

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Ammar will be happy to arrange your first Software lesson.
Ammar
One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Ammar will be happy to arrange your first Software lesson.
- Price $25
- Answer 2h
-
Students50+
Number of students Ammar has accompanied since arriving at Superprof
Number of students Ammar has accompanied since arriving at Superprof

$25/h
1st lesson free
- Software
- Machine learning
- Coding
Master Machine Learning, AI & Python with a PhD Engineer and Professor | 25+ Years’ Expertise & Professor | Beginner to Advanced Levels
- Software
- Machine learning
- Coding
Lesson location
Ambassador
One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Ammar will be happy to arrange your first Software lesson.
About Ammar
I am a PhD Engineer, university professor, researcher, and multidisciplinary technical educator with more than 25 years of experience in engineering, mathematics, statistics, programming, data analysis, research methodology, and computational modelling.
I have taught and supported university students, graduate researchers, engineers, analysts, professionals, and career-transition learners. My students range from complete Python beginners to advanced learners working on machine-learning assignments, dissertations, predictive models, artificial-intelligence applications, technical interviews, and professional data projects.
My teaching philosophy is based on a clear principle: machine learning should be understood as a connected system of mathematics, data, algorithms, code, evaluation, and application—not treated as a collection of library commands.
I explain what each model is designed to do, how its mathematical logic works, what assumptions it makes, how Python implements it, how performance should be measured, and how to identify data leakage, overfitting, bias, and interpretation errors. When a concept is difficult, I connect equations, diagrams, code, model outputs, and practical examples.
My expertise includes:
• Python, NumPy, pandas, SciPy, Statsmodels, Matplotlib, Seaborn, and scikit-learn
• Supervised and unsupervised machine learning
• Regression, classification, clustering, dimensionality reduction, anomaly detection, and forecasting
• Neural networks, deep learning, TensorFlow, Keras, and PyTorch
• Natural language processing, computer vision, recommendation systems, and generative-AI foundations
• Model evaluation, feature engineering, hyperparameter tuning, explainability, and responsible AI
• SQL, Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, Excel, and Power BI
• Statistics, linear algebra, optimization, research methodology, and reproducible analytical workflows
Lessons are personalized to your level and objectives. I can help you learn Python and machine learning systematically from the beginning, understand difficult theory, debug code, complete an assignment, analyze research data, prepare for a technical interview, or develop an end-to-end AI project.
My goal is to help you become accurate, confident, and independent. You should leave each lesson understanding what the model does, why it works, how to test it, how to improve it, and how to apply the same reasoning to new problems.
About the lesson
- High School
- Year 10
- TAFE
- +8
levels :
High School
Year 10
TAFE
Diploma/Certificate
Beginner
Intermediate
Advanced
Professional
PhD
Year 11-12
Year 12
- French
- English
All languages in which the lesson is available :
French
English
Machine learning and artificial intelligence become much easier when the mathematics, algorithms, Python code, data, and real-world applications are connected clearly.
My lessons help you move beyond copying code or using models as black boxes. You will learn how to define the problem, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret the results responsibly.
Each lesson is personalized to your current level, mathematical background, programming experience, dataset, assignment, research project, interview, or professional objective. We begin by identifying your existing knowledge, software environment, expected output, and main conceptual or technical difficulties. We then establish a structured learning plan.
The first free lesson combines a discussion of your background, objectives and tutoring needs, an initial assessment of your current knowledge, personalized planning and scheduling, and a short trial lesson so that we can determine the most effective way to work together.
A- PYTHON FOUNDATIONS
• Variables, data types, operators, conditions, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management
B- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation
C- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms
D- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation
E- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern discovery
• Selecting methods, evaluating structure, and interpreting results without predefined labels
F- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; and hyperparameter tuning
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R²
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, selection, scaling, and regularization
G- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent networks, and transformer foundations
• TensorFlow, Keras, or PyTorch depending on the project and learner’s environment
H- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and language-model foundations
• Computer vision, image classification, object detection foundations, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications
I- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention, prompting, retrieval-augmented generation, and model evaluation
• Using AI APIs, vector databases, document retrieval, and structured AI workflows when relevant
• Reliability, hallucination, bias, privacy, responsible use, and appropriate human validation
J- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when they support the project
• Additional libraries may be introduced according to the selected specialization and dataset
K- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• End-to-end projects involving data preparation, model development, evaluation, interpretation, and presentation
• Academic assignments, dissertations, research studies, portfolio projects, technical interviews, and workplace applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results
A typical lesson may include conceptual explanation, mathematical intuition, live coding, guided implementation, model evaluation, troubleshooting, and a concise summary of the next steps.
You may work with your own dataset, assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets adapted to your level.
My objective is not merely to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable and interpretable solution.
Recommendations
Recommendations come from relatives, friends and acquaintances of the teacher
You are my ideal . You are a great leader, honestly you are the best.
I met professor Ammar in University and I have never seen someone so kind, charismatic, encouraging, has effective classroom management strategies, and solid knowledge of the subject matter or the field. Promotes positive learning experiences, attitudes, engagement and motivation. Whenever we faced a problem or a difficulty with something we would always go to professor Ammar and we he would always listen and help us in a heartbeat. I feel proud that I got to meet such an inspirational professor in my life that I will never forget.
Exceptional skills and understanding. Making it easy to grasp the knowledge and content of the course. Will go above an beyond to make sure you fully understand.
I just want to say thank you, for being a teacher who cares about what we learn and who we are becoming.
You’ve encouraged us to grow as students, and you’ve remembered we are growing as people, too, delivering your instruction with love and warmth and caring, somehow, you made even the hardest times fun.
Thank you, for making our days at college way much easier.Professor Ammar Explains information in an easy-to-understand manner Which makes the lessons easy for the student. In addition to his cheerful spirit and answering questions, and answering them clearly and simply
Ammar first is a great person and sincere.
When he is tutoring I like the way of his examples to make easy to understand the topic (Math in my case).
He was able to understand my problem and able to help me solve the problem. I would recommend him.
Dr. Ammar is wonderful, but more than wonderful
Best PROf in the world
Dr. Ammar, is one of the most important and greatest professors I have ever met. I have known him for more than 6 years. Skilled in providing consultancy in various disciplines. He has important knowledge and skills in the field of management, technology and many specializations. I had several trainings with him. I am proud to know him. It was a wonderful opportunity and every year I see him adding new knowledge to his sciences. Encyclopedia of knowledge and science.
Julian AliHe is the best teacher. He taught me business administration, management and organization, and he taught me programming and graphic design. He is the best teacher
A real Guru in Business and technology , one of the best mentors any one could ever have ,very helping , caring and supportive . Always keeping his students updated and sharing valuable knowledge with them .
Dr. Ammar has wealth of knowledge in management especially project management.
He gets the student engaged intova comprehensive understanding about the concept at a strategic level of mangement.
He has a very good manner in giving the lesson in a systematic approach.
I have learnt a lot from Dr. Ammar. He has been my first professional guide in IT studies and researches and many other subjects. He is a creative and an out-of-the-box thinker. I enjoyed learning and working with him. I always wish him all the best.
I have attended many training sessions in different subjects with Dr. Ammar, and I benefited a lot. He explains in details all you need to know and more which allows you to master the application or the software.
View more recommendations
Rates
Price
- $25
Pack prices
- 5h: $127
- 10h: $253
online
- $25/h
travel fee
- + $10
free lessons
The first lesson with Ammar will allow you to get to know each other and discuss your needs for future lessons.
- 1hr
Details
The first free lesson is a structured introductory and trial session. We will briefly introduce ourselves—including your academic or professional background and my relevant expertise—clarify your objectives, deadlines and tutoring needs, and assess your current knowledge through discussion and a short diagnostic activity. We will then establish a focused learning plan and schedule for future lessons. The remaining time will be used for a short trial lesson on a representative concept or problem, allowing you to experience my teaching approach before deciding whether to continue.
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