Hello, my name is Madueke
I' m a Data Scientist
A dedicated professional specializing in transforming raw data into actionable insights. With expertise in, data analysis, data science, machine learning, deep learning, Generative AI, and web analytics, I excel at uncovering patterns and trends to drive informed decision-making and innovation. Explore my portfolio to see projects that address complex challenges with data-driven solutions, including predictive modeling, big data analytics, interactive dashboards, and elegant visualizations. My ultimate goal is to leverage these skills and experiences to become a Chief Technology Officer, driving technological innovation and strategic growth.
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About Me
I'm Madueke a Data Scientist
As a seasoned Data Analyst and Data Scientist, I bring a rich blend of education, professional experience, and expertise in tools like TensorFlow, Power BI, Tableau, Python, and more, showcased through my projects, skills, and a professional introduction video.
Birthday : 28 Oct
Website : riteclick.com.ng
Degree : B-Eng
City : Asaba, Delta State.
Phone : 07062535775
Email : maduekedickson@gmail.com
Freelance : Available
Pandas
Scikit-Learn
Matplotlib
Power BI
TensorFlow
Education
2024 - 2025
Masters in Information Management
Ahmadu Bello University, Zaria
Nigeria.
2014 - 2018
Degree in Electrical Electronics Engineering
Federal University of Technology,
Owerri
Nigeria.
2011 - 2013
Diploma in Electrical Electronics Engineering
Federal Polytechnic, Damaturu
Nigeria.
Experience
2023 - Date
Data Scientist/Analyst
Schoolville Academy
2020 - 2023
Digital Marketing Analyst
Schoolville Limited
2019 - 2020
Field Researcher
Nielsen
Services
Data Science
Leveraging machine learning, deep learning, and statistical analysis to extract actionable insights and drive data-driven decision-making.
Data Analytics
Transforming raw data into meaningful insights through advanced analytics techniques and interactive visualizations.
Cloud Computing
Deploying scalable and efficient data solutions on cloud platforms for seamless data storage, processing, and analysis.
Data Engineering
Designing, building, and maintaining robust data pipelines and architectures to ensure smooth data flow and integrity.
Frontend Webdev
Creating engaging and responsive web interfaces using modern frameworks and technologies for an optimal user experience.
Web Analytics
Analyzing web data to optimize user experience, track performance metrics, and drive strategic business decisions using Google Analytics and Tag Manager.
Portfolio
My Latest Projects :
Power BI
Exploring UEFA Champions League Historical Dataset
This project delves into the rich history of the UEFA Champions League, analyzing data to uncover trends, team performances, and player statistics across different eras of the competition.
Power BI
Insights from Netflix Viewing Data
This project involved analyzing Netflix data to identify viewing trends, popular genres, user preferences, and regional content performance, offering actionable insights into audience behavior.
Power BI
Analyzing Delta State Bursary Registration Data 2024
This project focused on analyzing student registration data for the Delta State bursary scheme to uncover trends in application rates, demographic distributions, and eligibility patterns, providing insights to improve program efficiency for the Delta State Government.
Python, Pandas, Scikit-learn
Career Recommendation System for Students
Developed a recommendation system that suggests suitable courses for students based on their high school subject scores. The system leverages machine learning to align students' strengths with potential academic paths.
Python, Machine Learning, Scikit-Learn
Diabetes Prediction Model
Built a machine learning model to predict the likelihood of diabetes based on health metrics such as glucose levels, BMI, and age. This project aims to support early detection and preventive healthcare measures.
Power BI
FIFA World Cup Data Analysis and Dashboard
Conducted an in-depth analysis of the FIFA World Cup dataset and developed an interactive Power BI dashboard to visualize team performance, player statistics, and tournament trends, providing actionable insights for football enthusiasts and analysts.
Python, Machine Learning, Spotify API
Music Recommendation System Using Cosine Similarity
Developed a music recommendation system using the cosine similarity method to suggest songs based on user preferences. Integrated Spotify API to fetch album cover images for recommended tracks, enhancing the user experience.
Python, Deep Learning, TensorFlow
Cat and Dog Image Classifier Using TensorFlow
Created an image classification model using TensorFlow to distinguish between cat and dog images. The project involved training a convolutional neural network (CNN) on labeled datasets to achieve high accuracy in image recognition.
Python, Machine Learning
Movie Recommendation System Using Cosine Similarity
Built a movie recommendation system using the cosine similarity method to suggest movies based on user preferences. Integrated the TMDB API to fetch movie cover images, enhancing the recommendation experience with visual elements.
Python, Seaborn
Heart Disease Prediction with Dockerized ML Model
Developed a machine learning model to predict the likelihood of heart disease based on patient data. The model was containerized using Docker for seamless deployment and scalability, making it accessible for real-world healthcare applications.
Google Analytics, Google Tag Manager, Power BI
Web Analytics for Schoolville Website with Power BI
Conducted a web analytics analysis on the Schoolville website, extracting key metrics through Power BI. Designed and developed an interactive dashboard to track user engagement, page performance, and traffic sources, providing valuable insights for improving website optimization and user experience.
Python, Beautifulsoup
Portfolio Website Chatbot with Web Scraping
Built a chatbot that web scrapes my portfolio website to generate relevant answers and content. The bot interacts with users, providing information and insights based on the data scraped from the website, enhancing user engagement and experience.
Python, Scikit-Learn, Machine Learning
Loan Approval Prediction Application
Developed a loan approval prediction application that uses machine learning to assess the likelihood of loan approval based on applicant data such as income, credit score, and loan amount, streamlining the decision-making process for financial institutions.
Python, Machine Learning
Medical Insurance Charge Prediction Model
Created a predictive model to estimate medical insurance charges based on factors such as age, BMI, smoking habits, and region. This model helps insurance companies assess risk and set appropriate premiums for clients.
Python, Machine Learning
Udemy Course Recommendation System
Developed a recommendation system that suggests Udemy courses to users based on their interests, past learning activities, and user ratings. The system helps users find courses tailored to their learning needs and preferences.
Python, Machine Learning
Crop Recommendation System
Built a crop recommendation system that suggests optimal crops for farmers based on factors such as soil type, climate, and historical yield data. The system helps increase agricultural productivity by guiding farmers toward the best crops for their specific conditions.
Power BI
Prime Video Analytics Power BI Dashboard
Analyzed Prime Video viewership data and created an interactive Power BI dashboard to visualize key metrics such as user engagement, popular genres, regional preferences, and content performance, offering insights for improving content strategy and user experience.
Python, NLP
Spam SMS Classifier
Developed a machine learning model to classify SMS messages as spam or not spam based on message content. The classifier uses natural language processing (NLP) techniques to filter out unwanted messages, improving mobile security and user experience.
Python, Machine Learning
Rainfall Prediction Model
Built a machine learning model to predict rainfall patterns based on historical weather data, including temperature, humidity, and pressure. This model helps in weather forecasting and assists in agricultural planning and disaster preparedness.
Python, Folium
Infrastructure Analysis using Folium Map Visualization
Created a map visualization using Folium to analyze and visualize infrastructure, such as the distribution of hospitals in a region. The interactive map highlights key locations, helping in assessing accessibility and planning for infrastructure development.
Python, Machine Learning, Scikit-Learn
Malaria Risk Prediction Model
Developed a machine learning model to predict the likelihood of malaria based on environmental factors, fever, travel history, mosquito exposure, and other risk indicators. Utilized Scikit-learn for model training and evaluation to enhance disease prediction accuracy.