Housing Prices Prediction-Kaggle Learn Users Competition
Summary
Used a Random Forest regression model to predict house prices. Achieved a Mean Absolute Error (MAE) score of 21217.9 on the public leaderboard.
Analytical and detail-oriented aspiring Data Scientist with a strong foundation in Python, data analysis, and statistical problem-solving, complemented by a background in microbiology, customer service, and education. Equipped with hands-on training from intensive bootcamps, industry-recognized certifications, and ongoing diploma studies in data science. Passionate about transforming raw data into actionable insights through cleaning, visualization, and predictive modeling. Combining critical thinking, adaptability, and clear communication honed through collaborative and client-facing roles, to deliver impactful solutions in fast-paced environments. Eager to contribute technical skills and a growth mindset to a team-driven data science initiative.
Higher National Diploma (HND)
Microbiology
→
Online
Diploma in Data Science (In Progress)
Python, SQL, MATLAB.
pandas, NumPy, scikit-learn, Matplotlib, Seaborn, TensorFlow, Jupyter,Google Colab,Git.
Verbal & Written Communication, Teamwork, Customer Service, Collaboration, Presentation Skills.
Time Management, Multitasking, Adaptability.
Critical Thinking, Analytical skills.
Issued By
UC San Diego (Coursera)
Issued By
ALX Africa
Issued By
University of Texas, Permian Basin
Issued By
IBT Learning Africa
Native
Summary
Used a Random Forest regression model to predict house prices. Achieved a Mean Absolute Error (MAE) score of 21217.9 on the public leaderboard.
Summary
Used NLP techniques (tokenization, lemmatization, and stemming ) to analyze IMDB movie reviews. Built a logistic regression model to classify reviews as positive or negative. Achieved 90% accuracy on the test set. Created an interactive web app using Streamlit for real-time sentiment prediction with word clouds for visual insights.
Teller/Customer Service Representative
Summary
Managed daily customer interactions and resolved complex issues to enhance satisfaction and retention.
Highlights
Process Optimization: Enhanced customer satisfaction scores by collaborating with team members to provide exemplary service and promptly addressing inquiries, increasing customer retention, and receiving positive feedback.
Technical Adaptation: Leveraged banking software to process transactions accurately, demonstrating attention to detail and comfort with data systems.
Data-Driven Problem-Solving: Resolved over 80 customer inquiries daily by maintaining up-to-date product knowledge and working closely with colleagues to solve problems, increasing customer satisfaction, and reducing follow-up inquiries.
Basic Science/Health Education Teacher
Summary
Developed and delivered comprehensive science curricula, improving student performance and engagement.
Highlights
Data-Informed Instruction: Improved student test scores by analyzing performance trends and adapting lesson plans to target knowledge gaps.
Visual Communication: Designed engaging presentations and visual aids to simplify complex scientific concepts.
Collaborative Analysis: Worked with staff to evaluate curriculum effectiveness using student feedback and grading data.