Trusted teacherStatistics, data visualization and machine learning for beginners – course in FrenchTranslate this text using Google Translate.
Statistics, data visualization and machine learning for beginners – course in FrenchTranslate this text using Google Translate.
📊 Introduction to Data Science with Python
Full Title: Statistics, Data Visualization, and Machine Learning for Beginners
(100% online course – for students, professionals in retraining, or curious data enthusiasts)
Data science is now at the heart of the most innovative professions and strategic decisions in all sectors. However, when you're just starting out, you can quickly feel overwhelmed by technical jargon, Python libraries, or statistical models.
With this course, my goal is to make this exciting discipline understandable and accessible to everyone, even without advanced mathematical training or computer science background.
I offer step-by-step support based on practical experience, concrete projects, and a supportive teaching approach. You'll learn how to manipulate data, extract information from it, and create your first machine learning models with ease.
🎯 Course objectives
Discover the basic tools of Data Science with Python
Understand and apply the fundamental concepts of exploratory statistics
Know how to manipulate, clean, visualize and interpret real data sets
Carry out initial predictive modeling (linear regression, classification)
📚 Course content
✔ Fundamental libraries in Data Science
– pandas: reading, cleaning and transforming data
– numpy: mathematical operations and array manipulation
– matplotlib & seaborn: clear and aesthetic data visualization
– Getting Started with Scikit-Learn for Machine Learning
✔ Data cleaning and analysis
– CSV file import and data mining
– Management of missing values and duplicates
– Creation of variables, filtering, groupings
– Visualization: histograms, curves, heatmaps, boxplots...
✔ Introduction to Machine Learning
– Understand how linear and logistic regression work
– First classification models (KNN, simple decision trees)
– Data separation (training/test set), single cross-validation
– Interpretation of results and improvement of the model
🧭 How the sessions work
1️⃣ Assessment of the student's objectives: discovery, professional project, preparation for training, etc.
2️⃣ Personalized progression plan, adapted to the starting level.
3️⃣ Alternation of visual theory and intensive practice on real data sets (health, sports, finance, etc.).
4️⃣ Practical mini-projects at each stage: analyzing survey results, predicting simple results, automating analyses.
5️⃣ Explanation of errors encountered, individualized educational monitoring.
6️⃣ Regular assessment, with reinforcement of key points as needed.
🌐 100% online courses – accessible teaching methods
Classes via Zoom, Google Meet, or the tool of your choice
Live screen sharing, work on interactive notebook (Jupyter or Google Colab)
PDF supports + commented code provided after each session
Possibility of intensive coaching for training or an interview
Flexible hours, adapted to the time zone of the Gulf countries and your availability
👨🎓 For whom?
Complete beginners in Data Science and Python
Students wishing to enrich their profile with practical skills
Professionals retraining for data professions
Anyone curious about understanding the world through data!
This course has been designed so that each participant can progress at their own pace, develop their analytical logic and discover the pleasure of "making the data speak".
Feel free to contact me to discuss your goals and build a customized program together. I would be delighted to accompany you on this wonderful adventure that is data science.
