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Usama
- Rate Ksh. 4,383
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Number of students Usama has accompanied since arriving at Superprof
Number of students Usama has accompanied since arriving at Superprof
Ksh. 4,383/hr
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1st lesson free
- Computer Basics
- Computer Science
- ICT
- Machine Learning
Python, Data Science & AI Tutor | Machine Learning, Neural Networks & Deep Learning for A-Level and BSc
- Computer Basics
- Computer Science
- ICT
- Machine Learning
Lesson location
About Usama
I help students from all backgrounds (from University of Greenwich and University of Gujrat to GCSE and A-Level Students) to achieve the satisfaction of submitting work you're truly proud of, and the boost to your grades that comes with that!
Having a 1st Class Degree in Computer Science (3.72/4.0) and being awarded the Prime Minister Youth Laptop Scheme and the University of Greenwich International Scholarship for my MSc in Data Science allows me to help you get to the top of your game, whether it's writing a 1st Class Thesis, building a Supervised Machine Learning Model, Unsupervised Categorical Model, or just doing Data Analysis in Python/SQL/R!
At a high level, I cover the following Computer Science and Data Science content from Undergraduate to GCSE and A Level (please click "read more" to get the full scope):
Python Programming (Fundamentals, OOP, pandas, NumPy, scikit-learn, BeautifulSoup, Scrapy)
Machine Learning (Supervised Learning, Unsupervised Learning, Neural Networks, Deep Learning)
Data Science (Data Collection, Data Processing, Data Analysis, Data Visualisation, Predictive Modelling)
Computer Science (Data Structures, Algorithms, Database Systems, SQL, NLP, Bioinformatics)
Web Scraping & Automation (Building scripts and automated data pipelines)
I have mentored and taught students from various backgrounds for over 3 years, with a successful track record of positive outcomes that you can see from my experience as a Volunteer Data Science Mentor and Educational Counsellor.
A bit more about me here:
Usama holds a BS in Computer Science and is currently advancing his expertise through an MSc in Data Science at the University of Greenwich, supported by an International Scholarship. He was awarded the prestigious Prime Minister Youth Laptop Scheme and received merit scholarships four years consecutively for ranking in the top 3 of his cohort. His final year project involved developing a machine learning model to predict protein functions with 85% accuracy, which was recognized as a top thesis, and he has further applied these skills in bioinformatics research on Alzheimer's therapeutics at the University of Veterinary and Animal Sciences, performing molecular docking on 25+ compounds.
Usama's professional experience is uniquely blended between tech and leadership. He has worked as a Web Scraping Intern, developing Python scripts using Scrapy and BeautifulSoup to automate data extraction from 50+ websites, improving data accuracy by 30%, and also served as an Operations Manager, where he coordinated international exam programs (NCC Education, OET, LanguageCert) for over 1,000 candidates and implemented data-driven systems that cut operational costs by 10%.
Usama has always been deeply interested in the process of learning itself. Through his experience mentoring high school students in Python and guiding 100+ students to successful university admissions as a counsellor with a 90% success rate, he has developed a patient, step-by-step teaching methodology. He focuses on ensuring students don't just memorize code, but understand the underlying logic and application, thereby building lasting confidence and practical problem-solving skills.
Usama's first professional roles were in tech and operations, thereafter heading into the education and consultancy world where he worked with international testing bodies and students, across industries including EdTech, Academia, and Environmental Protection.
Usama teaches not just for income, but for the enjoyment of empowering others. He is easy-going, competent, and dedicated, living an active lifestyle in London while balancing his postgraduate studies with tutoring.
Usama is proficient and able to teach subjects including, but not limited to:
Python Programming; Machine Learning; Data Science; Artificial Intelligence; SQL and Database Management; Data Structures and Algorithms; Bioinformatics; Web Scraping and Automation; Natural Language Processing (NLP); Data Visualisation; Statistics for Data Science; Computer Science (GCSE & A-Level); ICT (GCSE & A-Level); OET Test Preparation for Healthcare Professionals.
Usama covers the following courses and tools in rich detail and can help with everything from exam preparation to coursework and baseline understanding:
Programming & Tools:
Python, SQL, R, Jupyter Notebook, Google Colab, Git & GitHub, VS Code, Anaconda, PyMOL, ChemDraw, Scikit-learn, TensorFlow, Pandas, NumPy, Matplotlib.
Core Subject Areas:
Machine Learning & AI: Supervised Learning (Linear/Logistic Regression, SVMs), Unsupervised Learning (K-Means, PCA), Neural Networks, Deep Learning, Model Evaluation, Ensemble Methods.
Data Science: Data Collection & Web Scraping, Data Wrangling & Cleaning, Exploratory Data Analysis (EDA), Statistical Analysis, Predictive Modelling.
Computer Science: Object-Oriented Programming (OOP), Data Structures (Arrays, Linked Lists, Trees, Graphs), Algorithms (Sorting, Searching), Database Systems & Normalization, Software Engineering Principles.
Bioinformatics: Protein Function Prediction, Molecular Docking, Sequence Analysis, Structural Bioinformatics.
Exam Preparation: GCSE Computer Science, A-Level Computer Science, University-level Programming and Data Science Modules, OET Exam for Healthcare Professionals.
Usama covers the following courses in rich detail and can help with everything from exam preparation to coursework and baseline understanding.
Course coverage includes:
Machine Learning & Artificial Intelligence
*Topic: Supervised Learning
Key Topics: Linear Regression, Logistic Regression, Support Vector Machines (SVMs), Decision Trees, Random Forests, Model Evaluation (Accuracy, Precision, Recall, F1-Score, Cross-Validation), Feature Engineering, Hyperparameter Tuning.
Keywords: Regression Analysis, Classification, Predictive Modeling, Overfitting, Underfitting, Training/Test Split, scikit-learn.
*Topic: Unsupervised Learning
Key Topics: Clustering Algorithms (K-Means, Hierarchical), Dimensionality Reduction (PCA, t-SNE), Anomaly Detection, Association Rules.
Keywords: Pattern Discovery, Data Compression, Customer Segmentation, Principal Component Analysis, Silhouette Score.
*Topic: Neural Networks & Deep Learning
Key Topics: Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs) for image data, Recurrent Neural Networks (RNNs) for sequence data, Backpropagation, Activation Functions (ReLU, Sigmoid, Tanh).
Keywords: Deep Learning, TensorFlow, Keras, Image Recognition, Time Series Forecasting, Natural Language Processing (NLP).
Data Science & Analytics
*Topic: Data Wrangling & Preprocessing
Key Topics: Data Cleaning, Handling Missing Values, Data Transformation, Feature Scaling, Data Integration, Using pandas and NumPy.
Keywords: Data Cleaning, ETL (Extract, Transform, Load), Data Quality, Python.
*Topic: Exploratory Data Analysis (EDA) & Visualization
Key Topics: Summary Statistics, Univariate and Bivariate Analysis, Correlation Analysis, Creating plots with Matplotlib and Seaborn (Histograms, Box Plots, Scatter Plots).
Keywords: Data Visualization, Statistical Summaries, Insight Generation, Pattern Identification.
*Topic: Statistical Analysis for Data Science
Key Topics: Descriptive Statistics, Inferential Statistics, Hypothesis Testing, Confidence Intervals, Probability Distributions.
Keywords: A/B Testing, p-values, Statistical Significance, Central Limit Theorem.
Computer Science Fundamentals
*Topic: Programming with Python
Key Topics: Syntax and Semantics, Data Types, Control Structures, Functions, Object-Oriented Programming (OOP), Error Handling.
Keywords: Python, OOP, Classes, Objects, Inheritance, Polymorphism.
*Topic: Data Structures & Algorithms
Key Topics: Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Sorting Algorithms, Searching Algorithms, Time Complexity Analysis.
Keywords: Big O Notation, Algorithm Efficiency, Problem Solving, Technical Interviews.
*Topic: Database Management & SQL
Key Topics: Relational Database Design, SQL Queries, Normalization, Joins, Subqueries, Transactions.
Keywords: MySQL, PostgreSQL, Database Schema, Data Integrity.
Applied Computing & Specialized Domains
*Topic: Web Scraping & Automation
Key Topics: HTML Parsing, HTTP Requests, Data Extraction, Building Scalable Scrapers, Handling Dynamic Content, Legal Compliance.
Keywords: BeautifulSoup, Scrapy, Selenium, Data Pipelines, Automation.
*Topic: Bioinformatics
Key Topics: Biological Data Analysis, Sequence Alignment, Protein Function Prediction, Molecular Docking, Structural Analysis.
Keywords: Biopython, PyMOL, Genomic Data, Computational Biology.
*Topic: Natural Language Processing (NLP)
Key Topics: Text Preprocessing, Sentiment Analysis, Named Entity Recognition, Topic Modeling.
Keywords: NLTK, spaCy, Text Classification, Word Embeddings.
Exam & Curriculum-Specific Support
*Topic: GCSE Computer Science
Key Topics: Algorithms, Programming Fundamentals, Data Representation, Computer Systems, Networks.
Keywords: AQA, OCR, Edexcel, Past Papers, Coursework.
*Topic: A-Level Computer Science
Key Topics: Computational Thinking, Advanced Programming, Data Structures, Theory of Computation, Systematic Approach to Problem Solving.
Keywords: Exam Technique, Project Guidance, NEA.
*Topic: University-Level Projects & Dissertations
Key Topics: Project Planning, Literature Review, Methodology, Implementation, Data Analysis, Report Writing.
Keywords: Final Year Project, Thesis, Research Methods, Academic Writing.
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About the lesson
- Lower Primary
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levels :
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- English
All languages in which the lesson is available :
English
I've helped 100+ students achieve deep understanding and top grades. I use an interactive, project-based approach grounded in practical industry and research experience, not just theory. I employ the Socratic method to guide you to discover solutions yourself, ensuring you understand the first principles behind every line of code, removing the need for rote memorisation.
So whether you're stuck on: Python basics, Data Structures, Supervised Models, Unsupervised Models, Neural Networks, SQL queries, or Web Scraping, I offer personalized lesson plans to get you to the next level.
My teaching is built on a foundation of real-world projects. For my 1st Class BSc Computer Science thesis, I developed the "Smart Protein Function Predictor (SPFP)"—a machine learning model using Python (pandas, scikit-learn, Neural Networks) to analyze protein sequences, achieving 85% accuracy and reducing prediction errors by 20%, which was recognized as a top undergraduate project. Furthermore, I conducted advanced bioinformatics research at the University of Veterinary and Animal Sciences, performing molecular docking on 25+ compounds for Alzheimer's therapeutics using PyMOL and Schrodinger Suites.
Professionally, as a Web Scraping Intern at GulzarSoft, I built scalable Python scripts with Scrapy and BeautifulSoup to extract data from 50+ websites, improving data accuracy by 30% and automating data pipelines. I am proficient in the entire data science stack: Python, SQL, Pandas, NumPy, Scikit-learn, Jupyter, Git, TensorFlow, and PyMOL.
I help students achieve academic and career success in Computer Science, Data Science, and Machine Learning by connecting complex topics to tangible projects and applications, making learning both effective and engaging.
Having graduated with a 1st Class Degree in Computer Science (3.72/4.0) and being a recipient of the Prime Minister's Laptop Scheme and the University of Greenwich International Scholarship, I will show you the proven strategies and efficient learning techniques to master your syllabus and build an impressive portfolio.
At a high level, I cover the following Computer Science & Data Science content from Undergraduate to GCSE and A Level (please click "read more" to get the full scope):
Python Programming (Fundamentals to Advanced)
Machine Learning (Supervised, Unsupervised, Neural Networks)
Data Science & Analytics (SQL, EDA, Statistical Analysis)
Data Structures & Algorithms
Web Scraping & Automation
Database Management & SQL
Bioinformatics (Molecular Docking, Protein Function Prediction)
Natural Language Processing (NLP)
For a full breakdown of each topic I cover, please see the selection below:
Machine Learning & Artificial Intelligence (Python)
*Topic: Supervised Learning
Key Topics: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines (SVMs), Model Evaluation, Cross-Validation, Hyperparameter Tuning.
Keywords: Regression Analysis, Classification, Predictive Modeling, scikit-learn, Overfitting, Precision, Recall, F1-Score.
*Topic: Unsupervised Learning
Key Topics: Clustering (K-Means, Hierarchical), Dimensionality Reduction (PCA, t-SNE), Anomaly Detection.
Keywords: Pattern Discovery, Customer Segmentation, Principal Component Analysis, Data Compression.
*Topic: Neural Networks & Deep Learning
Key Topics: Artificial Neural Networks (ANNs), Backpropagation, Activation Functions, Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs).
Keywords: Deep Learning, TensorFlow, Image Recognition, Natural Language Processing, Sequential Data.
Data Science & Analytics (Python/SQL)
*Topic: Data Wrangling & Exploratory Data Analysis (EDA)
Key Topics: Data Cleaning with Pandas, Handling Missing Data, Feature Engineering, Data Visualization with Matplotlib/Seaborn, Statistical Summaries.
Keywords: Data Cleaning, ETL, Python, Pandas, NumPy, Insight Generation.
*Topic: Database Management & SQL
Key Topics: Relational Database Design, SQL Queries (SELECT, JOIN, SUBQUERIES), Normalization, Transactions.
Keywords: MySQL, PostgreSQL, Database Schema, Data Integrity.
Software Engineering & Development
*Topic: Python Programming
Key Topics: Syntax, Data Structures, Object-Oriented Programming (OOP), Algorithms, Error Handling.
Keywords: OOP, Classes, Inheritance, Polymorphism, Time Complexity.
*Topic: Web Scraping & Automation
Key Topics: HTML Parsing, HTTP Requests, Data Extraction, Building Scalable Scrapers, Legal Compliance.
Keywords: BeautifulSoup, Scrapy, Selenium, Data Pipelines, Automation.
Bioinformatics & Computational Biology
*Topic: Protein Bioinformatics
Key Topics: Protein Function Prediction, Sequence Analysis, Structural Analysis, Molecular Docking.
Keywords: Biopython, PyMOL, Genomic Data, Computational Biology, Drug Discovery.
*Topic: Data Analysis in Biology
Key Topics: Processing Biological Datasets, Statistical Analysis in Research, Visualizing Biological Data.
Keywords: Research Methods, Data Visualization, Statistical Testing.
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Rates
Rate
- Ksh. 4,383
Pack prices
- 5h: Ksh. 20
- 10h: Ksh. 40
online
- Ksh. 4,383/h
free lessons
The first free lesson with Usama will allow you to get to know each other and clearly specify your needs for your next lessons.
- 1hr
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