Python Instructor/MentorResagratia | Oct 2022 – Present | RemoteIn my role as a Python Instructor and Mentor at Resagratia, I have:Developed comprehensive online Python courses: Designed to meet the needs of learners with diverse backgrounds, ranging from beginners to advanced students. Each course was crafted to accommodate different learning styles and skill levels.Enhanced educational offerings: Played a pivotal role in expanding course content, helping to attract a broader audience and foster a thriving community of passionate learners.Contributed to company growth: Helped establish Resagratia as a recognized authority in Python programming, significantly contributing to the company’s growth and increasing industry recognition.Mentored data science students: Provided guidance at every data science Bootcamp, and had successfully trained several students who are now experts in Python programming for data science.

Machine Learning Engineer InternCognify Technologies | August 2024 – September 2024As a Machine Learning Engineer intern at Cognify Technologies, I worked on several key projects aimed at leveraging data to drive business insights in the restaurant industry:Predicting Restaurant Ratings: Developed a machine learning model using regression techniques to predict restaurant ratings based on various features. Successfully identified the most influential factors affecting customer ratings.Restaurant Recommendation System: Built a content-based recommendation system that suggested restaurants to users based on their preferences, including cuisine type and price range. Implemented collaborative filtering techniques to improve recommendation accuracy.Location-based Analysis: Performed geographic analysis on restaurant distribution using latitude and longitude data. Visualized and analyzed the concentration of restaurants across cities, uncovering patterns related to average ratings, price ranges, and cuisines by location.Throughout the internship, I gained hands-on experience in data preprocessing, model training, evaluation using metrics like Mean Squared Error and R-squared, as well as geospatial data visualization using Python libraries. I also improved my skills in interpreting model outputs to inform strategic decision-making.

Data Scientist / Machine Learning Engineer (Pollution Prediction Project)Developed regression models: Predicted black carbon and dust particle pollutants over Nigeria using data from 2010 to 2020, employing various regression techniques including simple linear regression, multiple regression, and support vector regression.Applied advanced models: Integrated random forest, logistic regression, decision tree, and random forest models to improve the accuracy of predictions and capture complex patterns in the dataset.Model validation: Ensured the reliability of predictions by validating models with key performance metrics, including the R-squared score, Mean Squared Error (MSE), and Mean Absolute Error (MAE).Utilize simple linear, multiple, and support vector regression techniques. Include random forest, logistic, and decision tree models in the analysis.Validated my models using the R-squared score, Mean Squared Error, and Mean Absolute Error.