Data Science Institute
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Register for the Postgraduate Diploma in Data Science through The Data Science Institute. This a postgraduate level credit rated qualification carrying 120 credits on the UK qualifications framework.
This diploma programme is divided down into 10 modules delivered via our online platform including scheduled live class groups, practice assignments based on real world examples.
Assessment: Assessment by technical exams and projects based on real world scenarios. You choose the projects under the guidance of your course mentors and draw on the full range of skills and knowledge gained on the programme. Through your project portfolio you will be able showcase your job readiness to employers.
Duration: 6 months to complete depending on either full time or part time basis. You will need to devote your time to studying the course content in depth, attend online group sessions, work with your mentors, carry out tasks and project work and take exams during the course.
- Live online group sessions
- Industry experts
- One-to-one mentoring,
- Project support
- Mobile ready Learning platform
- 100+ video lessons
- Detailed lecture slides
- Case studies
- Practical activites
Developed at a masters degree level, the Data Science Institute's online data science course enables you to gain skills in maths, statistics and programming in R, Python and SQL to organise, analyse and visualise data to uncover hidden solutions that challenge traditional business assumptions and produce entirely new operating and strategic models. The projects you do as part of the course will allow you to apply Data Science to a specialist field, including Fintech, the Pharmaceutical industry, IoT, Economics or Marketing.
Exploratory Data Analysis
Programming in Python, R and SQL
Measures of central tendency and variation
Principles of statistical inference
Analysis of variance (ANOVA)
Fundamentals of Predictive Modelling
Predictive modelling principles
LInear regression models
Python and R packages for predictive modelling
Advanced Predictive Modelling
Time Series Analysis
Time Series concepts
ARIMA, ARCH, GARCH modelling
Panel data regresssion
Unsupervised Multivariate Methods
Principal Component Analysis
Machine Learning 1
Support Vector Machines
K nearest neighbours
Machine Learning 2
Text Mining and Natural Language processing
Structured and unstructured data
Text mining in R and Python
Natural language processing
Data Science in Practice
Presentation and communication skills
Synthesis of data science knowledge
Application to real world data and scenarios
Who is this course for?
This course is for both experienced data professionals and graduates from other disciplines looking to develop a a career in data science, AI and analytics.
An undergraduate degree or equivalent in any discipline.
Other professional qualifications at level 6 in a numerate discipline such as accounting, finance, IT, computing.
Candidates without a degree but with at least three years relevant experience may also apply
Graduates of this programme will find opportunities in data science, data analytics, business analysis and statistics. Sectors include banking and finance, insurance, pharmaceuticals, consulting and education
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