Certificates Repository

This repository showcases the certificates I have earned through self-study during my college years. These credentials highlight my commitment to continuous learning and skill development, covering a range of topics from foundational courses to advanced professional certificates.

Certificates

• IC3 Digital Literacy: IC3 Digital Literacy.pdf
  This professional certification marked the beginning of my formal education in digital literacy. It was a prerequisite for "Application Development" in my second year of university, covering essential topics such as Digital Literacy, Networking, Basic Troubleshooting, and Cybersecurity. This certificate laid the groundwork for my technical skills, particularly in my journey to becoming a data engineer.

• Understanding Data Engineering (DataCamp): Understanding Data Engineering.pdf
  This foundational course provided a comprehensive introduction to key data engineering concepts, including Big Data, Databases, Data Warehouses, Cloud Computing, and Data Pipelines. It served as a strong starting point in shaping my mindset for the field of data engineering.

• Introduction to SQL (DataCamp): Introduction to SQL.pdf
  My first hands-on course in data engineering, sponsored by "Data Engineering Pilipinas," introduced the fundamentals of SQL. The course covered querying tables, creating views, working with data types and schemas, and various SQL dialects. This provided a solid foundation for practical data engineering tasks.

• Intermediate SQL (DataCamp): Intermediate SQL.pdf
  This course built on the basics of SQL, enhancing my practical knowledge of functions such as COUNT, MAX, MIN, and AVG. The skills learned here were crucial for working on mini-projects documented in my Roadmap. It strengthened my problem-solving abilities and confidence in handling SQL tasks.

• Joining Data in SQL (DataCamp): Joining Data in SQL.pdf
  This course deepened my understanding of joining data using Set Theory, Outer Joins, Self Joins, Cross Joins, and Subqueries. I applied these concepts in my projects to enhance my proficiency as a data professional. As someone who learns best through practice, I continuously build projects to apply what I learn.

• Relational Databases in SQL (DataCamp): Relational Databases in SQL.pdf
  Completing this course strengthened my foundation in Attribute Constraints, Key Constraints, and Referential Integrity. I immediately applied these concepts to real-world mini-projects involving data truncation, column migration, and schema refinement, which can be found in my Roadmap.

• Web Scraping (Bootcamp): Web Scraping (Bootcamp).pdf
  This bootcamp introduced me to foundational web scraping techniques such as working with HTML div elements, classes, asynchronous programming, and authentication handling. One of the most exciting parts was learning video-to-text transcription using ASR (Automatic Speech Recognition) and Diarization with tools like WhisperX and Hugging Face models. This strengthened both my scraping and data-processing skills.

• Database Design in SQL (DataCamp): Database Design in SQL (DataCamp).pdf
  This course taught me the techniques and technologies used to design and manage databases for different use cases, including:

  • Conceptual Modeling
  • Logical Modeling
  • Physical Modeling
  • Normalization
  • Denormalization
  • Types of Normal Forms
  • Managing Views
  • Managing Roles and Privileges
  • Table Partitioning

  This knowledge is crucial for me as an aspiring Data Engineer, as database design plays a huge role in building reliable data systems.

• Python for Data Engineering Certificate (Coursera):
  Python for Data Engineering Certificate.pdf
  and
  Python for Data Engineering Badge.pdf
  This project-based course taught me the practical skills needed to implement ETL pipelines using different ingestion methods such as APIs, Web Scraping, and Object Relational Mapping for connecting relational databases in Python. This course aligns with my learning philosophy of “learning by doing,” enabling me to build, optimize, and solve real ETL workflows.

• Data Warehousing Concepts (DataCamp): Data Warehousing Concepts (DataCamp).pdf This course strengthened my understanding of how modern data warehouses work and why they are essential for analytical workloads. Key concepts include:

  • OLTP vs OLAP Systems
  • ETL vs ELT Pipelines
  • Dimensional Modeling (Star & Snowflake Schemas)
  • Fact & Dimension Tables
  • Data Marts
  • Data Lakehouse Concepts
  • Traditional vs Cloud Data Warehouse Architectures

  This certificate plays a major role in my data engineering journey, helping me understand how to design scalable analytical systems. I actively apply these concepts in the projects within my Roadmap.

Contact

Feel free to reach out if you have any questions or would like to collaborate on a project:

• Email: christianbacani581@gmail.com
• LinkedIn: Christian Bacani
• Portfolio: Christian Bacani on DataCamp