Machine Learning Specialization

Stanford University | Oct 2024 - Mar 2025

• Built robust ML models using NumPy and scikit-learn for prediction and binary classification (linear, logistic regression).
• Developed and trained neural networks with TensorFlow for multiclass classification, incorporating decision trees and ensemble methods.
• Applied ML best practices and utilized unsupervised learning techniques (clustering, anomaly detection).
• Constructed recommender systems via collaborative filtering and content-based deep learning, along with a deep reinforcement learning model.

Professional Project-Oriented Course in ML With Python

Quera | Aug 2024 - Dec 2024

• Mastered project management tips for ML workflows.
• Executed data preparation and feature engineering.
• Implemented various regression and classification techniques.
• Conducted model evaluation, selection, and regularization.
• Developed Artificial Neural Networks and gained an introduction to Natural Language Processing.
• Applied unsupervised learning and clustering methods.

Task-Oriented Course in Data Analysis With Python

Quera | Jul 2024 - Nov 2024

• Proficient in data cleaning and preparation techniques.
• Skilled in data analysis and interpretation of results.
• Adept at creating compelling data visualizations.
• Extensive experience with NumPy, Pandas, Matplotlib, and Seaborn libraries.

Professional Project-Oriented Course in Natural Language Processing

Quera | Jul 2025

• Basic Text Processing in Python and Text Preprocessing with NLTK
• Working with Regular Expressions (Regex)
• Introduction to the Text Processing Pipeline in spaCy
• Advanced Tokenization (spaCy, Subword, Byte-Pair)
• Statistical Text Representation (One-hot, Bag of Words, Tf-Idf)
• Text Classification with Machine Learning
• The Concept of Language Model and the N-gram Method
• Word Embedding and Introduction to Gensim

Databases and SQL for Data Science

IBM | Nov 2024 - Jan 2025

• Mastered creating, deleting, and modifying databases and tables.
• Proficient in retrieving, deleting, and modifying data.
• Skilled in filtering and grouping data for analytical purposes.
• Adept at joining tables and optimizing data processing.
• Utilized built-in functions for data manipulation and explored advanced concepts like views and stored procedures.

Task-Oriented Course in Version Control With Git

Quera | Jan 2025

• Proficient in installing and running Git.
• Mastered basic Git commands (pull, push, commit).
• Skilled in working with branches, merge, and rebase operations.
• Adept at diagnosing and correcting repository errors.
• Experienced with supplementary commands (stash, cherry-pick) and platforms like GitHub and GitLab.

Persian Financial Chatbot

Persian Financial Chatbot is an AI-powered assistant built with Streamlit that delivers real-time financial insights in Persian. Users can sign up, log in, and track their chat history, making it easy to manage past queries. It provides up-to-date market data—including stock prices, currency exchange rates, and gold values—through intuitive charts and conversational responses. Designed for Persian-speaking users, it offers a seamless and interactive financial information experience..

News Text Classification

This project implements a machine learning-based news text classification system. The goal is to categorize news articles into predefined categories (e.g., sports, politics, business) using their content. The project leverages various natural language processing (NLP) techniques for text preprocessing and machine learning models for accurate classification. Implemented in Python and Jupyter notebooks, it offers a clear and interactive demonstration of the underlying logic.

Salary-Prediction

I built a machine learning model to predict whether an individual earns more than $50K per year using the UCI Adult Income dataset. The project involved end-to-end data handling — from importing and cleaning raw data to feature engineering and preprocessing. I explored demographic patterns through visualizations and applied several classification algorithms, including Logistic Regression, Decision Tree, and Random Forest. To enhance performance, I implemented hyperparameter tuning using GridSearchCV and cross-validation, which significantly improved model accuracy. The XGBoost model emerged as the top performer with an accuracy of ~86%. I also conducted a model comparison based on precision, recall, and F1-score to ensure balanced performance. This project helped me deepen my understanding of supervised learning pipelines and real-world data handling.

Portfolio Management System

Designed to assist individuals and institutions in effectively managing their investment portfolios. The system enables users to track and analyze assets, evaluate portfolio performance, and make data-driven investment decisions. With a focus on data analysis, risk management, and visualization, the system helps users understand investment performance and assess associated risks.

Java Store Application

An online store application reminiscent of major e-commerce platforms. Developed in Java, this project features a comprehensive graphical user interface (GUI) and integrates with a MySQL database. It employs various methods for efficient program management, highlighting the importance of Object-Oriented Programming (OOP) and adhering to principles such as SOLID.