Our Graduate Level 6 Diploma in Data Science is aimed at individuals who want to develop a deep understanding of data science concepts, techniques, and tools. This diploma program focuses on the application of data science methods and practices to address complex problems and real-world challenges. It prepares students for a career in data-driven industries such as finance, healthcare, marketing, technology, and much more. The diploma program focuses on the advanced concepts and techniques used in data science, including statistical analysis, machine learning, data mining, data visualization, and predictive modelling. It will also cover topics such as big data analytics, natural language processing, deep learning, and cloud computing.
Start Date: You can start this course any day of the year, it is an online course, and we enrol students on a daily basis.
Accreditation:UK Education Bridge.
Course Duration: 4-7 months, depending on your lifestyle, We have no problem with how fast or slow you want to complete the course. The course is valid for 12 months, so you can submit your assignments at any time during the 12-month period.
Course Fee: The fee for this course is £177, which covers everything you need to complete this course, including a certificate and transcript. There are no other charges.
Course Credits: This course carries 120 credits. It will appear on your transcripts.
Who can apply for this course? Anyone with an interest can apply for this course, you do not have to be in the UK to apply for this course.
Course Contents
Course Contents
Advanced Statistics: In-depth study of statistical concepts and techniques used in data analysis, including hypothesis testing, regression analysis, and experimental design.
Machine Learning: Exploration of various machine learning algorithms and techniques for data classification, clustering, regression, and reinforcement learning.
Data Mining: Techniques for extracting useful patterns and insights from large datasets, including association rule mining, clustering, and outlier detection.
Data Visualization: Methods for visually representing data to communicate insights effectively, including the use of charts, graphs, and interactive dashboards.
Predictive Modeling: Techniques for building models that can predict future outcomes based on historical data, such as regression models, decision trees, and ensemble methods.
Big Data Analytics: Introduction to handling and analyzing large-scale datasets using distributed computing frameworks like Hadoop and Spark.
Natural Language Processing: Techniques for processing and understanding human language, including text classification, sentiment analysis, and language generation.
Deep Learning: Exploration of deep neural networks and their applications in areas like image recognition, natural language processing, and speech recognition.
Cloud Computing: Introduction to cloud platforms and technologies for scalable data storage, processing, and deployment of data science applications.
Data Ethics and Privacy: Consideration of ethical and legal issues related to data science, including privacy protection, bias mitigation, and responsible AI practices.
Duration
Duration
4–7 months, depending on how quickly the students can submit their assignments.
Entry Requirements
Entry Requirements
Progression
Progression
After completing the course, students will be awarded the Graduate Level 6 Diploma In Data Science.
Career Path
Career Path
Course Delivery
Course Delivery
This course is delivered via our online Learning Portal. All course materials are available online.
Payment Options
Payment Options
There is a number of ways you can pay your fees. We accept bank transfer, Sterling cheques, Sterling Bank drafts, Master Card, Debit Card payments, Paypal and Western Union.
Tutor Support
Tutor Support
Once a student is registered, we will assign a UK-Based tutor to guide the student through out his/her studies. The tutor will be available via email and via Virtual Learning Environment. The tutor will guide and support the student till the given assignments are complete and submitted.
