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Professional Diploma in Data Science

9 months Part time / 6 Months Full time Instructor-led Live & Mentor-led Blended Learning NICF-Diploma in Infocomm Technology (Data)

Be a Data Scientist skilled at R programming , Statistics, Spark with Azure HDInsights and Azure Machine learning.

What do I Get?

Acquire Data Science Skills

Learn  R programming , Statistical modelling and Azure Machine learning to Clean, Analyse , Visualize and Predict both structured and unstructured data using machine learning models in R studio, Azure Machine Learning studio, Spark HDInsights to prepare yourself for a Data Scientist role 

Mentor-Led Blended Learning Delivery

We deliver blended learning through a combination of self-paced e-learning, instructor-led flipped classes and mentoring  from industry experts to greatly increase your efficiency and effectiveness

Up to 95% Funding

Singapore Citizens / Permanent Residents can receive up to 95% funding* from SkillsFuture Singapore and further subsidies using your SkillsFuture credit and Post-Secondary Education Account.

*Terms and Conditions Apply.

Audience and Certificates

Target Audience

  • Individuals who are interested in a Data Science career

Prerequisite

Minimum Age: Min. 21 years

Academic Level & Work Experience: 3 GCE A Level passes or its equivalent and minimum 1-year experience in statistics or programming.

Graduation Requirements

  • Minimum attendance of 75% for all Sessions in each of the modules of the qualification
  • Should be assessed Competent (C) in each of the modules of the qualification

Certificate(s)

  • Statement of Attainment by SSG, Singapore: ICT-DES-4001-1.1 Data Design

    Design data models and data flow diagrams and mechanisms to optimise the flow, maintenance, storage and retrieval of data

  • Statement of Attainment by SSG, Singapore: ICT-DIT-4006-1.1: Data Visualisation

    Design data displays to present trends and finding, incorporating new and advanced visualisation techniques and analytics capabilities

  • Statement of Attainment by SSG, Singapore: ICT-SNA-4009-1.1:Data Strategy)

    Develop data management structures and recommend policies, processes and tools for effective data storage, handling and utilisation

  • Statement of Attainment by SSG, Singapore: Data Engineering : ICT-DIT-4005-1.1

    Translate business requirements into data structures and processes to standardise data, verify data reliability and validity, store, extract, transform, load and integrate data

  • Statement of Attainment by SSG, Singapore: Analytics and Computational Modelling : ICT-DIT-4001-1.1

    Develop and utilise new algorithms and advanced statistical models to enable the production of desired outcomes

  • Statement of Attainment by SSG, Singapore: Emerging Technology Synthesis : ICT-SNA-4011-1.1

    Evaluate new and emerging technology and trends against the organisational needs and processes

  • Statement of Attainment by SSG, Singapore: Problem Management : ICT-OUS-3011-1.1

    Handle specific problems from diagnosis and prioritisation to the identification and implementation of solutions

  • Statement of Attainment by SSG, Singapore: Project Management : ICT-PMT-4001-1.1

    Business Needs Analysis : Investigate existing business processes, evaluate requirements and define the scope for recommended solutions and programmes

Blended Learning Journey

(363 Hours)

E-Learning

90 hours

Projects / Assignments

180 hours

Flipped Class/Mentoring

90 hours

Assessment

3 hours

Modules

Data Queries and Visualization Basics (SF)

You will get started on your Data Science journey by learning how to write queries and modify data using Transact-SQL as well as visualise data using Power BI.

Session Plan

More Details

Learning Outcome

Knowledge

 

  • Foundational statistics that can be used to analyze data
  • Syntax of Transact-SQL, working with data types, tables and manipulating data using T-SQL
  • How to program using Transact-SQL
  • Learn how to perform visual analysis to gather insights
  • Understand different types of data visualisation techniques using Power BI
  • Learn how to perform visual analysis to gather insights
  • Understand Data visualisation tools like Power BI
  • Understand the anatomy of a data visualisation
  • Understand Visualisation design methodology and process with Power BI

Skills

  • Identify key factors that may affect the success of data visualisation
  • Assess the data to be visualised based on the volume, velocity and variety
  • Gather insights/stories using the relevant Power BI visualisation techniques
  • Develop a data visualisation model that conveys the insights to the audience
  • Write programs using T-SQL
  • Implement error handling and transactions using T-SQL
  • Identify key factors that may affect the success of data visualisation
  • Assess the data to be visualised based on the volume, velocity and variety

Other Information

  • Funding Validity Period:  30/7/2021
  • Course Developer : Lithan Academy
  • Qualification Course Code:  CRS-Q-0038611-ICT

 

Basic R Programming(SF)

You will learn the basics of R programming, how to handle data structures such as vectors, matrices, lists and data frames and create your own stunning data visualisations.

Session Plan

More Details

Learning Outcome

Knowledge

  • Introductory R language fundamentals and basic syntax
  • Basics of R and how it’s used to perform data analysis
  • Creating Matrices and Data frames
  • Work with data in R
  • Introduction to Azure Machine Learning  
  • Introduction to Forecasting and Time Series 

Skills

  • Define analytics architecture requirements to deploy the predictive model
  • Design and develop predictions in Azure Machine Learning(AML) studio 
  • Create R scripts and integrate in AML
  • Create Time series forecasting model
  • Monitor and tune the deployed model to ensure that it delivers the expected outcome and minimize the error predictions

Other Information

  • Funding Validity Period: 30/7/2021
  • Course Developer : Lithan Academy
  • Qualification Course Code: CRS-Q-0038611-ICT

Data Science Essentials (SF)

You will explore Advanced R programming and perform predictive analytics and create visualisations using the popular ggplot2 package.

Session Plan

More Details

Learning Outcome

Knowledge

  • Research practices
  • Various research claims 
  • Survey design and measurement, Reliability and Validity
  • Correlation and Experimental design
  • Legal and ethical foundations in Data practice 
  • Bias in Data processing and Data privacy
  • Business and Ethical Data usage

Skills

  • Design Correlation and Regression Experiments
  • Sampling analysis using Azure notebooks 
  • AnalyseFrequency and Association 
  • Apply the IRAC framework to real-world cases
  • Analyse Recidivism data set and context.

Other Information

  • Funding Validity Period: 30/7/2021
  • Course Developer : Lithan Academy
  • Qualification Course Code: CRS-Q-0038611-ICT

 

Statistical Thinking for Data Science and Analytics(SF)

You will learn descriptive statistics, basic probability, random variables, sampling and confidence intervals and hypothesis testing using Excel.

Session Plan

More Details

Learning Outcome

Knowledge

  • Range of statistical and advanced computational modelling techniques
  • Advanced mathematical models and theories
  • Elements of various Statistics and probability 
  • Features, pros and cons of various statistical approaches, algorithms and storytelling 
  • Hypothesis Testing procedures to evaluate statistical models
  • Impact of changes to algorithms and models on optimization

Skills

  • Craft analytics story 
  • Conduct probability analysis
  • Differentiation and derivatives 
  • Perform matrix transformations 
  • Perform Hypothesis testing
  • Perform sampling distribution 

Other Information

  • Funding Validity Period: 30/7/2021
  • Course Developer : Lithan Academy
  • Qualification Course Code: CRS-Q-0038611-ICT

Principles of Machine Learning (SF)

You will get hands-on experience building and deriving insights of text analytics from machine learning models using R and Azure Machine Learning.

Session Plan

More Details

Learning Outcome

Knowledge

  • Text analytics solutions
  • Text analytics process and artifacts
  • Text mining techniques and how to apply them
  • Operation of Classifiers and how to use Logistic Regression as a Classifier
  • Metrics used to evaluate classifiers and regression models
  • Operation of Regression models and how to use Linear regression for prediction and forecasting
  • Problems of over-parameterization and dimensionality
  • How and when to use common supervised machine learning models
  • Compare different Multi Class models to analyse the best model

Skills

  • Identify text analytics solution and platform requirements
  • Define the metadata and corpus for the data to be imported into the text analytics repository
  • Develop a standardised set of text analytics artifactswith the relevant stakeholders
  • Develop term-document frequency matrix to enable lookup of text and documents within the corpus
  • Modify the text analytics solution to ensure that it produces the expected results
  • Define the process to perform text analytics based on the business requirements and text analytics artifacts
  • Use regularization on over-parameterized models
  • Apply cross validation to estimating model performance
  • Apply and evaluate k-means and hierarchical clustering models
  • Apply Machine Learning models to real-life situations

Other Information

  • Funding Validity Period: 30/7/2021
  • Course Developer : Lithan Academy
  • Qualification Course Code: CRS-Q-0038611-ICT

Spark on Azure HDInsight(SF)

You will learn how to use Spark in Microsoft Azure HDInsight to create predictive analytics and machine learning solutions.

Session Plan

More Details

Learning Outcome

Knowledge

 

  • Programming language and tools for big data analytics and how they integrate with big data technologies
  • Emerging trends in the business domain
  • Concepts of computing used in big data analytics
  • Machine Learning Support in Spark Clusters
  • Implement a predictive solution using Spark
  • Build real-time machine learning solutions with Spark.
  • Use R to work with data and build models by leveraging Hadoop in HDInsight.

 

  • Software development methodologies, with emphasis on requirement gathering for data science projects
  • Role of stakeholders and their level of involvement in data science projects
  • Information gathering methods for data science projects
  • Functional and non-functional requirements of Data Science projects and document them
  • Principles of reactive and proactive problem management
  • Documentation requirements and protocols in problem management
  • Usage of documentation tools, systems and records to log relevant information throughout the problem's lifecycle
     

Skills

  • Review the hypothesis to address problem statement for the analytics project
  • Explore the data in the analytics platform/organisation to familiarise with the data available for analysis
  • Perform analysis on the data to prove/disprove the hypothesis and obtain business insights using the relevant programming language/tools for big data analytics tools
  • Develop a report of the business insights for a case study
  • Implement a predictive solution using Spark
  • Identify and review key information sources related to the business problem / needs
  • Elicit information from key stakeholders using appropriate information gathering methods
  • Analyse and prioritise the business requirements to be aligned to the organisation’s directions
  • Identify dependencies for the identified business requirements 
  • Implement solutions to address the problem through appropriate control procedures
  • Propose solutions to prevent future occurrences of similar problems
  • Document information about problems and the appropriate workarounds and resolutions

Other Information

  • Funding Validity Period: 30/7/2021
  • Course Developer : Lithan Academy
  • Qualification Course Code: CRS-Q-0038611-ICT

Pricing and Funding

SGD 18000.00

Pricing

Fee Description

Detailed Breakdown

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