UPSKILLING

What you will learn :
1) importance of data quality / collection
2) data integration into a centralized system
3) to identify patterns and trends
4) to help business leaders to make better decisions by providing up to date insights
5) to support strategic planning and identifying HSE risk and opportunities

What you will learn :
1) the knowledge to identify risk key factors to potential accidents
2)selections of significant variables / features
3) to develop predictive models
4) to generate alerts for high-risk situations
5) the challenges in predicting workplace accidents

What you will learn :
- to effectively clean, explore, and manipulate data to uncover insights and trends related to WSH Performance
- to create engaging and informative visualization of WSH data
- to effectively communicate findings to different stakeholders, including senior management
- working with real world WSH data sets to develop their data analysis and visualization skills
- to apply data analytics and visualization skills to improve WSH performance in their organization

What you will learn:
1) intermediate concepts of data analytics and visualization
2) knowledge and skills necessary to analyze and visualize WSH Data using Power BI
3) able to effectively clean, explore, and manipulate data to uncover insights and trends related to HSE Performance
4) able to create engaging and advance visualization of WSH data
5) able to effectively communicate findings to different stakeholders, including senior management
6) gain hands-on experience working with real world WSH data sets to develop their data analysis and visualization skills
7) able to apply intermediate data analytics and visualization skills to improve WSH performance in their organization

What you will learn:
1) Fundamental concepts of predictive analysis and its relevance in the field of HSE.
2) To effectively collect, clean, organise, pre-process data relevant to HSE domain.
3) To conduct Exploratory Data Analysis.
4) To create predictive models using Microsoft Excel and Orange.
5) Select and apply appropriate models based on their HSE datasets.
6) To evaluate predictive models' performance.
7) Able to apply predictive analytics to HSE scenarios.

What you will learn :
- 8D Practical Problem Solving methodology
- Problem Definition
- Root Cause Analysis
- Cross- functional team building
- Qualitive tools such as 5 Why,
Is / Is Not analysis, Ishikawa Diagram,
Fault Tree Analysis, Event Tree Analysis
- Facilitate Incident Investigation using 8D PPS methodology
- Develop / Monitor / Evaluate mitigation measures strategy

What you will learn:
1) To effectively Drive Change
2) To effectively Build a Safety Culture
3) To effectively Engage Stakeholders
4) To effectively Resolve Conflict
5) To effectively Present Data
6) To effectively Lead and Advocate HSE causes

What you will learn: 1) various applications of AI in HSE management
2) to improve risk management
3) to enhance compliance monitoring
4) to optimise training programs
5) to reduce environment impacts

What you will learn:
1) Concepts of advance machine learning models and its relevance in the field of HSE.
2)To deploy various advance machine learning models in HSE context
3)To create various advance predictive models using Orange.
4)To effectively select advance machine learning models on HSE datasets
5)To effectively deploy advance machine learning models on HSE datasets
6)To evaluate advance predictive models' performance.

What you will learn:
1) Fundamental concepts of machine learning models and its relevance in the field of HSE.
2) Supervised and Unsupervised machines learning models.
3) To create predictive models using Orange.
4) To effectively select machine learning models on HSE datasets
5) To effectively deploy machine learning models on HSE datasets
6) To evaluate predictive models' performance.