Skills and Tools Details
Programming
Short Description: Python, Java, Swift, Objective-C, C, C++, C#, SQL, PHP
Description: Python: For research and development in Masters and PhD at Deakin and Coventry Uni.
Java: For research and development of thesis work and mobile application in B.Sc. at HSTU.
Swift, Objective-C: Industrial (development) level experience.
C, C++, C#: Academic and professional (teaching) level experience.
SQL: Academic and professional (teaching) level experience.
PHP: Academic and personal (or in team) skill development level experience.
Level: 100%
Datascience
Short Description: Data Collection, Cleaning, Preprocessing, EDA, Analysis, Feature Engineering, Numpy, Pandas, Matplotlib
Description: Data Cleaning: Missing data identification, Data cleaning, removal and imputation.
EDA: Exploratory data analysis, univariate, bivariate and multivariate analysis and visualisation.
Data Preprocessing: Data type conversion, encoding, scaling, splitting.
Feature Engineering: Feature removal, feature derivation.
Data Analytics: Statistical analysis, distribution analysis, statistical significance analysis, p-value, AUC, chi2, correlation analysis, mutual information (MI).
Numpy: Data manipulation using 1D and 2D array, different array functions.
Pandas: Data manipulation using dataframe, different dataframe functions for data manipulation and visualisation (plotting).
Matplotlib: Different types of plot and subplot drawing: scatter plot, line plot, histogram, bar plot, bix plot, violin plot, spider plot, area plot, group plots, etc.
Level: 100%
Machine Learning
Short Description: Concept and Application, Scikit-learn, Auto-ML
Description: Concept and Application: ML fundamental, supervised, unsupervised, semi-supervised, reinforcement learning, ML algorithms, ensemble learning, data leakage, splitting, performance metrics, cross-validation, post-analysis, and pipelining.
Scikit-learn: ML concepts implementation.
Auto-ML: PyCaret, Auto-sklearnm AutoGluon, lazypredict, TPOT.
Darts: Time series data analysis.
Level: 95%
Deep Learning
Short Description: Concept and Application, Pytorch, Tensorflow, Keras
Description: Concept and Application: NN structure and optimisation, ANN, CNN (1D and 2D), RNN, LSTM, transfer learning, transformers, VGG-XX, ResNet, AlexNet, and data generators.
Pytorch: Image classification.
Tensorflow and Keras: Image classification and time series analysis.
Level: 85%
Health Informatics and Signal Processing
Short Description: Disorder detection, Epilepsy, Sleep disorders, EEG
Description: Disorder detection: Disorders related to epilepsy, sleep and ageing.
Epilepsy: Epileptic seizure detection, seizure event detection, time series data analysis, EEG data analysis.
Sleep disorders: Bruxism, insomnia, breathing disorders, movement disorders, REM behavioural disorders, hypersomnia, nervous system failure disorders, etc.
EEG signal: Time series data analysis, EEG data processing, data segmentation, feature extraction, EEG channel optimisation for specific applications.
Level: 95%
Could Platforms
Short Description: AWS, AWS Sagemaker, MS Azure, Azure ML Designer
Description: AWS: EC2, S3, ETL, Scheduling, Sagemaker, AutoGluon.
AWS Sagemaker: Sagemaker, Sagemaker Studio, Notebook, Lambda.
MS Azure: Virtual Machine, Virtual Network.
Azure ML Designer: Azure ML, Azure ML Designer.
Level: 80%
Teaching and Training
Short Description: Demonstration, Communication, Supervision
Description: Demonstration: Demonstrate and illustrate concepts using intuitive examples.
Communication: Communicate information and knowledge, and get feedback for learning development.
Supervision: Project and thesis supervision, and career consultation.
Evaluation: Evaluate learning performances, give feedback, and suggest improvement plans.
Level: 100%
Reporting and Presentation
Short Description: LaTeX, MS Word, MS Excel, MS PowerPoint, Illustrator
Description: LaTeX: LaTex report, LaTex beamer.
MS Word: Document processing and reports.
MS Excel: Data organisation and plotting.
MS PowerPoint: Presentation and storytelling.
Illustrator: Image editing.
Level: 95%
Management and Leadership
Short Description: Project Management, Team Lead, Client Management
Description: Project Management: Software project management, task scheduling, reporting and feedback, milestone management.
Team Lead: Team management, task distribution, product testing and feedback management, task integration.
Client Management: Requirement gathering, progress reporting and milestone delivery.
Level: 90%
Soft Skills
Short Description: Critical Thinking, Problem Solving, Communication, Collaboration
Description: Critical Thinking: Problem analysis, critical thinking and analysis, questioning, interpreting, and evaluating a problem.
Problem Solving: Problem identification, systematic solution planning, solution design, solution breakdown, section prioritisation, solution accumulation.
Communication: Presenting idea.
Collaboration: Collaboration and team work.
Level: 90%
