Committed to staying at the forefront of data engineering, machine learning, and cloud technologies through continuous professional development.
2024 • Amazon Web Services
Latest AWS certification validating expertise in AI and machine learning services on AWS. Demonstrates proficiency in AI/ML fundamentals, AWS AI services, and responsible AI practices. Recently obtained - reinforcing production ML deployment capabilities.
September 2024 • Microsoft
Foundation certification in Microsoft Azure cloud services, architecture, and governance. Expands cloud expertise beyond AWS, demonstrating multi-cloud competency essential for enterprise data engineering projects.
"Gaining this certification has expanded my cloud knowledge and further solidified my foundation in cloud computing, Azure services, and cloud architecture. This is another step forward on my journey toward mastering tools for Data Engineering."
August 2024 • Udemy
Advanced training in Amazon QuickSight for business intelligence and data visualization. Transitioned from Tableau to leverage QuickSight's ML insights with Amazon Q and Natural Language Queries capabilities.
January 2024 • Pierian Training
Comprehensive course in AI principles and language model fine-tuning led by Jose Marcial Portilla, Head of Data Science at Pierian Training. Focused on domain-specific datasets, model accuracy improvement, and cost-effective training methodologies.
June 2023 • Amazon Web Services
Foundation AWS certification demonstrating broad understanding of AWS Cloud services, pricing, security, and architectural principles. Entry-level certification that established AWS expertise later applied in production ML deployments.
April 2021 • DataCamp
Comprehensive data science certification achieved after 200 hours of training and 29 individual certifications over 10 months. Established foundation in Python data science ecosystem that directly enabled current ML engineering work.
"This certification provided the career-building Python skills needed to succeed as a data scientist. The versatile Python knowledge gained enables me to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional."
My approach to professional development reflects the rapidly evolving nature of data engineering and machine learning. Each certification represents not just academic achievement, but practical skills immediately applied to real-world projects.
Certifications align with current and future project needs, ensuring immediate practical application.
Staying current with emerging technologies like BERT, GPT models, and cloud-native ML services.
Build from foundations (DataCamp) through cloud platforms (AWS/Azure) to advanced AI specializations.
Every certification translates to measurable improvements in project outcomes and team capabilities.