Gain the career-building talent analytics skills you need to succeed as a talent analytics specialist. No coding experience required.
In this course, you will learn integral skills in data analytics by applying machine-learning algorithms in processing structured and unstructured data. You will learn how to import, clean, manipulate, visualise and analyse human resource data through hands-on interactive exercises. You will learn two easy to use and highly popular tools, Microsoft Power BI Desktop and Orange datamining tool to conduct data visualisations and analysis. With the newly acquired data analytics skill set, you can gain insights into your HR data and make critical data-driven decisions.
Who Should Attend
- HR Data Analyst, HR Executives, HR Managers, HR Generalist, HR Specialist, HR Consultant, HR Business Partner and any keen learners on Talent Analytics
- Data Science Lingo
– Understand basic data science terminologies and a typical data analysis process.
- Data Pre-processing
– Understand the need for data pre-processing and apply essential steps in importing, cleaning and transforming data in preparation for analysis.
- Data Visualisation
– Create professional looking HR dashboards using Microsoft Power BI Desktop.
– Tell a data story using the dashboard.
- Data Collection Process
– Understand the different ways data can be collected and stored for analysis.
- Machine Learning
– Understand the relation between Machine Learning and Artificial Intelligence.
– Apply Machine Learning techniques in employee attrition prediction.
- Employee Sentiment Analysis
– Build an employee Sentiment Analysis model to analyse organisation-wide climate survey.
- Course introduction (What is Talent Analytics and its objectives)
- Data analytics terminologies and stages
- Sources and type of data
- Data pre-processing
- Visual Vocabulary and Data visualisation
- Workshop 1 – Data Visualisation using MS Power BI
- Workshop 2 – Data Storytelling using MS Power BI Dashboard
- Discussion & Sharing
- Employee lifecycle
- Talent Data collection
- Supervised Learning – Regression vs Classification
- Workshop 3 – Machine Learning; employee attrition prediction using Orange
- Natural Language Processing – Sentiment Analysis
- Workshop 4 – Machine Learning; employee survey sentiment analysis using Orange
- Discussion & Sharing
Learners will be assessed in the following manner:
- Pop quizzes during lessons.
- Completion of an individual assignment on building a HR Dashboard using Microsoft Power BI Desktop application.
- Completion of an individual Machine Learning assignment on employee attrition prediction using Orange datamining tool.
- Completion of an individual Sentiment Analysis assignment on staff written feedback using Orange datamining tool.
- No prior knowledge in data science, machine learning, or statistics is required.
- A computer with Internet access, Orange Data mining tool and Microsoft Power BI Desktop installed.
Time: 9.00am to 5.30pm
(Registration starts at 8.30am on the first day)
Platform: SHRI Premises @
137 Cecil Street, #09-08
SHRI Members: S$650.00
(Sign up for SHRI Membership to enjoy $100 off course fee!)
(Course fee is subject to 7% GST)
Limited Seats only, sign up now to avoid disappointment!
*Grant amount indicated here does not include absentee payroll (AP) funding as this is dependent on the trainee’s hourly basic salary (other than for trainees supported by surrogate Employers, where AP is computed on flat rate independent of salary).
Mr Calvin Choon has over 15 years of experience in the telecommunication industry at an upper middle management level and over 20 years of teaching experience at both schools and Institutes of Higher Learning (IHL). Calvin started his consulting firm, Frindle Learning, in 2019 to provide Education and Career Guidance to youths and young professionals. He decided to take up that role as he has rich industry experience and also a good understanding of Singapore’s education system. As an educator, he believes in creating abundance and not scarcity. He derives satisfaction from helping others to succeed.
As a lifelong learner, Calvin recently completed his second Master’s degree in Industry 4.0 at NUS and attained a GPA of 4.7. It has equipped him with the latest knowledge in Industry 4.0 technologies. With the increase in both life expectancy and retirement age of workers, continued education is becoming very important. He is a firm believer that education should not be viewed as a means to an end but as an attitude of learning and development of new skills so as to remain a valuable contributor to our society.
Calvin’s areas of expertise include (but not limited to): Artificial Intelligence (Machine Learning), Data Analytics, Data Engineering, Industry 4.0 technologies, Digital Transformation, Education and Career guidance, Educational Psychology, Design Thinking.