Lamis Abdallah

Delivered online programming lessons to school students in Saudi Arabia with an emphasis on interactive, engaging instruction. Provided personalized learning paths and one-on-one sessions tailored to different age groups and skill levels.

Developing hands-on skills in intermediate embedded systems with AVR microcontroller programming (Atmega 32) and low-level hardware interfacing. Worked on system design topics including timers, interrupts, and interfacing peripherals such as 7-segment displays, LCDs, and sensors.

Completed a 6-month data engineering track (648 hrs) covering Python, OOP, data structures and algorithms, SQL/NoSQL, ETL, and big data tools including Hadoop, Hive, Spark, and Kafka. Worked on an end-to-end capstone involving scalable data pipeline development, including collection, cleaning/preprocessing, ML model building, and production deployment.

Completed a 120-hour machine learning summer training (including 30 hrs soft skills & freelancing). Covered supervised and unsupervised learning (e.g., regression, SVM, KNN, Naive Bayes, decision trees, random forests, boosting, K-means, GMM, PCA) and introduced neural networks with cloud-based projects and capstone work.

Contributed to embedded systems academic and practical projects focused on AVR microcontrollers (Atmega 32). Collaborated with peers to implement peripheral interfacing and applications using timers, interrupts, and serial communication protocols.

Participated in backend development training focused on understanding the architecture and functionality of payment systems powering Damen's ePayment platform. Worked with development teams to apply backend concepts in building scalable and secure payment services.

Completed a data analytics and statistical modeling training using SAS to manipulate large datasets, run analyses, and derive insights for finance-related decision-making. Also covered financial markets and corporate banking strategies and learned professional networking and personal branding through LinkedIn workshops.

Mentored 5 high school students through the Technovation Girls program, supporting them from ideation to building an MVP. Guided students in programming fundamentals and helped simplify complex concepts while reinforcing an entrepreneurial mindset throughout execution.

Delivered AI and machine learning sessions to students and designed hands-on projects to simplify complex ML concepts. Organized technical events and workshop-style learning activities.

Completed an intensive embedded systems course covering microcontroller architectures including AVR and ARM Cortex-M. Developed embedded systems with AVR and implemented RTOS for ARM-based projects to improve task scheduling, multi-threading, and real-time performance.

Activities and societies: Covered Python, OOP, data structures & algorithms, SQL/NoSQL, data modeling, ETL, and big data tools (Hadoop, Hive, Spark, Kafka) plus Azure Synapse.

Intensive Data Engineering track with hands-on training in building scalable data pipelines and real-time data streaming solutions. Includes an end-to-end capstone involving data collection, cleaning/preprocessing, ML modeling, and deployment.

Activities and societies: Trained on supervised and unsupervised learning (e.g., linear/logistic regression, SVM, KNN, Naive Bayes, decision trees, random forests, boosting, K-means, GMM, PCA) and introductory neural networks using Google Cloud and Kaggle.

120-hour summer training focused on machine learning concepts and algorithms. Completed projects covering data preprocessing, model selection, and performance evaluation, including a capstone deployed from analysis to deployment.