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Hi, I am Hafsa

TAUIL Hafsa

computer engineering student at ENSA

My name is TAUIL Hafsa, born in 2004. I earned a Mathematics B Baccalaureate in 2021, followed my studies as an MP student in CPGE, and am currently pursuing a degree in computer engineering at ENSATE. My passion lies in exploring the realms of Data Science and Artificial Intelligence, challenging by wonder to make machines able to think, behave, and analyze like a human brain..

Problem Solving
Fast Learner
Critical thinking
Story telling
Adaptability
Curiosity

Education

2023-Present
Computer engineering student
Baccalaureate in Mathematical Science

Skills

Projects

Automaton manipulation
Developer 2024

I developed a program capable of reading and storing in memory an automaton A from a .txt file. Subsequently, I implemented some basic algorithms for automaton manipulation.

CGIAR Eyes on the Ground Challenge Zindi Competition
Developer 21 July 2023 - 03 November 2023

The objective of this challenge was to create a machine learning model to Predict drought damage from smartphone images of crops.

Drowsiness detection while driving
Developer 2023

I developed a comprehensive solution to prevent drivers from falling asleep while driving, utilizing the power of deep learning (PyTorch) and OpenCV.

Accomplishments

Generative AI for Everyone

This course will introduce you to the fascinating world of generative AI, covering what it is, how it works, and its common use cases. You’ll explore the capabilities and limitations of generative AI technologies, understanding what they can and cannot do. Additionally, you’ll learn to navigate the lifecycle of a generative AI project, from conception to launch, including building effective prompts to guide the generative process. Moreover, you’ll examine the potential opportunities and risks that generative AI technologies present to individuals, businesses, and society, gaining a comprehensive understanding of this rapidly evolving field.

Advanced Learning Algorithms

In this comprehensive course, you’ll learn to build and train neural networks using TensorFlow for multi-class classification tasks. You’ll also discover best practices for machine learning development, ensuring that your models generalize well to real-world data and tasks. Additionally, you’ll master decision trees and tree ensemble methods, including random forests and boosted trees, to further enhance your machine learning skills. By the end of the course, you’ll be equipped with the knowledge and techniques to tackle a variety of machine learning challenges effectively.

Supervised Machine Learning

This course is designed to provide you with the essential skills to build machine learning models in Python using popular libraries such as NumPy and scikit-learn. You’ll learn to build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression. By the end of the course, you’ll be proficient in using these libraries to tackle real-world problems and build robust machine learning models with confidence.