Sulayam Abdul Rehman

Completed comprehensive training in Machine Learning and Data Science.
Gained expertise in data collection, cleaning, preprocessing, and visualization techniques using Python, Pandas, Numpy, Matplotlib, and Seaborn.
Conducted Exploratory Data Analysis (EDA) to identify data patterns and relationships, focusing on feature engineering and selection.
Studied supervised learning algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forests, SVM) and their evaluation metrics (accuracy, precision, recall, F1 score).
Learned unsupervised learning algorithms, including clustering methods (K-means, Hierarchical, DBSCAN) and dimensionality reduction techniques (PCA, t-SNE).
Explored advanced machine learning techniques, such as ensemble methods (Boosting, Bagging), basics of Neural Networks and Deep Learning, and an introduction to TensorFlow and Keras.
Acquired foundational knowledge of Natural Language Processing (NLP) and OpenCV.
Practiced model tuning and optimization, including hyperparameter tuning (Grid Search, Random Search), cross-validation, and strategies to avoid overfitting and underfitting.
Engaged in end-to-end real-world projects and industry-specific case studies, gaining hands-on experience in EDA and machine learning models.
Enrolled and contributed to all 5 intensive Kaggle competitions hosted by Tahaluf Al Emarat Technical Solutions, enhancing competitive data science skills and experiencing real-time problem-solving challenges.

Data Science and Machine Learning trainee at Tahaluf | Abu Dhabi, UAE March. 2024 - present
⦁ Completed comprehensive training in Machine Learning and Data Science. Gained expertise in data collection, cleaning, preprocessing, and
visualization techniques using Python, Pandas, Numpy, Matplotlib, and Seaborn.
⦁ Conducted Exploratory Data Analysis (EDA) to identify data patterns and relationships, focusing on feature engineering and selection. Studied
supervised learning algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forests, SVM) and their evaluation metrics
(accuracy, precision, recall, F1 score).
⦁ Learned unsupervised learning algorithms, including clustering methods (K-means, Hierarchical, DBSCAN) and dimensionality reduction
techniques (PCA, t-SNE). Explored advanced machine learning techniques, such as ensemble methods (Boosting, Bagging), basics of Neural
Networks and Deep Learning, and an introduction to TensorFlow and Keras.
⦁ Acquired foundational knowledge of Natural Language Processing (NLP) and OpenCV. Practiced model tuning and optimization, including
hyperparameter tuning (Grid Search, Random Search), cross-validation, and strategies to avoid overfitting and underfitting.
⦁ Engaged in end-to-end real-world projects and industry-specific case studies, gaining hands-on experience in EDA and machine learning models.
Projects are mentioned below.
⦁ Enrolled and contributed to all 5 intensive Kaggle competitions hosted by Tahaluf Al Emarat Technical Solutions, enhancing competitive data
science skills and experiencing real-time problem-solving challenges.

Data Science and Machine Learning trainee at Tahaluf | Abu Dhabi, UAE March. 2024 - present
⦁ Completed comprehensive training in Machine Learning and Data Science. Gained expertise in data collection, cleaning, preprocessing, and
visualization techniques using Python, Pandas, Numpy, Matplotlib, and Seaborn.
⦁ Conducted Exploratory Data Analysis (EDA) to identify data patterns and relationships, focusing on feature engineering and selection. Studied
supervised learning algorithms (Linear Regression, Logistic Regression, Decision Trees, Random Forests, SVM) and their evaluation metrics
(accuracy, precision, recall, F1 score).
⦁ Learned unsupervised learning algorithms, including clustering methods (K-means, Hierarchical, DBSCAN) and dimensionality reduction
techniques (PCA, t-SNE). Explored advanced machine learning techniques, such as ensemble methods (Boosting, Bagging), basics of Neural
Networks and Deep Learning, and an introduction to TensorFlow and Keras.
⦁ Acquired foundational knowledge of Natural Language Processing (NLP) and OpenCV. Practiced model tuning and optimization, including
hyperparameter tuning (Grid Search, Random Search), cross-validation, and strategies to avoid overfitting and underfitting.
⦁ Engaged in end-to-end real-world projects and industry-specific case studies, gaining hands-on experience in EDA and machine learning models.
Projects are mentioned below.
⦁ Enrolled and contributed to all 5 intensive Kaggle competitions hosted by Tahaluf Al Emarat Technical Solutions, enhancing competitive data
science skills and experiencing real-time problem-solving challenges.

Worked as a Software Engineer on Python, Java etc..
Worked on various tools like DOTVVM, Portability Analyzer, Upgrade Assistant etc. for the accelerators in modernizing .NET to .NET Core Apps.
Developed Typescript based React Components to build an In-house component library using a developed Healthcare based Application which connects React webpage to WinForms application.

Software Engineer at Persistent Systems Ltd. | Bengaluru, Karnataka Jan. 2023 - March 2024
⦁ Worked as a Software Engineer on Python, Java etc..
⦁ Worked on various tools like DOTVVM, Portability Analyzer, Upgrade Assistant etc. for the accelerators in modernizing .NET to .NET Core Apps.
⦁ Developed Typescript based React Components to build an In-house component library using a developed Healthcare based Application which
connects React webpage to WinForms application.

Software Engineer at Persistent Systems Ltd. | Bengaluru, Karnataka Jan. 2023 - March 2024
⦁ Worked as a Software Engineer on Python, Java etc..
⦁ Worked on various tools like DOTVVM, Portability Analyzer, Upgrade Assistant etc. for the accelerators in modernizing .NET to .NET Core Apps.
⦁ Developed Typescript based React Components to build an In-house component library using a developed Healthcare based Application which
connects React webpage to WinForms application.

Collaborated with a team of 5 to build a motion detector device using Raspberry Pi, cameras and sensors for hardware and Computer Vision (OpenCV) for building the algorithm.
Used libraries like Numpy, Pandas, flask and OpenCV.

Marketing Data Analyst Intern at BYJU’s | Abu Dhabi, UAE Jan. 2021 - June. 2021
⦁ Conducted detailed market research to understand target demographics and customer behaviour.
⦁ Analyzed data from various campaigns to identify trends and optimize marketing strategies.
⦁ Utilized statistical tools to evaluate the effectiveness of marketing pitches, leading to a 12% incentivized conversion rate.
⦁ Assisted and collaborated with the marketing team to develop data-driven insights and actionable recommendations.

Marketing Data Analyst Intern at BYJU’s | Abu Dhabi, UAE Jan. 2021 - June. 2021
⦁ Conducted detailed market research to understand target demographics and customer behaviour.
⦁ Analyzed data from various campaigns to identify trends and optimize marketing strategies.
⦁ Utilized statistical tools to evaluate the effectiveness of marketing pitches, leading to a 12% incentivized conversion rate.
⦁ Assisted and collaborated with the marketing team to develop data-driven insights and actionable recommendations.

Conducted detailed market research to understand target demographics and customer behaviour.
Analyzed data from various campaigns to identify trends and optimize marketing strategies.
Utilized statistical tools to evaluate the effectiveness of marketing pitches, leading to a 12% incentivized conversion rate.
Assisted and collaborated with the marketing team to develop data-driven insights and actionable recommendations.