David Quindoza

Education 🌱

09 Oct 2023
Exploratory Data Analysis Machine Learning Tableau Web Development SLDC Quality Improvement Anrdoid Studio

Google Advanced Analytics Professional Certificate (June - October | 2023)

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Recently completed the Google Data Analytics Professional Certificate, composed of 2 parts:

  • Data Analytics Professional Certificate

This was the introductory course to Data Analytics, giving me a solid foundation of how Data Professional use their skills in identifying problems, exploring the problem with data and creating impact to the organizations by providing data driven recommendations.

Some of the notable skills learned here was the usage of SQL with Bigquery to pull in data to Google Sheets. Google Sheets was then used to explore, manipulate, and tidy up the data.

Tableau was also introduced as means of data storytelling through compelling data visualizations and dashboards.

The last course introduced us into R programming language with Palmer Penguins dataset, I proceeded to continue the next part of the course, to learn more on how Python libraries like pandas,matplotlib, seaborn were used in Jupyter Notebook to make more versatile analysis of data.

  • Advanced Analytics Professional Certificate

This certification has provided me with a solid foundation in the principles of data science, including the PACE (Plan, Analyze, Construct, Execute) workflow. It has equipped me with the necessary tools and guidance for performing exploratory data analysis and statistical analysis using Python in Jupyter Notebook.

The course introduced Kaggle as a platform for engaging with a community of data analysts and scientists, allowing the sharing of projects, hobbies, and participation in machine learning competitions.

Statistical analysis was a key component of the course, covering A/B testing, probability, types of data distributions, sampling methods, and confidence intervals.

The next parts of the course covered introductions to Regression models and their assumptions. It was important to emphasize the ethical considerations when creating models and proper workflow. Understanding the business problem, and then identifying what kind of task the model will be doing comes first.

The later parts of the course began with Feature Engineering, selecting and making new features, cleaning up the data, considering imbalances of the dataset and label encoding (Feature Selection, Feature Transformation and Feature Extraction).

Some of the models taught in this part were Regression Models, K-Means, Random Forests and XGBoost paired with Gridsearch to find the best parameters of the model.

The final section emphasized model evaluation and the importance of iterative practices in planning, exploratory data analysis, and model development. It was important to split our data into training, validation, and test data(unseen data so we know how the model works in real world scenario).

You can find most of the applications of my learning through the capstones and the projects section of my website.

Mapua University (2019 - 2023)

I have my background as a recent information systems graduate, I have gained valuable experience in analyzing complex business problems, identifying gaps and requirements, and implementing solutions/recommendations through websites and data driven storyboards. Through these tools and methods, I have developed a strong foundation in problem-solving and analytical thinking.

Tools for understanding Business Problems:

  • Process Maps w/ Pain points
  • Why-Why Diagrams
  • Flow Charts
  • Business Requirements
  • Design Thinking
  • Process Chart Analysis (VA/NVMA/NVA Analysis)

Skills learned:

  • HTML/CSS
  • Jekyll
  • Angular
  • Java
  • Android Studio
  • Python and Jupyter Notebook
  • SQL
  • SAP Analytics Cloud

As an aspiring data analyst, my proficiency in these technical skills allows me to efficiently navigate large datasets and perform data analysis using a variety of tools and programming languages. Through my experience with case studies, process mapping, and other analysis techniques, I have honed my ability to identify patterns, detect anomalies, and draw insights from complex data. These skills enable me to contribute to an organization by providing valuable data-driven recommendations and aiding in effective decision-making.

In addition, I also had notable experience in Data Analytics as participating and getting into the National Finals of the 2020 ASEAN Data Explorers Competition.

Below are a list of some of my projects in my course:

  • A static HTML and CSS Website Image 1
  • A static HTML and CSS Website with single line of JS Image 2
  • Simple Store Catalog Site Image 3

Simple Pokedex App made in Android Studio

  • Demo Video:

Screenshots of Pokedex List Image 4

Screenshots of Pokedex Entry Image 5

ASEAN Data Explorers 2020 Finals Entry

Used SAP Cloud Data Analystics to visualize data from cleaned datasets regarding:

  • Population of Slums and Urban Areas until 2050
  • Urbanization from 2000 - 2018
  • Vehicle registration per Popultion
  • Traffic Congestion
  • Plastic Waste

From the Visalized data, we evaluated possible solutions and provided all data and solutions through a storyboard.

THESIS T.E.R.M. (Ticketing Expert Repair Maintenance) System for Small and Midsized Auto Shop Businesses

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The Term System is prototype of an Auto Shop System with an online ticketing with scheduling feature. Creates a ticket from customer bookings, that is regularly updated with the car’s progress in the auto shop. It also shows lead/idle time in between mechanics switching of work. Working demo at this link.