Anass | PhD Researcher - Computer programming tutor - Chicago
1st lesson free
Anass | PhD Researcher - Computer programming tutor - Chicago

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Anass | PhD Researcher will be happy to arrange your first Computer Programming lesson.

Anass | PhD Researcher

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Anass | PhD Researcher will be happy to arrange your first Computer Programming lesson.

  • Rate R294
  • Response 4h
  • Students

    Number of students Anass | PhD Researcher has accompanied since joining Superprof

    44

    Number of students Anass | PhD Researcher has accompanied since joining Superprof

Anass | PhD Researcher - Computer programming tutor - Chicago
  • 4.9 (6 reviews)

R294/h

1st lesson free

Contact

1st lesson free

1st lesson free

  • Computer Programming
  • Python
  • Programming Languages
  • Artificial Intelligence

Practical AI, Machine Learning, GenAI, LLMs and Python with a PhD Researcher

  • Computer Programming
  • Python
  • Programming Languages
  • Artificial Intelligence

Lesson location

Ambassador

One of our best tutors. Quality profile, experience in their field, verified qualifications and a great response time. Anass | PhD Researcher will be happy to arrange your first Computer Programming lesson.

About Anass | PhD Researcher

I am an artificial intelligence and cybersecurity professional, as well as a PhD researcher working at the intersection of AI and cybersecurity.

I help students, professionals and career changers learn artificial intelligence, machine learning, deep learning, generative AI, large language models and Python through clear explanations and practical projects.

My teaching philosophy is simple:

Understand → Practice → Build → Improve

Whether you are starting from zero, completing a university project, preparing for an interview or developing professional AI skills, I will guide you step by step through a structured and personalized learning path.

My teaching areas include:

• Python programming for data science and artificial intelligence
• Machine learning and model evaluation
• Deep learning and neural networks
• Generative AI and large language models
• Prompt engineering and AI applications
• Natural language processing
• Computer vision
• Data analysis and visualization
• AI project development
• AI interview and career preparation
• Academic and professional project support

I focus on making complex concepts understandable, practical and directly applicable. Instead of only explaining formulas or libraries, I help you understand why a method is used, how it works, how to implement it and how to evaluate the results.

My lessons combine academic foundations, industry tools, guided exercises and portfolio-ready projects. The objective is not only to help you write code, but also to help you think like an AI practitioner and confidently explain your work.

Lessons are available online in English or French.

Explore my AI, cybersecurity and cloud projects, educational resources and professional portfolio at arharif.github.io.

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About the lesson

  • Primary
  • Secondary
  • Matric/GCSE
  • +12
  • levels :

    Primary

    Secondary

    Matric/GCSE

    AS Level

    A Level

    BTech

    Adult education

    Masters

    Doctorate

    MBA

    Beginner

    Intermediate

    Advanced

    Professional

    Kids

  • French
  • English

Languages in which the lesson is available :

French

English

Every lesson is adapted to your current level, objectives and preferred learning pace.

I work with complete beginners, university students, developers, professionals and career changers who want to build practical skills in artificial intelligence, machine learning, deep learning, generative AI and Python.

Depending on your objectives, your personalized learning roadmap may include:

AI and Machine-Learning Foundations

• Artificial intelligence, machine learning, deep learning and generative AI
• Supervised and unsupervised learning
• Regression, classification and clustering
• Training, validation and testing
• Overfitting, underfitting and regularization
• Accuracy, precision, recall, F1 score and ROC-AUC
• Feature engineering and data preparation

Python and Data Tools

• Python foundations for artificial intelligence
• NumPy for numerical computing
• Pandas for data preparation and analysis
• Matplotlib for visualization
• Scikit-learn for machine-learning projects
• Jupyter Notebook and Google Colab

Deep Learning

• Neural-network foundations
• Forward propagation and backpropagation
• Convolutional neural networks
• Recurrent neural networks
• TensorFlow or PyTorch
• Training, evaluation and optimization

Generative AI and Large Language Models

• Large-language-model foundations
• Prompt engineering
• Embeddings and semantic search
• Retrieval-augmented generation
• AI agents and automation fundamentals
• Building simple LLM-powered applications
• Responsible AI and model limitations

Practical Projects

Projects are selected according to your level and goals. Examples include:

• Spam or phishing-message detection
• Fraud-detection models
• Customer-churn prediction
• Image classification
• Sentiment analysis
• Recommendation systems
• Text classification
• AI-powered assistants
• Retrieval-augmented-generation applications
• Portfolio projects using real datasets

Teaching Method

Each lesson follows a practical and progressive structure:

1. Review your objectives and current level
2. Explain the concept clearly
3. Demonstrate the implementation step by step
4. Guide you through practical exercises
5. Apply the concept to a project
6. Review the results and identify improvements

The balance between theory and practice is adapted to your needs. Beginners receive more guidance and structured explanations, while intermediate and advanced learners can focus on project design, debugging, model improvement and professional use cases.

You may also receive:

• Personalized learning roadmaps
• Guided exercises and optional homework
• Project feedback and code review
• Interview questions and mock interviews
• Support with portfolio presentation
• Help explaining your projects professionally
• Progress tracking and recommendations after each session

The complimentary 30-minute introductory session is used to understand your background, assess your level and define the most suitable learning roadmap.

Whether your goal is to understand AI, complete an academic project, build a portfolio, prepare for an interview or transition into an AI-related career, the lessons will give you a clear and practical path forward.

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Rates

Rate

  • R294

Package rates

  • 5h: R1387
  • 10h: R2611

online

  • R294/h

free lesson

The free first lesson with Anass | PhD Researcher allows you to get to know the tutor and discuss your needs and expectations.

  • 30min

Details

The standard rate is $18 per hour.

The 5-hour package is available for $85 and is suitable for learning a focused topic, completing a small project or strengthening specific AI and Python skills.

The 10-hour package is available for $160 and is recommended for a complete learning roadmap, portfolio project, interview preparation or structured machine learning and generative-AI training.

Packages may include a personalized roadmap, practical exercises, project guidance, code review, learning resources and progress feedback.

The complimentary 30 minute introductory session is dedicated to understanding your objectives, assessing your current level and proposing a suitable learning plan.

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