Welcome to my GitHub profile! I'm an engineering student at INSAT Tunisia, specializing in Computer Networks and Telecommunications with a focus on Machine Learning, Deep Learning, and Data Science. I work on Computer Vision, Natural Language Processing (NLP), and Large Language Models (LLMs), with a particular interest in advancing model capabilities. I also have knowledge in MLOps, focusing on streamlining AI workflows. I'm passionate about research and staying updated on the latest in AI. Currently, I'm working on advanced LLM projects and exploring emerging technologies.
- ⭐ Ranked in the top 3 of my academic class.
- ⭐ Reached the benchmark for the ASVspoof Deepfake Detection competition.
- Languages: Python, Matlab, JavaScript, C, Java, SQL, Bash
- Frameworks & Libraries: PyTorch, TensorFlow, Keras, Scikit-learn, Pandas, Numpy, Matplotlib, NodeJs, FastAPI, Tkinter
- Machine Learning & Deep Learning: Regression, Decision Trees, Random Forests, SVM, Neural Networks, CNN, RNN, MLP, Transformer, ResNet, ViT, YOLO, RCNN
- Data Science: Data Analysis, Data Cleaning, Data Augmentation, Feature Engineering, Data Visualization
- Model Fine-tuning & Agents: Fine-tuning and deploying large language models (LLMs) using LangChain, LangGraph, and OpenAI GPT. Experienced with models such as LLaMA, DeBERTa, BERT, T5, and Phi3, as well as techniques like LoRA and QLoRA for efficient parameter tuning. Proficient in Prompt Engineering and building Retrieval-Augmented Generation (RAG) systems for enhanced model performance. Skilled in designing multi-agent systems using MultiChain for complex, dynamic workflows.
- Web Development: NestJs, Angular, JavaScript, HTML, CSS
- DevOps: Git, Docker, Docker Compose, GitHub, GitLab, Containerization
- Networking: LAN, WAN, Basic Configuration and Security
- Cloud: Azure
- Agent in LangGraph — DeepLearning.AI Specialized certification focused on building agents using LangGraph for advanced AI workflows.
- Deep Learning Specialization — DeepLearning.AI Comprehensive expertise in deep learning fundamentals, including CNNs, RNNs, and advanced neural network architectures.
- Machine Learning Specialization — DeepLearning.AI Mastery in foundational machine learning algorithms and techniques, including supervised learning, unsupervised learning, and deep learning.
- Effective MLOps — Weights and Biases Demonstrated proficiency in MLOps, focusing on machine learning pipeline optimization, version control, and production deployment.
- AZ-900: AI Fundamentals — Microsoft Certified in AI fundamentals, covering core AI concepts, machine learning, and Azure AI services.
- AZ-900: Azure Fundamentals — Microsoft Certified in Azure cloud fundamentals, including core cloud services, architecture, and basic implementation.
- CCNA: Introduction to Networks & Switching, Routing, and Wireless Essentials — Cisco Proficiency in networking fundamentals, including LAN/WAN setup, routing protocols, switching, and wireless technologies.
- Fortinet Network Security Expert (NSE) Levels 1, 2, and 3 Certified expertise in Fortinet security solutions, with strong knowledge of network security protocols and implementation strategies.
- JavaScript Algorithms and Data Structures — freeCodeCamp Comprehensive understanding of JavaScript algorithms, data structures, and their applications in software development.
- Email: [email protected]
- LinkedIn: Haykel Bargougui
- GitHub: HaykelBargouguy