About
I am Jaouad Chakir, a software engineer and deep learning enthusiast based in Morocco. I specialize in backend development and building scalable, efficient systems using Python, TypeScript, and C++. My skills include developing RESTful APIs, working with frameworks like Django and NestJS, and deploying containerized applications with Docker.
I am also passionate about deep learning and enjoy solving real-world problems through data analysis, models fine-tuning, or even models selection. I have experience with neural networks, and other Deep Learning algorithms, using tools like NumPy, Keras, and PyTorch.
I am currently a student at 1337 Coding School (42 Network), where I focus on enhancing my skills in software engineering and deep learning. My GitHub projects showcase my work in backend systems, machine learning models, and algorithm development.
When I’m not coding, I explore advanced technologies to find innovative solutions to everyday challenges, or simply play football.
Education
1337 Coding School
2021 - 2024
Learned advanced problem-solving and collaboration skills through peer-based challenges.
BTS Al Khawarizmi
2017 - 2019
Gained in-depth knowledge in Linux, network design, and CCNA 200-301 fundamentals.
Experience
AI Intern at Sofrecom Morocco
Feb 2024 - Aug 2024
- Explored AI model training and data optimization workflows.
- Developed an automated tag prediction system using XGBoost.
- Improved machine learning algorithms and neural networks to increase accuracy.
Backend Developer Intern at Sofrecom Morocco
Feb 2023 - Sep 2023
- Built scalable RESTful APIs with Django and optimized query performance.
- Integrated AI/ML models into applications to generate predictions.
Projects: Software-Engineering
Transcendence: Online Ping-Pong
Real-time multiplayer game with chat features
Inception: Microservices Architecture
Built a microservices architecture with Docker, implementing Nginx for load balancing.
Containers: STL-like Container Implementation
Recreated STL containers like vector and map using C++ templates and Red-Black Trees.
WebServ: HTTP Server
Developed a reliable HTTP server using C++ sockets and Linux syscalls for connection management.
Projects: Machine-Learning
Tagma: Automated Tag Prediction
Developed a model to predict project tags using XGBoost
MLP: Multi-Layer Perceptron
Built a neural network from scratch for classification tasks, optimizing parameters for enhanced efficiency.
Tweets: NLP and Sentiment Analysis
Processed tweet data to classify sentiment and employed various ML algorithms for analysis.
Churn: Bank Data Processing and Models Training
Banking data preprocessing and training multiple Machine Learning models, including Naive Bayes, Random Forest, and MLP.
Technical Skills
Programming Languages
Frameworks
Machine Learning Tools
Tools & Technologies
Skills
Languages
Arabic
Native
English
Upper Intermediate
French
Intermediate