Choice Awards 2022, 2020, 2019, 2018, 2017

    Department of Computer Science

    Number 1 in the Russell Group for student satisfaction

    National Student Survey 2022

    Rated 8th nationally for the quality of our research environment

    Research Excellence Framework 2021

    (Video) Ioannis Antypas - On Tech Innovation, AI, & automation of Industrial Placement process...

    Student profiles

    Computer Science (Artificial Intelligence) with an Industrial Placement Year (6)

    Sheffield has the perfect balance between nature and city life. Jia Mei Grace Lim BSc Artificial Intelligence and Computer Science, MSc Cybersecurity and Artificial Intelligence Grace loved studying at Sheffield so much that she chose to return to do an MSc in Cybersecurity and Artificial Intelligence after successfully completing a BSc in Artificial Intelligence and Computer Science.

    Graduate careers

    Department of Computer Science

    Some of our graduates have gone on to become IT consultants, software engineers, software developers, project managers, and data scientists in companies such as Amazon, ARM, BT, Bank of America & BofA Securities, Goldman Sachs, Google, IBM, Microsoft, and Plusnet. Others have begun their research careers by starting a PhD.

    I left Sheffield not only with an excellent career perspective but also with good friends and skills for life. Laura Craciun MComp Artificial Intelligence and Computer Science Since graduating from the University of Sheffield, Laura's career has gone from strength-to-strength, and she now works as a Developer on the Pega automation platform within the Automation and Robotics domain at Vodafone UK.

    Fees and funding

    Fees

    Tuition fees

    Fee status help

    Additional costs

    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. There are also other costs which you may need to consider.

    Examples of what’s included and excluded

    Funding your study

    Depending on your circumstances, you may qualify for a bursary, scholarship or loan to help fund your study and enhance your learning experience.

    Use our Student Funding Calculator to work out what you’re eligible for.

    Visit us

    University open days

    We host five open days each year, usually in June, July, September, October and November. You can talk to staff and students, tour the campus and see inside the accommodation.

    Open days: book your place

    Subject tasters

    If you’re considering your post-16 options, our interactive subject tasters are for you. There are a wide range of subjects to choose from and you can attend sessions online or on campus.

    Upcoming taster sessions

    Applicant days

    If you've made an application to study with us, we'll invite you to one of our applicant days, which take place between November and April. These applicant days have a strong department focus and give you the chance to really explore student life here, even if you've visited us before.

    Campus tours

    Our weekly guided tours show you what Sheffield has to offer - both on campus and beyond. You can extend your visit with tours of our city, accommodation or sport facilities.

    Campus tour: book your place

    Apply for this course

    Make sure you've done everything you need to do before you apply.

    How to apply When you're ready to apply, see the UCAS website:
    www.ucas.com

    Not ready to apply yet? You can also register your interest in this course.

    Contact us

    Telephone: +44 114 222 1800
    Email: ug-compsci@sheffield.ac.uk

    Department of Computer Science

    The awarding body for this course is the University of Sheffield.

    Recognition of professional qualifications: from 1 January 2021, in order to have any UK professional qualifications recognised for work in an EU country across a number of regulated and other professions you need to apply to the host country for recognition. Read information from the UK government and the EU Regulated Professions Database.

    (Video) 5 Career Paths in Artificial intelligence

    Any supervisors and research areas listed are indicative and may change before the start of the course.

    Our student protection plan

    Terms and Conditions upon Acceptance of an Offer

    FAQs

    Is computer science with Artificial Intelligence good? ›

    Artificial intelligence is one of the fastest developing areas of computer science. It is being used in exciting new ways to enhance and evolve computer games, web search, biometric systems and many other areas of modern IT.

    What is computer science with Artificial Intelligence? ›

    Artificial intelligence is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.

    What course should I take for artificial intelligence? ›

    • Data Science.
    • Data Analytics.
    • Machine Learning.
    • Python.
    • SQL.
    • Excel.
    • AI.

    Do you need physics for artificial intelligence? ›

    Is physics required for studying artificial intelligence? No. A reasonable math background is needed and the ability to program can be helpfu. Python is very popular in the AI world.

    Is AI in computer science hard? ›

    Learning AI is not an easy task, especially if you're not a programmer, but it's imperative to learn at least some AI. It can be done by all. Courses range from basic understanding to full-blown master's degrees in it. And all agree it can't be avoided.

    Which is better it or artificial intelligence? ›

    Both the subject is equivalently good but AI has more scope . Hope this helps. For more such queries, ping us down below.

    Is artificial intelligence a good career? ›

    Extremely promising. In fact, there are more artificial intelligence jobs than skilled professionals to fill them, and the AI world has shown no signs of slowing down, so the demand is very high.

    Which country is best for artificial intelligence? ›

    Best countries to study artificial intelligence
    • Artificial Intelligence in UK.
    • Artificial Intelligence in Canada.
    • Artificial Intelligence in Germany.
    • Artificial Intelligence in USA.
    • Artificial Intelligence in Sweden.
    • Artificial Intelligence in France.
    • Artificial Intelligence in Ireland.

    What are the 4 types of AI? ›

    There are a lot of ongoing discoveries and developments, most of which are divided into four categories: reactive machines, limited memory, theory of mind, and self-aware AI.

    How long is artificial intelligence course? ›

    Tech in artificial intelligence is offered as a B. Tech Computer Science course in India. Like other B. Tech courses, this AI course is also 4 years long.

    What skills do I need to get a job in artificial intelligence? ›

    • Programming. Whatever Artificial Intelligence career you're looking to pursue developing a strong knowledge of programming languages is a key skill that you need to harness. ...
    • Database Modelling, Data Warehousing and Data Processing. ...
    • Machine Learning. ...
    • Knowledge of Intelligent User Interfaces (IUI) ...
    • Problem Solving.

    Which is the most successful field of artificial intelligence? ›

    Let us look at the top ten one by one.
    • Business Intelligence Developer. ...
    • Research Scientist. ...
    • Big Data Engineer/Architect. ...
    • Software Engineer. ...
    • Software Architect. ...
    • Data Analyst. ...
    • Robotics Engineer. ...
    • NLP Engineer.
    7 Mar 2022

    Does AI require a lot of math? ›

    In AI research, math is essential. It's necessary to dissect models, invent new algorithms and write papers.

    Is artificial intelligence all math? ›

    Yes, especially linear algebra, probability, and calculus are currently used by AI. The topics necessary are all compiled, alongside computer programming, to create AI at its core.

    Can you do AI without coding? ›

    Machine Learning without programming is occupying that space and making AI accessible for everyone. This is because you can gain Artificial Intelligence without a single line of code, whether your business is large or small. And this is closing the gap between technology experts and businesses.

    Is AI easier than data science? ›

    Data Science vs Artificial Intelligence – Key Difference

    The tools involved in Data Science are a lot more than the ones used in AI. This is because Data Science involves multiple steps for analyzing data and generating insights from it. Data Science is about finding hidden patterns in the data.

    What is the average salary of an AI engineer? ›

    The entry-level annual average AI engineer salary in India is around 8 lakhs, which is significantly higher than the average salary of any other engineering graduate. At high-level positions, the AI engineer salary can be as high as 50 lakhs.

    Should I study artificial intelligence or computer science? ›

    If you yourself interested in AI and you want to learn new things then you should choose Artificial Intelligence, else Computer Science is the safest bet. In Computer Science you have programs for everything, in some languages, which are understood by only trained professionals. This programming is called as coding.

    Does AI have a future? ›

    Artificial intelligence is shaping the future of humanity across nearly every industry. It is already the main driver of emerging technologies like big data, robotics and IoT, and it will continue to act as a technological innovator for the foreseeable future.

    Why should I study artificial intelligence? ›

    Becoming an expert in AI will enable you to challenge current ways of working and change the way you perceive most things. Highlighting yourself as someone who strives for positive change, as well as an eagerness to learn the latest technologies could take you a long way in your career.

    Is cyber security better or AI? ›

    More than 80% of people suggest cyber security as the best career choice for the future. There's always something new that you can learn about or try out in the field. New security practices and technologies keep you interested in the field for the long run.

    Which jobs will survive artificial intelligence? ›

    The list is based on my 38 years of work in AI research, products, business, and investment.
    • Psychiatry. ...
    • Therapy. ...
    • Medical care. ...
    • AI-related research and engineering. ...
    • Fiction writing. ...
    • Teaching. ...
    • Criminal defense law. ...
    • Computer science and engineering.

    Do artificial intelligence jobs pay well? ›

    AI Salary Overview

    According to Datamation, the average salary for an artificial intelligence programmer is between $100,000 and $150,000. AI engineers, on the other hand, earn an average of $171,715 with the top earners making more than $250,000.

    Is AI a difficult field? ›

    The answer is yes. As one of the leading fields in technology today, artificial intelligence can be challenging to learn. Proof that more than 90% of automation technologists admit that they feel inadequately prepared for the challenges in the future of smart machine technology.

    Which is the best place to study AI? ›

    The Best Artificial Intelligence Colleges: AI Degrees & Certificates
    RankSchoolLocation
    1Carnegie Mellon UniversityPittsburgh, Pennsylvania
    2Stanford UniversityStanford, California
    3Massachusetts Institute of TechnologyCambridge, Massachusetts
    4University of California-BerkeleyBerkeley, California
    26 more rows
    26 Sept 2022

    Where are the most AI jobs? ›

    Looking specifically at the US, we see that AI jobs are overwhelmingly concentrated in California. Its 80,238 jobs in 2021 are over twice as many as those in Texas, which had the second-highest total with 34,011.

    Who is father of AI? ›

    If John McCarthy, the father of AI, were to coin a new phrase for "artificial intelligence" today, he would probably use "computational intelligence." McCarthy is not just the father of AI, he is also the inventor of the Lisp (list processing) language.

    What type of AI is Google? ›

    Google Search is a form of narrow AI, as is predictive analytics, or virtual assistants. Artificial general intelligence (AGI) would be the ability for a machine to “sense, think, and act” just like a human.

    How many subjects are there in artificial intelligence? ›

    BTech Artificial Intelligence and Data Science syllabus is divided into 8 semesters. It focuses on key Artificial Intelligence and Data Science concepts through the study of subjects such as Data Structures & Algorithms, Software Engineering, Computer Networks, etc.

    Which subject is most important for artificial intelligence? ›

    The main research topics in AI include: problem solving, reasoning, planning, natural language understanding, computer vision, automatic programming, machine learning, and so on. Of course, these topics are closely related with each other.

    Which programming language is required for artificial intelligence? ›

    Python is the best programming language for AI. It's easy to learn and has a large community of developers. Java is also a good choice, but it's more challenging to learn. Other popular AI programming languages include Julia, Haskell, Lisp, R, JavaScript, C++, Prolog, and Scala.

    Are artificial intelligence jobs in demand? ›

    Data science, machine learning, and artificial intelligence (AI) are considered to be the most in-demand technologies used in almost every field from science, medicine, and business administration.

    Which AI skills are most in demand? ›

    NLP is crucial for AI because it allows computers to understand human language, which is essential for tasks like creating chatbots or voice assistants. CV is vital for AI because it allows computers to interpret and understand images, which is essential for tasks like object recognition or facial recognition.

    How much does a PHD in AI make? ›

    Doctor of Philosophy (PhD), Artificial Intelligence Jobs by Salary
    Job TitleRangeAverage
    Computer ScientistRange:$67k - $123k (Estimated *)Average:$91,926
    Lead Data ScientistRange:$82k - $123k (Estimated *)Average:$102,979
    Machine Learning EngineerRange:$79k - $138k (Estimated *)Average:$105,541
    4 more rows
    15 Sept 2022

    Can I do machine learning without calculus? ›

    For machine learning, the real prerequisite skill that one needs to learn is data analysis, beginners and there is no need to know calculus and linear algebra in order to build a model that makes accurate predictions.

    Is AI like a brain? ›

    AI systems are often compared to the human brain, even though they have almost nothing in common. To achieve artificial general intelligence (AGI), we tend to look to the only example of general intelligence available for humans to study: the human brain.

    How much math is required for AI? ›

    What mathematics do I need to know to launch a career in artificial intelligence? The course will cover the three main branches of mathematics used in data science and artificial intelligence: linear algebra, calculus and probability.

    What level of math is needed for AI? ›

    To become skilled at Machine Learning and Artificial Intelligence, you need to know: Linear algebra (essential to understanding most ML/AI approaches) Basic differential calculus (with a bit of multi-variable calculus) Coordinate transformation and non-linear transformations (key ideas in ML/AI)

    Is Python needed for AI? ›

    Python has proven to be one of the most efficient programming languages for AI and ML solutions. The technology transformation of AI can help in providing better outputs.

    Is Python must for AI? ›

    Python is a key part of AI programming languages due to the fact that it has good frameworks, such as scikit-learn-Machine Learning in Python that meets almost all requirements in this area as well as D3. js data-driven documents JS. It is among the most efficient and user-friendly tools to visualize.

    Which is better CSE or CSE with Aiml? ›

    If you are not sure about specialisation the taking CSE as the course is good. But if you are having special interest in AI or ML and you want to do something in AI and ML only then taking the CSE with specialisation is better. If you are not sure about specialisation the taking CSE as the course is good.

    Is a career in artificial intelligence worth it? ›

    Is Artificial Intelligence a Good Career? The field of artificial intelligence has a tremendous career outlook, with the Bureau of Labor Statistics predicting a 31.4 percent increase in jobs for data scientists and mathematical science professionals — which are crucial to AI — by 2030.

    Is studying artificial intelligence good? ›

    Studying artificial intelligence will open multiple job opportunities for a person. Moreover, the sector has a high demand for experts. Therefore, finding jobs after completing the course will not be a big worry.

    Which branch is better CSE AI? ›

    If you yourself interested in AI and you want to learn new things then you should choose Artificial Intelligence, else Computer Science is the safest bet. In Computer Science you have programs for everything, in some languages, which are understood by only trained professionals. This programming is called as coding.

    Which country is best for computer science and Artificial Intelligence? ›

    Best countries to study artificial intelligence
    • Artificial Intelligence in UK.
    • Artificial Intelligence in Canada.
    • Artificial Intelligence in Germany.
    • Artificial Intelligence in USA.
    • Artificial Intelligence in Sweden.
    • Artificial Intelligence in France.
    • Artificial Intelligence in Ireland.

    Is cyber security better than AI? ›

    More than 80% of people suggest cyber security as the best career choice for the future. There's always something new that you can learn about or try out in the field. New security practices and technologies keep you interested in the field for the long run.

    Which AI job pays the most? ›

    Among the highest paying jobs in the artificial intelligence industry, Big Data Engineers or Architects make anywhere between 12 to 16 LPA at the beginning of their journey, with plenty of scope for growth as they continue working.

    Is artificial intelligence high paying? ›

    The AI job market has been growing at a phenomenal rate for some time now. The entry-level annual average AI engineer salary in India is around 8 lakhs, which is significantly higher than the average salary of any other engineering graduate. At high-level positions, the AI engineer salary can be as high as 50 lakhs.

    Can an average student learn artificial intelligence? ›

    Yes, Artificial Intelligence is quite hard, but if you make your mind nothing is hard. It only depend to person to person, If you have interest than you will be able to make it quick. Artificial Intelligence have better future.

    How long does it take to learn AI? ›

    The truth is, it depends on a lot of factors. But if you'd like a straight answer, research has proven that it takes 10,000 hours to master any craft. So you could say this applies to machine learning as well.

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