My Resume

Skills & Expertise

Management Studio

2021-Recent

Relevant courses to data analytics

Advanced Mathemathics: Applied advanced mathematical concepts, including calculus, differential equations, linear algebra, number theory, topology, and abstract algebra. Leveraged the R programming language to deepen understanding and practical application in data analytics and mathematical modeling.

Fundamentals of Data Science: gain understanding in data cleaning, forecasting, and advanced analysis using Python and Google Colab. Grounded in the study of handling vast data volumes, uncovering patterns, and making informed decisions. Proficient in applying complex machine learning algorithms for predictive modeling.

Intelligent and Decision Support System: analyzing multiple sources of data and identifying patterns, trends and associations to emulate human decision-making capabilities.

2023-2024

Relevant courses to data analytics

Data visualization: covers data visualization concepts, techniques, and tools (SaaS and Tableau), exploring sources, acquisition, and analysis of diverse data types.

AI for Everyone: provides a brief overview of AI concepts, including history, basic principles, and real-world applications, introducing key processes like Machine Learning and Natural Language Processing.

Human Computer Interaction: gain insights into principles, methods, and analytical skills essential for creating effective and user-friendly interactions between humans and computers.

Aug 2022-Aug 2023

Contributed to the development of a medical chatbot using Python as part of a team, achieving an impressive accuracy rate of 81%, surpassing industry benchmarks such as ChatGPT (74%) and Hugging Face (51%)
Conducted thorough testing of the chatbot using 128 sets of user data using Postman API and stored in MySQL database
Formulated and implemented over 140 regular expressions in machine learning for data processing, which were stored in a JSON database
report using Microsoft Excel

Aug 2023-Now

Facilitated the grading process for over 90 theory and hands-on assignments related to machine learning
Analyzed and refined scoring parameters to ensure precision and accuracy in assignment evaluations
Applied advanced statistical techniques in the analysis and interpretation of data, including regression analysis, properties of distributions, and statistical tests.

Oct 2022-Aug 2023

Streamlined and refined grading criteria for 90+ assignments, resulting in improved accuracy and precision, leading to a 20% reduction in grading errors and enhanced student satisfaction
Created wireframes and UI/UX design for the Laboratory Assistant Presence System and utilized JIRA for the team management, enhancing the user experience and functionality of the system

Sep 2022

Occupational techniques (Python basics, data manipulation, web scaping, automation, data science and AI techniques).
Science applied to Python development (data science principles, AI concepts, data visualization).
Occupational technology (Python libraries, Jupyter notebooks, Integrated Development Environments [IDEs]).

Jun 2023

Define and explain key concepts involved in data analytics including data, data analysis, and data ecosystems.
Conduct an analytical thinking self assessment giving specific examples of the application of analytical thinking.
Discuss the role of spreadsheets, query languages, and data visualization tools in data analytics.
Describe the role of a data analyst with specific reference to jobs.

Oct 2023

Gain insights into the meanings of neural networks, machine learning, deep learning, and data science.
Realistically assess what AI can and cannot do.
Spot chances to apply AI solutions within the organization.
Get hands-on with the process of building machine learning and data science projects.
Learn how to effectively work with an AI team and formulate an AI strategy in the company.