Data Professional Salary Prediction Model
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Summary
Developed a regression-based machine learning model to predict salaries for data professionals, leveraging key industry and experience factors.
About
Results-driven AI/ML Engineer with a B.Eng. in Mechatronic Engineering, passionate about leveraging data-driven insights to build intelligent predictive systems. Proficient across the entire machine learning pipeline, from data preprocessing and exploratory analysis to model development, evaluation, and deployment. Currently enhancing expertise through the 3MTT Airtel NextGen AI/ML Engineering programme, with a proven track record in developing real-world classification and regression models and solving complex data challenges.
Work
3MTT Airtel NextGen Cohort (Federal Government of Nigeria Initiative)
|AI/ML Engineering - Professional Training Programme
Kano, Kano State, Nigeria
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Summary
Actively engaged in an intensive, industry-aligned training program focused on machine learning engineering and applied AI, developing practical skills through hands-on projects.
Highlights
Engaged in intensive, industry-aligned training across machine learning engineering and applied AI, mastering advanced algorithms and methodologies.
Executed hands-on projects spanning the full ML pipeline, including supervised/unsupervised learning, data preprocessing, and robust model deployment.
Developed expertise in critical AI/ML topics, including neural networks, advanced feature engineering, and rigorous model evaluation using Python for ML.
Education
Bayero University, Kano (BUK)
Kano, Kano State, Nigeria
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Bachelor of Engineering (B.Eng.)
Mechatronic Engineering
Grade: Second Class
Courses
Specialization: Artificial Intelligence & Machine Learning
Final year focus on AI-driven predictive systems and intelligent engineering solutions
Coursework: Control Systems
Embedded Systems
Signal Processing
Mathematics for AI
Certificates
AI/ML Engineering - Professional Training Programme
Issued By
3MTT Airtel NextGen Cohort (Federal Government of Nigeria Initiative)
Skills
Programming Languages
Python.
Machine Learning
Supervised Learning, Unsupervised Learning, Regression, Classification, Clustering Algorithms, Feature Engineering, Data Preprocessing, Model Evaluation, Hyperparameter Tuning, Predictive Model Development, Machine Learning Pipeline (End-to-End), Neural Networks, Deep Learning Fundamentals (in progress), NLP Fundamentals (in progress).
Data Analysis & Tools
Exploratory Data Analysis (EDA), Data Analysis, Statistical Modelling, Statistics & Probability for ML, Data Visualisation & Storytelling, Pandas, NumPy, Matplotlib, Seaborn.
ML Frameworks & Platforms
Scikit-learn, Google Colab, Jupyter Notebooks.
Version Control
Git, GitHub.
Core Competencies
Problem Solving & Analytical Thinking, Research & Rapid Prototyping, Technical Documentation & Reporting.
Projects
Credit Risk Classification Model
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Summary
Engineered a binary classification model to assess customer credit risk, utilizing comprehensive financial and demographic data for predictive analysis.