The details
Location: Online Mode of study: Part-time Qualification: Online professional course (20 credits) Study duration: 13 weeks
Start date: Awarding body: University of Essex Delivered by: Kaplan Open Learning For queries: Call +44 (0) 1206 489 358

Explore the key aspects of data science and artificial intelligence – and improve your understanding of statistical analysis – in this online professional course. 

You’ll start by investigating the key aspects of both AI and data science, before moving on to critically evaluating the range of mathematical and statistical methodology within these disciplines. Ultimately, you’ll build sound knowledge of how to interpret numerical results as part of decision-making processes. 

The course covers a range of topics, including: 

  • foundational mathematical principles and methods 
  • application of programming and data-driven techniques from both a theoretical and practical viewpoint 
  • how to present results to a diverse audience 

At the end of the course, you’ll have the opportunity to study one of our popular postgraduate computing courses. 

 

Why we’re great 

  • Build on your existing critical thinking and analytical skills.  
  • Showcase your strengths and knowledge through a course e-portfolio. 
  • Gain a recognised qualification in as little as 13 weeks, with no need for a career break. 
  • Enjoy 24/7 access to learning materials on our purpose-built virtual learning environment (VLE). 
  • Build connections with fellow students across more than 140 countries worldwide. 

You’ll study the following topics as part of the online professional course: 

  • introduction to mathematical and statistical modelling, and challenges in practical data analyses  
  • vectors and matrices 
  • differential calculus and numerical integration 
  • probability 
  • statistics, including confidence intervals, hypothesis, testing and bayes theorem 

Teaching methods 

Studying online gives you the freedom to complete your qualification when and where it suits you – at home, during your lunch hour or in a café. 

Our online professional courses are delivered through a virtual learning environment (VLE) instead of a traditional campus. This means you’ll have access to your study materials 24/7, including: 

  • multimedia lecturecasts made up of written content, short videos, animation, audio recordings, infographics, short tests and mini-assignments 
  • discussion forums for you to chat about the module content with fellow students 
  • live Q&A sessions with your tutors 
  • a comprehensive eLibrary of textbooks and academic journals 
  • support from academic staff and your dedicated Student Support team 

To ensure you receive high-quality tutor support, each class is capped at 20 students. 

 

Assessment methods 

You’ll be assessed exclusively through assignments. These include assessed discussion forums, written assignments and journal entries. 

We’re committed to providing frequent and transparent feedback in the following ways: 

  • our assessment criteria are designed to be simple and transparent 
  • you’ll always be aware of your current provisional grade, right from the start 
  • you’ll be able to clearly view your marks in your gradebook whenever you log on to the learning platform 
  • there’s a seven-day turnaround for marking and feedback of assessed work 
  • you’ll have regular contact with your Student Support team, with whom you can discuss any concerns as soon as they arise 

  

Study duration 

Our Numerical Analysis online professional course has a study duration of 13 weeks, including a one-week induction to help you settle into online study. 

The Numerical Analysis online professional course offers a whole host of opportunities. This will be beneficial whether you’re looking to climb the career ladder or take the first step into business – helping you stand out amongst the competition. 

If you wish to continue your studies and boost your prospects, you could choose additional computing online professional courses. Alternatively, you could progress onto one of the following postgraduate certificates (60 credits), postgraduate diplomas (120 credits) or full Masters degrees (180 credits): 

Please note, acceptance on to a postgraduate qualification is subject to meeting the entry requirements of your chosen programme. 

No formal qualifications or experience is necessary.  

As our courses are delivered in English, a high proficiency of English is required. If English isn’t your first language, your ability should be equivalent to an IELTS (Academic) score of 6.5. Don’t worry if you don’t hold an IELTS or equivalent qualification – we offer a free online English test to assess your proficiency.  

You don’t need to prove your English ability if you’re a national of, or have completed a qualification equivalent to a UK degree in, any of these countries. 

Full tuition fee:
£1,386 UK / £1,455 International (2024-25) Δ
 

  • Our online professional courses are fully inclusive – all teaching materials and required reading are included. 
  • Alumni discount of 10% of the tuition fee available if you’re a previous graduate with the University of Essex or University of Essex Online.   
  • 10% anniversary scholarship available when you enrol by 31 July 2024.
  • We offer a 14-day moneyback guarantee, so if you decide your course isn’t for you during the first 14 days, we’ll give you a full refund. Terms and conditions apply. 

Δ All tuition fees shown are net of any applicable sales tax payable by you in your country of residence. Where we are required to add sales tax at the local statutory rate, this will be added to the tuition fees shown and confirmed during the payment process. 

Subject specialists, industry authorities and experienced academics: the tutors who teach on our Numerical Analysis online professional course are experts in the business field.

What our students say

testimonials

Joy Ngugi -MSc Data Science

I can maintain my job while pursuing my studies, enabling me to apply new skills directly to my work and vice versa. 

With a background in computer science, I always knew I wanted to further my education with a postgraduate degree. In the fourth year of my studies, I was introduced to machine learning and this became an instant passion! Having excelled in mathematics from an early age, this solidified my decision...

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