Mir Abir Hossain

Developed an automated system using OCR and LLM for invoice data extraction, integrating it with Microsoft Dynamics Business Central via Power Automate. Created a custom chatbot with a GPT model and client data using RAG on Azure platform.

Taught the first half of CS106A: Introduction to Python to new coders. Guided students through mini-projects on functional programming, object-oriented programming, and data analysis with pandas.

Developed a customer complaint analysis dashboard using Flask, HTML, CSS, Bootstrap, JavaScript, and Python. Implemented a PI for the myBL app using FastAPI and MySQL database, and automated reports with Power Automate and Python.

Trained a CNN model to construct 3D building roof models from 2D satellite images and point cloud data for solar energy optimization. Built a CNN model to classify 7 different diseases and healthy mango leaves, achieving 95% accuracy.

Focused on Intelligent Radio Service Engineering with a specialization in Automation and AI. This program provided advanced knowledge in computing and its applications in modern communication systems.

Currently pursuing a course in Machine Learning in Production, focusing on deploying and managing machine learning models in real-world environments. This course covers best practices for ML operations and scalability.

Completed a comprehensive curriculum in Civil Engineering, gaining foundational knowledge in various engineering principles and practices. This degree provided a strong analytical and problem-solving background.

Activities and societies: Completed 4 mini projects on functional programming, object-oriented programming, and data analysis with pandas.

Undertook a course in Applied Data Science, focusing on practical applications of data analysis. Completed mini-projects on functional programming, object-oriented programming, and data analysis with pandas.

Activities and societies: Total 4 courses: Machine Learning, Deep Learning, Generative AI, Computer Vision and Natural Language Processing.

Completed a microdegree focusing on Artificial Intelligence, covering key areas such as Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing. Developed practical skills in AI model development and application.

Activities and societies: Introduction to CNN, RNN, LSTM, Attention model in NLP, Reinforcement Learning, Introduction to PyTorch.

Completed an introductory course to Machine Learning, covering fundamental concepts and algorithms. Gained a solid understanding of the principles behind machine learning models.

Activities and societies: Completed 2 mini projects on machine learning algorithms and natural language processing.

Engaged in an Applied Data Science course, completing mini-projects focused on machine learning algorithms and natural language processing. Developed practical skills in implementing and applying these techniques.