1st lesson free
Mohamed's profile, diploma and contact details have been verified by our experts
Mohamed
- Rate Ksh. 3,234
- Response 8h
-
Students50+
Number of students Mohamed has accompanied since arriving at Superprof
Number of students Mohamed has accompanied since arriving at Superprof
Ksh. 3,234/hr
Contact
1st lesson free
- Artificial Intelligence
- Machine Learning
Applied AI Research Engineer with 3+ years’ experience teaches machine learning, deep learning, NLP, computer vision, and generative AI
- Artificial Intelligence
- Machine Learning
Lesson location
Super Prof
Mohamed is one of our best Artificial intelligence tutors. They have a high-quality profile, verified qualifications, a quick response time, and great reviews from students!
About Mohamed
Hi, I’m Mohamed, an Applied AI and Research Engineer with a B.Sc. in Communications and Information Engineering from Zewail City of Science and Technology.
I have more than five years of experience across machine learning, deep learning, applied research, AI engineering, and technical projects, alongside over three years of online tutoring experience.
I have supported undergraduate and master’s students, including learners enrolled at Georgia Tech and the University of Maryland, with machine-learning courses, programming assignments, research papers, technical projects, debugging, and academic preparation.
My experience covers the complete AI development process:
Understanding and preparing data
Selecting and implementing appropriate models
Training and evaluating machine-learning systems
Diagnosing poor performance and data leakage
Reading and reproducing research papers
Building NLP, computer-vision, recommendation, and biosignal-processing projects
Developing transformer and generative-AI systems
Building retrieval and agentic AI applications
Deploying AI systems using APIs, databases, caching, queues, and vector search
Designing model evaluations, experiments, and production monitoring
My research experience includes developing customized transformer models for biological sequence generation. My engineering work also includes production AI platforms, retrieval systems, agentic workflows, model evaluation pipelines, and backend infrastructure.
I teach more than library commands. My goal is to help you understand:
Why an algorithm works
Which assumptions it makes
How to select suitable evaluation metrics
Why a model is failing
How to improve an experiment systematically
How research code differs from production systems
Lessons are adapted to your current level and objective. I work with beginners learning Python, university students studying ML or deep learning, researchers working through papers, and engineers building production AI applications.
Lessons are available in English and Arabic.
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About the lesson
- Lower Secondary
- Senior School
- Adult Education
- +9
levels :
Lower Secondary
Senior School
Adult Education
University
Tertiary
Masters
Doctorate
MBA
Beginner
Intermediate
Advanced
Professional
- English
All languages in which the lesson is available :
English
Machine learning is not learned by copying notebooks or memorizing framework functions. In our lessons, you will build a clear understanding of the underlying concepts and then apply them through code, experiments, debugging, and practical projects.
I can help you with a complete learning path, a specific university topic, a research paper, an existing project, or a technical problem blocking your work.
How lessons are structured
The first session begins with an assessment of your current knowledge, target, and technical gaps. We then create a focused plan instead of following a generic course.
A typical lesson includes:
Reviewing the problem and required background
Explaining the concept visually and mathematically
Implementing it together in Python
Testing the implementation and interpreting results
Debugging mistakes or model-performance issues
Summarizing the lesson and defining the next practical step
You will write and reason about the code during the lesson. I will guide you through the process rather than simply providing finished answers.
Machine-learning foundations
We can cover:
End-to-end machine-learning workflows
Data cleaning and preprocessing
Exploratory data analysis
Feature engineering and feature selection
Regression and classification
Decision trees and ensemble methods
Support vector machines and nearest-neighbour methods
Clustering and dimensionality reduction
Cross-validation
Hyperparameter optimization
Regularization
Class imbalance
Data leakage
Error analysis
Model interpretation
Mathematics and statistics for AI
Topics can include:
Linear algebra for machine learning
Probability and distributions
Statistics and hypothesis testing
Calculus and gradients
Loss functions
Optimization
Gradient descent and backpropagation
Bias and variance
Overfitting and generalization
Understanding evaluation metrics correctly
The mathematics is taught at the depth required for your goal. Beginners can focus on intuition, while advanced learners can work through derivations and implementations.
Deep learning
We can study and implement:
Neural-network fundamentals
Forward and backward propagation
Optimization algorithms
Activation and loss functions
Convolutional neural networks
Recurrent neural networks
Attention mechanisms
Transformers
Transfer learning
Fine-tuning
Parameter-efficient fine-tuning
Embeddings and representation learning
Training stability and experiment debugging
PyTorch is my primary framework for advanced deep-learning work, but I can also support TensorFlow-based courses and projects.
Natural language processing and generative AI
Topics include:
Text preprocessing and tokenization
Word and sentence embeddings
Text classification
Semantic similarity
Information retrieval
Sequence-to-sequence models
Attention and transformers
BERT, T5 and related architectures
Language-model fundamentals
Prompt design and structured outputs
Model fine-tuning
Retrieval-augmented generation
Vector databases and embedding search
Tool-calling and agentic workflows
LLM evaluation
Hallucination and reliability analysis
Guardrails and AI-system safety
Computer vision
We can cover:
Image preprocessing
Image classification
Convolutional neural networks
Transfer learning
Data augmentation
Object-detection fundamentals
Segmentation fundamentals
Vision transformers
Model evaluation
Handling limited or imbalanced image datasets
Debugging training and generalization problems
Reinforcement learning
I can support reinforcement-learning foundations, including:
Agents, environments, states, and actions
Rewards and return
Markov decision processes
Value-based learning
Q-learning
Policy-based methods
Exploration versus exploitation
Implementing introductory environments and agents
For advanced reinforcement-learning research, contact me with the specific topic or paper before booking.
Research and academic support
I can help you:
Understand difficult research papers
Break equations and architectures into manageable steps
Reproduce published methods
Design controlled experiments
Establish suitable baselines
Select metrics
Conduct ablation studies
Diagnose invalid experimental conclusions
Organize a thesis or research project
Review methodology and technical writing
Prepare research presentations
Support is educational and collaborative. I will help you understand and improve your work rather than complete graded work on your behalf.
AI engineering and production systems
For learners moving beyond notebooks, lessons can cover:
Structuring maintainable ML projects
Building inference APIs
FastAPI-based model serving
Batch and asynchronous processing
PostgreSQL and Redis integration
Vector databases and retrieval systems
Dockerized deployment
Experiment tracking
Model and prompt versioning
Evaluation pipelines
Logging, monitorin,g and observability
Testing AI applications
Moving from a prototype to a production-ready system
Tools and technologies
Depending on the project, we may work with:
Python
NumPy and pandas
scikit-learn
PyTorch
TensorFlow
Hugging Face
OpenCV
Matplotlib
Jupyter and Google Colab
FastAPI
PostgreSQL
Redis
Docker
Vector databases and retrieval frameworks
Tools are selected based on the problem. The objective is not to memorize libraries, but to develop skills that remain useful when frameworks change.
Who these lessons are for
Lessons are suitable for:
Beginners entering AI or machine learning
University students
Master’s students and researchers
Software engineers transitioning into AI
Professionals preparing for ML interviews
Learners developing portfolio projects
Teams prototyping AI applications
Researchers implementing or evaluating papers
Standard lessons are 60 minutes. Coding sessions, project reviews, and research deep dives can be scheduled for 90 minutes.
Before the first lesson, send me your current level, the topic or project, relevant code or materials, and the outcome you want to achieve. I will use that information to prepare a focused session.
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Review
All of our reviews are collected by us and are 100% reliable. They correspond to a real experience lived by the students of Mohamed.
5 (11 reviews)
Perfect! Mohamed is an exceptional tutor whose expertise in machine learning is evident from the first meeting. His extraordinary gift for clarifying complex concepts makes him a truly world-class teacher.
What makes him special is his rare blend of deep theoretical knowledge and practical intuition. He provides clear materials, examples, and structured learning paths.
Beyond his technical brilliance, Mohamed fosters a collaborative and motivating learning environment. As a PhD candidate working with advanced ML architectures, I've been consistently impressed by Mohamed's rigorous project management and ability to break down complex research into executable phases.
He goes above and beyond to ensure comprehension, offering insightful analogies, real-world parallels, and relentless support. His passion for teaching is contagious, making even the most daunting topics engaging and rewarding. I’m deeply grateful for their guidance! Specially, for grad students who need a thinking partner for complex technical challenges!- Dedicated researcher applying SoTA tech innovations in life sciences to the benefit of humanity and life.Mohamed's response :
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Recommendations
Recommendations come from relatives, friends and acquaintances of the teacher
10
I think he's a trustworthy teacher because he teach me a lot in different fields and he help me always in complicated problems in CS and math I understand from him a lot of things I thought I will never learn it abd he makes things easier
Mohamed is an exceptional cybersecurity tutor who blends technical expertise with clear and concise explanations. They simplify complex topics like network security, ethical hacking, and threat mitigation, making them easy to understand. Their hands-on teaching style and real-world examples ensure practical learning and engagement. Additionally, they are patient, approachable, and always ready to answer questions. Highly recommended for anyone looking to build or advance their cybersecurity skills
I highly recommend Mohamed as a cybersecurity teacher on Superprof. His expertise in the field is evident through his in-depth knowledge, practical insights, and ability to explain complex concepts in an easy-to-understand manner. Having worked with Mohamed, I can attest to his professionalism, patience, and dedication to his students' success.
He ensures that his lessons are engaging, thorough, and tailored to the specific needs of each student. His passion for cybersecurity and teaching creates a supportive learning environment that inspires confidence in his students.
If you're looking for a trustworthy and skilled cybersecurity tutor, Mohamed is an excellent choice. I have no doubt he will exceed your expectations!I've learned a lot from you and you really helped me and made me understand a lot of complicated things and i hope you keep it cause the world needs a man like you . All support and love ️
Mohamed I’m grateful to every second spent with you, You know how to make learning fun and challenging in a creative manner ️
I highly recommend Mohammed as an outstanding machine learning instructor on Superprof. With deep expertise in the field, he simplifies complex concepts, making them accessible and engaging for learners at all levels. Whether you're a beginner just starting your journey or an advanced student looking to hone your skills.
Mohamed is a very diligent professor who is always aiming to help whoever is in need. He does not spare any info needed and is one of the most dedicated and hardworking tutors out there!
I am delighted to recommend Mohamed as an exceptional tutor on Superprof.
He always prepares interesting lessons that make even the toughest topics seem easy and fun.
Whether you’re preparing for exams or looking to deepen your understanding of a subject, Mohamed is the tutor who will guide you every step of the way.
His personalized lessons are designed to meet each student’s individual needs, making learning both effective and enjoyable.
His aim is to help students achieve their academic goals and develop a lifelong love for learning.
Mohamed is really helpful, his knowledge makes me feel like he is 40 or 50 years old, I can easily admit that he is the reason I loved Machine Learning.
I've personally worked with Mohamed as teachers which was how we first met, and i've seen how he teaches others. On a professional level, he is a very dedicated and knowledgeable teacher. If he's your teacher, you can very well expect him to go the extra mile, and provide more knowledge than what is asked of him. On a personal level, he is very friendly person and it's an absolute pleasure to talk to.
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Rates
Rate
- Ksh. 3,234
Pack prices
- 5h: Ksh. 14,874
- 10h: Ksh. 28,455
online
- Ksh. 2,587/h
free lessons
The first free lesson with Mohamed will allow you to get to know each other and clearly specify your needs for your next lessons.
- 30mins
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