Higher Diploma in Data Science and Analytics

This module will get students familiar with basic statistical concepts and applications for the collection, analysis, and interpretation of data for decision-making using data.

This module is to prepare students for data preparation and ETL data from different sources and combine them into a single dataset. Students perform more machine learning concepts and algorithms and apply them for various types of analytics

This module will get the student familiar with concepts of machine learning and data mining for predictive analytics. Students learn what are the algorithms available, what they do, and how to choose the best one and apply it to their data. Students learn to make predictions with the output of the model and compare them across different models. Students will be able to apply these concepts in business applications and other fields by studying patterns in the data and using them to make predictions.

This module is to prepare students for performing tasks in the cloud. Students are introduced to the concepts of cloud computing such as data bases & storage, creating virtual servers, and security

This module is to prepare students for creating simple apps to be deployed. Students will learn how to design the interface for their apps and store and manipulate data, have logic sequences, and making decisions (logic) as well as mobile features. Students will also learn how to automate processes in-app logic.

This module will get the student familiar with concepts of IoT data for analysis. Students learn how to extract IOT data and store it in a cloud server. Students perform data extraction from IoT devices and display the data for the monitor on the web. The monitored data will be store in the cloud server. The student will learn to download data for data analysis

This module will get the student familiar with concepts of project management following closely the PMBOK syllabus. Students will grasp the concepts of project management and will benefit greatly in their business & IT undertaking. Students will know the stages of each project from start to finish and all the various disciplines of the project management lifecycle.

This module will get the student familiar with state-of-the-art visualization capabilities. Students will use BI software to visualize data for insights and analysis. Create your own calculated fields and parameters, as well as join and blend different data sources.

This module introduces students to the database which is fundamental to current business information system activities. A database typically provides features to enhance compactness, reliability, flexibility, and Internet applicability. Students will be introduced to the concepts and fundamentals of database systems. Students will be able to specify and create a database model, including the setting of various parameters that can be modified to suit different structured or unstructured data requirements, the design of data, as well as the development of mechanisms for maintenance, storage, and retrieval of data based on the business requirements. An open-source database tool is considered for verifying the features.

This module introduces students to and gives a clear understanding of how networks from in-home local area networks (LANs), to the massive and global Internet, are built and how they allow us to use computers to share information and communicate with one another.

This module introduces students to the big data capabilities of a choice of Cloud. Through a blend of lectures, presentations, demonstrations, and hands-on lab exercises, students get an overview of a choice of Cloud and a detailed view of the data processing and machine learning capabilities. This module allows the ease, flexibility, and power of big data solutions on a choice of Cloud.

This module introduces students to the main aspects of deep learning and using R-based data science basics and techniques. Students will learn to apply R frameworks to real-life data, images, etc for classification and regression applications. Students will gain concepts to understand what algorithms and methods are best suited for the data. Students will be able to use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.

This module introduces students to learn, understand, and practice big data analytics approaches, which include the study of contemporary computing big data technologies and techniques focusing on industry applications. The module emphasizes efficient handling of data of any size, develops the pragmatics of managing data, alongside retrieval and analysis of information. Mainly the module focuses on conceptualization and summarization of big data trivial data versus big data, big data computing technologies, techniques, and approaches. Students will be exploring different publicly available datasets and select suitable applications.

This module introduces students to practical knowledge and understanding of web analytics and SEO fundamentals, web reporting visualization tools, web monitoring tools, and application of information to meet business requirements. Case scenarios, examples, exercises, and hands-on practical lab tasks will be used.

This module helps students to join the dots between mathematics, programming, and business analysis. This module provides an introduction as well as hands-on experience in data visualization, visual analytics, and visual data storytelling. If learners have no prior knowledge or learners with basic math skills but want to apply them in data science or learners have good programming skills but lack math, this module bridges the gap between mathematics and programming. It introduces design principles for creating meaningful displays of quantitative and qualitative data to facilitate managerial decision-making in the field of business analytics. Students will know how to structure and streamline data analysis assignments; collect, prepare, and “wrangle” data, and highlight implications using visualizations and storytelling.