Certifications

Courses and Certifications

Programming Language

• Programming for Everybody (Getting Started with Python) : University of Michigan, Grade: 99.17
• Introduction à la programmation orientée objet (en Java): EPFL, Grade: 95.34
• Getting Started with AWS Machine: AWS, Grade 100

Data science

• What is Data Science : IBM, Grade: 97.00
• Databases and SQL for Data Science with Python: IBM, Grade: 100.00

Data Analysis

• Data Analysis with Python: IBM, Grade: 95.64

Hyper Parameter Tuning

• Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: DeepLearning.AI, Grade: 99.20
• Neural Networks and Deep Learning: DeepLearning.AI, Grade: 95.70

Natural Language Processing

• NLP with Classification and Vector Spaces: DeepLearning.AI, Grade: 100.00
• Applied Text Mining in Python: University of Michigan, Grade: 93.05

Unsupervised Learning

• Clustering Geolocation Data Intelligently in Python: Coursera Project Network, Grade: 100.00

Computer Vision

• Emotion AI: Facial Key-points Detection: Coursera Project Network, Grade: 100.00
• AI for Medical Prognosis: DeepLearning.AI, Grade: -
• AI for Medical Diagnosis: DeepLearning.AI, Grade: 100.00
• AI for Medical Treatment: DeepLearning.AI, Grade: 100.00
• Classification with Transfer Learning in Keras: Coursera Project Network, Grade: 100.00
• Generate Synthetic Images with DCGANs in Keras: Coursera Project Network, Grade: 100.00
• Emotion AI: Facial Key-points Detection: DeepLearning.AI, Grade: 100.00

Skills

Machine Learning

• Tools: TensorFlow, Sklearn, Transformers, PyTorch

Computer Vision

Natural Language Processing (NLP)

• Tools: TensorFlow, Sklearn, Transformers, PyTorch, GLiNER

Data Science

Courses

Programming Language

• Programming for Everybody (Getting Started with Python): University of Michigan, Grade: 99.17
• Introduction à la programmation orientée objet (en Java): EPFL, Grade: 95.34
• Getting Started with AWS Machine: AWS, Grade: 100

Data Science

• What is Data Science: IBM, Grade: 97.00
• Databases and SQL for Data Science with Python: IBM, Grade: 100.00

Data Analysis

• Data Analysis with Python: IBM, Grade: 95.64

Hyperparameter Tuning

• Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: DeepLearning.AI, Grade: 99.20
• Neural Networks and Deep Learning: DeepLearning.AI, Grade: 95.70

Natural Language Processing

• NLP with Classification and Vector Spaces: DeepLearning.AI, Grade: 100.00
• Applied Text Mining in Python: University of Michigan, Grade: 93.05

Unsupervised Learning

• Clustering Geolocation Data Intelligently in Python: Coursera Project Network, Grade: 100.00

Computer Vision

• Emotion AI: Facial Key-points Detection: Coursera Project Network, Grade: 100.00
• AI for Medical Prognosis: DeepLearning.AI, Grade: -
• AI for Medical Diagnosis: DeepLearning.AI, Grade: 100.00
• AI for Medical Treatment: DeepLearning.AI, Grade: 100.00
• Classification with Transfer Learning in Keras: Coursera Project Network, Grade: 100.00
• Generate Synthetic Images with DCGANs in Keras: Coursera Project Network, Grade: 100.00

Portfolio

Projects

1. Fine-Tuning GLiNER for Location Mention Recognition (LMR)
   Published: September 01, 2024
   Fine-tunes the GLiNER model to enhance the recognition and classification of location mentions in text data for improved disaster response.

2. Specializing Large Language Models for Telecom Applications
   Published: July 01, 2024
   Enhances the accuracy of Falcon 7.5B and Phi-2 on telecom knowledge using the TeleQnA dataset.

3. Object Detection Using Transformers
   Published: May 01, 2024
   Develops a machine learning algorithm for accurate counting of roof types in rural Malawi using aerial imagery.

4. Semi-Supervised Learning with Few Labels
   Published: January 01, 2023
   Improves the performance of self-supervised learning models in scenarios with limited labeled data.

5. Continual Self-Supervised Learning through Distillation and Replay
   Published: September 01, 2022
   Addresses the challenges of continual learning in self-supervised learning by using distillation, proofreading, and a prediction layer.

6. Financial Data Generation
   Published: December 01, 2021
   Generates synthetic financial data for various applications.

7. Constraints Optimization of Resources Used by Tasks in Workflows
   Published: September 01, 2021
   Optimizes resource usage in workflows to enhance efficiency.

8. NER for Commands Extraction
   Published: June 01, 2021
   Extracts commands from text data using Named Entity Recognition techniques.

9. Users’ Understanding Queries
   Published: September 01, 2020
   Focuses on improving user query understanding for enhanced interaction.