Tuition Fee
USD 25,875
Per course
Start Date
Medium of studying
On campus
Duration
12 months
Details
Program Details
Degree
Masters
Major
Data Analytics | Data Science
Area of study
Information and Communication Technologies
Education type
On campus
Timing
Full time
Course Language
English
Tuition Fee
Average International Tuition Fee
USD 25,875
Intakes
| Program start date | Application deadline |
| 2023-10-06 | - |
| 2024-01-15 | - |
About Program
Program Overview
Our MSc Data Science and its Applications is a conversion course, designed for students with only a little prior experience of university-level mathematics and statistics, who want to be part of our fast-growing digital economy (students with no exposure to university-level mathematics may consider our MSc Applied Data Science ). This course will place you at the core of data science, with the application of theory and methods to real-world problems, including the use and exploitation of big data. At Essex, the techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society and are the basis of growth of the economy and success of businesses. The course introduces you to programming with the R language and as well as text analytics. Relational databases and SQL are developed and used for relevant applications from humanities, life sciences, linguistics, marketing and social science. The course encourages statistical thinking by data visualisations and guides you to develop your creativity within a scientific framework. You cover topics such as:
- Modelling experimental data
- Machine learning and decision making
- Applied statistics
- Combinatorial optimisation
- Statistical methods
- Stochastic processes
- We are international leaders in data science education for the digital industry.
- We offer you access to specialist research facilities such as the UK Data Archive and our Institute for Social and Economic Research (ISER), both located on campus.
- We have active links with industry to broaden your employment potential and placement opportunities.
Our expert staff
Today’s data scientists are creative people who are focused and committed, yet restless and experimental. We are home to many of the world’s top scientists, and our staff are driven by creativity and imagination as well as technical excellence. We conduct world-leading research in areas such as artificial intelligence, explorative data analysis, machine learning, classification and clustering, evolutionary computation, data visualisation and financial forecasting. Specialist staff at Essex working on data science across our departments include:- Dr Yanchun Bao – longitudinal and survival analysis, causal methods, instrumental methods (Mendelian Randomization), covariance modelling, mediation analysis
- Professor Luca Citi – machine learning, learning from biological signals and data (EEG, etc)
- Professor Edward Codling - animal movement and dispersal, random walks and diffusion, path analysis of movement data, behaviour of animal groups, human crowd behaviour
- Dr Stella Hadjiantoni – estimation of large-scale multivariate linear models and applications, numerical methods for the development of recursive regularisation and machine learning algorithms, numerical linear algebra in statistical computing and data science, numerical methods for handling high-dimensional data sets
- Dr Andrew Harrison – bioinformatics, big data science
- Professor Berthold Lausen – biostatistics, classification and clustering, data science education, event time data, machine learning, predictive modelling
- Dr Osama Mahmoud – biostatistics, data science, machine learning, Mendelian Randomization
- Dr Yassir Rabhi – mathematical statistics, mathematical foundations of data science
- Professor Abdel Salhi – optimisation mathematical programming and heuristics (evolutionary computing, nature-inspired algorithms, the Strawberry Algorithm), numerical analysis data mining (big data) bioinformatics
- Dr Dmitry Savostyanov – high-dimensional problems, tensor product decompositions
- Dr Alexei Vernitski – machine learning in mathematics; reinforcement learning applied to knot theory; mathematical education, and in particular, increasing motivation of learners of mathematics
- Dr Spyros Vrontos – actuarial mathematics and actuarial modelling
- Dr Jackie Wong Siaw Tze – Bayesian estimation, MCMC methods
- Dr Xinan Yang – approximate dynamic programming, Markov decision process
Specialist facilities
- All computers run either Windows 10 or are dual boot with Linux
- Software includes R, Python, SQL, Hadoop and Sparc
- We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors
- Collaborate with the Essex Institute of Data Analytics and Data Science (IADS) and the ESRC Business and Local Government (BLoG) Data Research Centre of the University of Essex
- The UK Data Archive and the Institute for Social and Economic Research (ISER) at Essex contribute to our internationally outstanding data science environment
Your future
With a predicted shortage of data scientists, now is the time to future-proof your career. A successful career in data science requires you to possess truly interdisciplinary knowledge and our staff ensure that you graduate with a wide-ranging, yet specialised, set of skills in this area. Data scientists are required in every sector, carrying out statistical analysis or mining data on social media. Our graduates are highly sought after by a range of businesses and organisations and find employment in financial services, scientific computation, decision making support and government, risk assessment, statistics, education and other areas. Our recent graduates have gone onto work as data scientists and data analysts in both the private and public sectors. We also offer supervision for PhD, MPhil and MSc by Dissertation. We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.See More
