Business Success
Through Data-Analysis and Insightful Strategies
Hello, I'm Muhammad Nouri, a former MBA student and a chemical engineer with a passion for data science and analytics. After earning my bachelor's degree in Chemical Engineering, I embarked on a journey that led me to the world of data analysis.
While pursuing an MBA, I discovered that my true passion lay in harnessing the power of data. This realization prompted me to transition from business studies to the world of data science after quitting MBA. I dedicated myself to mastering the art of advanced Python programming and honing my skills in supervised and unsupervised machine learning algorithms. Additionally, I have attained an advanced level of proficiency in PostgreSQL and familiarity with MongoDB, a solid understanding of Git as well familiarity with FastAPI, HTML, and CSS.
Comfortable operating within a Linux environment, I am committed to evolving into a top-tier data scientist. My unwavering aspiration is to leverage my expertise to make meaningful contributions to the field while continually striving for excellence in the realm of data science. I am thrilled by the endless possibilities presented by data and am determined to carve out a distinguished career in data science, with the ultimate goal of becoming one of the foremost data scientists in the world.
My key areas of expertise.
I am proficient in advanced Python programming, with experience in both supervised and unsupervised learning techniques. Additionally, I have a solid understanding of PostgreSQL, Linux systems, Git version control, and familiarity with MongoDB, which allows me to effectively manage and analyze large datasets. While I'm familiar with FastAPI, I am comfortable using it for web development projects. Overall, my skills in Python, supervised and unsupervised learning, Linux, Git, PostgreSQL, and MongoDB enable me to handle complex programming and data analysis tasks with confidence.
Python
With advanced proficiency in Python, I am confident in performing data analysis. My experience with Python includes working with various libraries for data manipulation including numpy, pandas, scipy, scikit-learn, ... and visualization including matplotlib and seaborn.
SQL
Proficient in PostgreSQL, I specialize in data manipulation and retrieval using advanced SQL queries, including CRUD operations, complex JOINs, and subqueries. As a data analyst, I have hands-on experience designing and implementing a complete PostgreSQL database for a backend project. While my expertise lies in data analysis rather than database design, I am committed to continuous learning and staying updated on best practices in these areas.
Linux
I possess a solid understanding of Linux systems, including command-line operations, system administration, and shell scripting. My medium-level expertise allows me to navigate and manage Linux environments effectively, install and configure software, and troubleshoot common issues.
Git
With a medium level of knowledge in Git version control, I am comfortable using repositories for collaborative software development, managing branches, merging code, and resolving conflicts. I can effectively utilize Git to track changes in projects and collaborate with team members on codebases.
Supervised and Unsupervised Learning
Proficient in advanced supervised and unsupervised learning techniques, I have the capability to develop and implement machine learning models for classification, regression, clustering. My expertise includes feature engineering, model evaluation, and selecting appropriate algorithms for different types of datasets.
HTML and CSS
While I have a familiarity with HTML and CSS, I am able to edit and improve any kind of template files and format it to be used for any purpose.
Recent Projects
An automated machine learning project. It starts by scraping data of house prices and saves data in postgresql; then proceeds to cleaning, transforming and finally finding the best algorithm to be used for prediction.
An automated ANN project. It starts by scraping data and saving them in MongoDB; then it initiates the neural network model training, train and saves the model alongside the preprocessor object in a folder called "data", and lastly runs the GUI for user input and makes prediction based on the created model.
This project contains the following steps: cleaning the data, Extracting the rules and recomendation system to recommend 3 products the user based on his previous choices.
This project contains a backend for a hotel reservation website using "SQLAlchemy", "PostgreSQL" and "FaseAPI". There is an schematic image of database created by pgadmin that shows the dynamic of database