Validated expertise in designing and building data pipelines on AWS, covering data ingestion, transformation, storage, and orchestration using services like S3, Glue, Redshift, Kinesis, and Lake Formation. Demonstrates hands-on ability to architect scalable, production-grade data engineering solutions on the AWS cloud.
Completed Google's professional certificate covering the full data analytics workflow — from data cleaning and preparation to analysis, visualization, and storytelling. Gained proficiency in SQL, R, Tableau, and spreadsheets to derive actionable insights and communicate findings effectively to stakeholders.
Gained foundational knowledge of cloud computing concepts including service models (IaaS, PaaS, SaaS), deployment models, and the core benefits of cloud infrastructure. Built a solid understanding of how cloud platforms enable scalable and cost-efficient application and data workloads.
Deepened understanding of core cloud computing principles including virtualization, distributed storage, cloud networking, and security. Covered key architectural patterns used in modern cloud-native systems and how enterprises leverage cloud infrastructure for resilience and scalability.
Learned the fundamentals of the Internet of Things including how connected devices communicate, collect, and transmit data across networks. Covered IoT sensors, protocols, security considerations, and real-world use cases — providing useful context for understanding data generation at the edge.
Completed the foundational Python programming course by Dr. Chuck at the University of Michigan. Covered core programming concepts including variables, conditionals, loops, functions, and data structures — laying the groundwork for the data engineering and ML work that followed.
Gained awareness of the cybersecurity landscape including common threats, attack vectors, and best practices for protecting data and systems. Covered topics such as network security, encryption, malware, and how organizations defend against cyber threats — relevant to building secure data pipelines.
