Specialist Diploma in Business & Big Data Analytics

The NYP Professional Competency Model for the Specialist Diploma in Business & Big Data Analytics consists of:

9 Competency Units – Within each Competency Unit, skills and knowledge of different disciplines are integrated and taught holistically. This enables learners to fulfil specific work tasks upon completion.
6 Course Competencies – Each Course Competency consists of a collection of Competency Units that enables specific learning outcomes and competencies to be developed.
3 Competency Canvases – Each Competency Canvas consists of a collection of Competency Units and a Work-Integration-Unit (WIU), which is a workplace-contextualised project. Competency Canvases help learners develop and demonstrate their abilities to perform work tasks at a higher proficiency.

In this PCM-based Specialist Diploma in Business & Big Data Analytics, there are 6 Course Competencies listed as follows:

Data Visualisation & Journalism
Analytics & Computational Modelling
Applied Artificial Intelligence
Data Administration & Management
Analytics with Programming
Data Strategy & Design

These Course Competencies are aligned to SSG’s Skills Framework and provides comprehensive coverage on the knowledge and skills sought after in the Data and Artificial Intelligence sectors.

Competency Units and Work Integrated Unit exhibiting the identified course competencies will be delivered across 3 Post-Diploma Certificates (PDC) as follows:

PDC in Business Analytics
PDC in Applied Data Science
PDC in Enterprise Big Data Management

Learners will be awarded the Specialist Diploma in Business & Big Data Analytics upon successful completion of any two of the Post-Diploma Certificates.

Post-Diploma Certificate in Business Analytics

The PDC in Business Analytics aims to equip learners with the necessary business analytics skills in preparing data for analysis, applying predictive and descriptive models, and presenting analysis results using data visualisation tools.

Data Journalism
Data Preparation & Feature Engineering
Predictive Analytics & Forecasting
Business Analytics Project WIU

Data Journalism [30 hours]

Data storytelling is interactive, visually compelling and provides deep business insights. Through this CmU, learners will develop competencies in designing and developing interactive dashboards using visual mapping techniques to visualise underlying data patterns in business data. Learners will also be competent in associating related dashboards into data stories to communicate effectively with stakeholders of different cultural background to meet their diverse needs and expectations.

Data Preparation & Feature Engineering [45 hours]

Data preparation & feature engineering is the process of transforming raw data into usable format for data analysis. The quality of the data and features directly affects the ability of the model to learn. Through this CmU, learners will develop competencies in collecting data using appropriate data collection tools and techniques and perform Extract-Transform-Load (ETL) tasks from the various data source using programming to solve business problems. Learners will also be competent in discovering underlying data relationships among data variables through data exploratory analysis.

Predictive Analytics & Forecasting [45 hours]

Predictive analytics & forecasting involve the use of machine learning methods to help discover data patterns and relationships between target prediction output and input features. Through this CmU, learners will develop competencies in applying relevant predictive modelling techniques to solve business problems and meet the service expectation of the stakeholders. Learners will also be able to evaluate the accuracy and effectiveness of different predictive models using relevant metrics. Learners will be equipped with both supervised and unsupervised modelling techniques and methods to evaluate modelling results.

Business Analytics Project WIU [30 hours]

Business analytics looks at utilising insights generated from analysing historical data using machine learning techniques to improve business decisions. Through this WIU, learners will demonstrate their competencies in developing a business analytics project in teams. Learners will apply data privacy and ethical principles in the collection, use and disposal of data, and impute data format, transform, and reshape the data before applying wide range of methods and assorted mathematical processes. Learners will predict the desired business outcomes through the evaluation of the analysis results and data stories that provides an effective narrative and visual representation of their predictive analytics project.

Post-Diploma Certificate in Applied Data Science

The PDC in Applied Data Science aims to train learners in the analysis and advanced analytics of big data. It focuses on the application of methodologies and techniques for big data analytics.

Applied Deep Learning
Text Analytics & Applications
Data Science for Business
Applied Data Science Project WIU

Applied Deep Learning [30 hours]

Deep learning is an AI approach that mimics the workings of the human brain in processing data for decision-making. Many companies are employing this to automate and improve business processes. Through this CmU, learners will develop lifelong learning competence as they conduct continual market research to discover trends and industry developments using deep learning frameworks to uncover insights and provide predictions for businesses. Learners will also be competent to work collaboratively in teams to select and use suitable deep learning networks to solve business problems in different domains.

Text Analytics & Applications [45 hours]

With a large amount of data generated by enterprise and social media platforms, text analytics provides an effective way to retrieve information from the structured/unstructured data. Through this CmU, learners will be competent in undertaking a technical lead role to work with stakeholders to build automated text analytics solutions. Learners will develop competencies in analysing large amount of textual data and perform common text analytics tasks such as entity extraction, text categorisation, clustering, association and trend analysis to uncover insights to support business decision making and recommend process improvement.

Data Science for Business [45 hours]

Data science looks at analysing large amounts of data by applying data mining and programming skills. Learners will develop competencies to uncover useful intelligence by mastering the full spectrum of the data science life cycle and maximize returns at each phase of the process. Learners will be provided with analytics scenarios for different industries and will assess and apply supervised and unsupervised learning techniques suited for large and complex datasets. Learners will also be competent in training Machine Learning models to support decision-making and solve business problems.

Applied Data Science Project WIU [30 hours]

Data science is about analysing and visualising large data sets to reveal relationships and dependencies to perform predictions of outcomes and behaviours. Learners will develop competencies to plan and execute a data science project as a team and deliver solutions with insights for the business. Learners will also be competent in analysing large amounts of data to discover themes, patterns and trends to aid in improving business process and decision making. Learners are required to apply modelling techniques to generate results for uncovering trends and future predictions to enable decision making.

Post-Diploma Certificate in Enterprise Big Data Management

The PDC in Enterprise Big Data Management delivers the concepts and techniques in design and implementation of big data architecture, as well as parallel processing for big data. It focuses on equipping the learners with essential know-how, best practices and key considerations in the design, implementation and debugging of workflows for big data.

Data Processing for Big Data (click and open popup with the details below)
Infrastructure Systems for Big Data Processing
Streaming & Parallel Computing
Enterprise Big Data Management Project WIU

Data Processing for Big Data [30 hours]

Big Data can be defined as high volume, velocity and variety of data that require high-performance processing to uncover deeper insight for businesses. Through this CmU, learners will develop competencies in managing parallel processing resources on large data set in Big Data platforms. Learners will also be competent in creating computer programs to facilitate parallel querying, aggregation and processing of data in a distributed Big Data platform.

Infrastructure Systems for Big Data Processing [45 hours]

Big data platforms offer solutions that meet the increased needs of businesses for greater scale and analytics with data. Through this CmU, learners will develop competencies in managing data cluster resources on Big Data platform for scalability and performance of Enterprise resources. Learners will be competent in making operational decisions by managing data nodes in Big Data clusters to achieve optimal performance and design suitable strategy for harnessing Big Data to create business values. Learners will also develop competencies in designing NoSQL database to handle specific structured/unstructured Big Data sources.

Streaming & Parallel Computing [45 hours]

Data is the new oil of digital economy. Processing structured and unstructured data quickly enables businesses to get real-time performance metrics on business operations. Through this CmU, learners will develop competencies to analyse, design and develop scalable parallel applications using Big Data frameworks. Learner will be competent in ingesting Big Data in real-time to build real-time analytics applications to draw insights and drive decision making.

Enterprise Big Data Management Project WIU [30 hours]

The combination of Big Data and Machine Learning will drive business innovation across industries by analysing massive amounts of data and deriving predictive insights. Through this WIU, learners will demonstrate their competencies in developing a Big Data management project in teams by handling Big Data and real-time data and managing it in a Big Data platform for Enterprise. Learners will be competent to work collaboratively in a team to develop and deploy Machine Learning models using open-source libraries to derive insights for businesses. Learners will also be competent in undertaking a technical lead role to drive team discussions in designing Big Data solutions and integrate them into the big data management project.

In this PCM-based Specialist Diploma Course, there are 3 Competency Canvases as listed below. Skills and knowledge learners have learnt will be assessed for competency, together with a Work-Integration-Unit (WIU). Each Competency Canvas is offered as a Post-Diploma Certificate in the Specialist Diploma in Business & Big Data Analytics.

Business Analytics Canvas
Applied Data Science Canvas
Enterprise Big Data Management Canvas

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Specialist Diploma in Business & Big Data Analytics

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Specialist Diploma in Business & Big Data Analytics

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