Here's the BIG Picture

The goal of the Data Analytics Diploma (E-Learning is to equip students with the necessary skills and abilities to thrive in a career in the field of data science and analytics, while giving them the flexibility of learning online. Students should have a variety of knowledge to help an organisation with its ability to store, process, and analyse its data.

By research, data analytics has been ranked as the top skill required for employment for the past several years. There is a bright future for data analytics graduates, as many organisations move towards analytics in cloud-supported infrastructure. The programme is ideal for those who want to start their career in data science professions in specific industries.

With this Course You Will:

• Gain essential knowledge of IT, data science and analytics, and practical skills to start a career as data analyst.
• Understand data science concepts to gather, clean, process, and transform data for better decision-making.
• Analyse and interpret data using an ethical and responsible approach.
• Apply appropriate analysis models, evaluate input quality, extract understanding from outcomes, and look into potential concerns.
• Use computing theory, languages, algorithms, mathematical and statistical models, and optimization concepts to use data analysis in the most appropriate way.
• Build communication and interpersonal skills, and gain awareness of their social and ethical responsibilities.
• Possess skills for lifelong learning and career development.

COURSE MODULES

Platform Technology

An introduction for students to computer system fundamentals, emphasizing modern operating systems and networking technology, required to support cloud architecture. It covers the following topics: operating system fundamentals; TCP/IP layered protocols; WAN and LAN networking fundamentals; internetworking and transport protocols, and fundamental computer and network security concepts, amongst others. You will also earn a microcredential from the University of Minnesota via Coursera for Campus.

Programming Fundamentals

In this module the student will gain a broader understanding of modern computer programming. The student will acquire introductory skills in problem analysis, solution design, and program construction. Through practical programming activities, the student will gain an appreciation of the nature and history of computer programming. You will also earn a microcredential from IBM via Coursera for Campus.

Mathematics for IT

Designed to develop students’ confidence with mathematical concepts and relationships, and improve their use of mathematics and statistical skills in a range of contexts, specifically problem solving and abstract thinking. Topics covered include numbers, functions and polynomials, derivatives, integrals, basic statistics and probability. You will also earn a microcredential from RICE University via Coursera for Campus.

Introduction to Data Science

This module will introduce students to Data Science principles and tools, as well as its general mindset. Students will gain the necessary knowledge to deal with various facets of data science practice, including: data collection and integration, exploratory data analysis, predictive and descriptive modelling, data product creation, effective communication, and the relevant business methodologies, amongst others. You will also earn a microcredential from IBM via Coursera for Campus.

Big Data & MongoDB

Students will learn the history and fundamentals of NoSQL databases, their key characteristics, four types of NoSQL databases, how they differ from each other, and their benefits. This course will give students hands-on experience with MongoDB database and Database-as-a-Service (DaaS) offerings. You will also earn a microcredential from IBM via Coursera for Campus.

Data Analysis & Visualisation

This subject focuses on building students' ability to understand and perform data wrangling, and exploratory data analysis using python and real world datasets. Students will be learning the Pandas DataFrame, and utilising Scikit-learn, an open-source library. The libraries allow the students to load, manipulate, analyse, and visualize datasets as well as use some of its machine learning algorithms to generate models and predictions. You will also earn a microcredential from IBM via Coursera for Campus.

Capstone Project – Data Analytics

Students will learn how to design a medium-scale technical solution through project-based learning (PBL). In this project, students will be involved in evaluating, selecting, and applying knowledge and practical skills acquired from this programme. Students can expand their skillset to construct new and improved ways of utilizing IT / computer solutions and technology to benefit society.