

Ouassima's profile, qualifications and contact details have been verified by our experts
Ouassima
- Rate RM143
- Response 3h
-
Students10
Number of students accompanied by Ouassima since their arrival at Superprof
Number of students accompanied by Ouassima since their arrival at Superprof

RM143/h
1st lesson belanja
- Databases
- Data Analysis
Data Analysis Tutor for Students and Professionals | Python, Pandas, Excel, SQL and Data Visualization
- Databases
- Data Analysis
Lesson location
Recommended
Ouassima is a respected tutor in our community. They are highly recommended for their commitment and the quality of their lessons. An excellent choice to progress with confidence.
About Ouassima
I am an engineer and PhD researcher specializing in Artificial Intelligence and data-driven systems, with more than eight years of programming experience and over six years of online teaching experience.
I have taught and mentored more than 100 learners worldwide, including university students, researchers, professionals, and beginners working with Python, statistics, Data Analysis, Machine Learning, and technical projects.
I have practical experience working with structured datasets, analytical workflows, Python notebooks, statistical methods, visualizations, and research-oriented projects.
My principal strength is helping learners understand the reasoning behind an analysis. Knowing a few Python commands is not enough—you also need to understand what the data represents, which steps are appropriate, how to recognize misleading results, and how to communicate your findings clearly.
My lessons combine clear explanations, live demonstrations, and guided practice. We can build your foundations, work through a university course, clean and explore a dataset, debug an existing notebook, or develop a complete analysis step by step.
Lessons are patient, practical, and adapted to your level. I teach in English, French, and Arabic.
Bring your learning objectives, course material, dataset, spreadsheet, notebook, or project description to the first session, and we will identify the best way to proceed.
About the lesson
- Form 6
- STPM
- Adult education
- +10
levels :
Form 6
STPM
Adult education
Masters
Doctorate
Beginner
Intermediate
Advanced
Professional
Kids
Primary
Secondary
SPM
- French
- English
- Arabic
All languages in which the lesson is available :
French
English
Arabic
Do you have a dataset, assignment, research project, or business question but feel uncertain about how to clean the data, choose the correct analysis, create useful visualizations, or explain your findings?
I provide personalized Data Analysis lessons for university students, researchers, professionals, and beginners who want to work confidently with real data using Python, Pandas, Excel, SQL, and visualization tools.
Depending on your level and objectives, we can work on:
• Python foundations for Data Analysis
• Working effectively with Jupyter Notebook
• NumPy and Pandas
• Importing data from CSV, Excel, and other structured files
• Understanding rows, columns, variables, and data types
• Cleaning missing, duplicated, inconsistent, and incorrect data
• Filtering, sorting, grouping, and aggregating information
• Combining datasets using merges and joins
• Pivot tables and summary tables
• Exploratory Data Analysis
• Descriptive statistics and statistical reasoning
• Identifying distributions, relationships, patterns, and outliers
• Creating clear visualizations with Matplotlib and Seaborn
• Writing SQL queries for Data Analysis
• Analyzing data with Excel formulas and pivot tables
• Interpreting analytical results correctly
• Presenting findings through notebooks, reports, and presentations
• Debugging Python notebooks and improving existing analyses
Every lesson begins with the question you are trying to answer. You can bring a course exercise, research dataset, business dataset, project instructions, notebook, or existing code.
We will work through a clear analytical process:
1. Define the question and expected outcome
2. Understand the structure and quality of the data
3. Clean and prepare the relevant variables
4. Select the appropriate analysis
5. Create visualizations that communicate useful information
6. Interpret the results without making unsupported conclusions
7. Organize the work into a clear and reproducible notebook or report
You will not simply receive code to copy. I will explain what each step accomplishes, why it is necessary, what assumptions it involves, and how you can apply the same reasoning to other datasets.
For academic work, I provide guidance that helps you understand and complete your own analysis while respecting academic-integrity requirements.
If your dataset contains confidential or personal information, please anonymize it before sharing.
The first 30-minute session is free. We will review your objective, assess your current skills, and create a focused plan for your course, research, or project.
Recommendations
Recommendations come from relatives, friends and acquaintances of the teacher
I made it through my college years thanks to Sima. She tutored me in multiple subjects, and I can confidently say that she truly knows what she is doing. She is knowledgeable, patient, and highly effective as a tutor.
I recommend Sima for her work in Machine Learning. She has a patient and encouraging way of explaining ideas, which helps students feel comfortable and confident.
She makes complex topics easier to understand and creates a supportive space where students feel they can ask questions and grow. Her kindness, reliability, and genuine care for student success make her someone students can truly trust.I’ve worked with Sima on multiple projects involving ML models, and she really knows what she’s doing. Her passion for the subjects she teaches is unmatched. She walks you through every detail with precision and patience. I cannot recommend her enough.
Ms. Sima is one of the best tutors I have learned from. Her ability to break down difficult AI and Python concepts into easy-to-understand lessons is truly remarkable. She creates an encouraging learning environment and always makes sure her students understand the material. Thanks to her guidance, I gained both knowledge and confidence in these subjects. I highly recommend her to anyone looking for an excellent and dedicated teacher.
Sima is really a wonderful tutor. I had the pleasure of meeting her at a conference and I was struggling on some projects at the moment and she offered to help. It was a wonderful experience and I still count on her for so many projects until this day. I totally recommend her as a mentor.
I totally recommend Sima. She is an excellent tutor who helped me throughout the years and I totally appreciate the way she made me feel during each class. Thanks to her I feel more confident and got the job I always wanted.
One of the best tutors I’ve worked with. Very professional, supportive, and genuinely cares about student progress. Lessons are organized, easy to follow, and never stressful.
I’ve seen a huge improvement in my understanding and grades since starting tutoring sessions. The explanations are always clear, patient, and adapted to my level. Highly recommended for anyone struggling with difficult subjects.
View more recommendations
Rates
Rate
- RM143
Pack rates
- 5h: RM715
- 10h: RM1430
free lessons
This first lesson is free to allow you to get to know your teacher so that they can best meet your needs.
- 30mins
online
- RM143/h
Details
Individual lessons are suitable for solving one specific data problem, understanding a difficult concept, debugging a notebook, or reviewing an existing analysis.
The 5-hour package is suitable for completing an Exploratory Data Analysis, learning a defined group of skills, or making substantial progress on a university, research, or professional project.
The 10-hour package provides a structured Data Analysis pathway covering data preparation, exploration, visualization, interpretation, and presentation.
Structured packages include an initial assessment, a personalized roadmap, progress reviews, and recommended practice or resources between lessons.
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