Overview
Overview
Course Summary:
Data Science and Big Data Analytics are exciting new areas that combine scientific inquiry, statistical knowledge and computer programming. Organizations are turning to customer data in order to innovate and respond quickly to shifts in the market. Meanwhile, Governments are using data to help guide policy decisions, making this a prime area for social scientists with an interest in quantitative methods.
This course aims to provide an introduction to the quantitative analysis of data, blending classical statistical methods with recent advances in computational and machine learning. You will cover key topics such as the challenges of analyzing big data using statistical methods, and how machine learning and data science can aid in knowledge generation and improve decision-making.
Course Syllabus :
• Data acquisition, processing, conversion and storage
• Normalising data
• Data management using SQLite
• Intermediate level Python
• Probability distributions, modelling and experimental design
• Social network analysis
• Data visualisation
Entry Requirement :
There are no formal entry requirements for this qualification, however A levels or equivalent preferably in physics / maths subjects with some experience will be ideal to start a data science course. Students with existing knowledge of one or more of the above units with be considered for Recognition of Prior Learning.
Assessment :
Each learner will be assessed by way of multiple choice questions at the end of the course. The candidates will also be required to create a portfolio of evidence which may include data science projects to demonstrates achievement of required knowledge of the subject.
The course is a part of continuous professional development of the candidates who are working in the related areas.
Progression :
Candidates can progress to next level of data sciences course or equivalent management qualifications.
Duration:
Duration of the course is appx 200 hours / 3 months.