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Since December 2021
Instructor since December 2021
Practical Data Science - Interview Preparation - Working backwards from End Product with Machine Learning
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From 54 € /h
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Class teaches you how to apply your math and coding skills, and prepares you for the interviews with the companies ranging from start-ups to the big tech giants. It covers ML part: (i) working backwards from problem statement with Data Science eyes, (ii) choosing the best Machine Learning approach, (iii) drilling down in ML, and interview preparation part: (iv) preparing you to answer tech questions, (v) ML concepts questions, (vi) product questions, (vii) work principles questions.
Location
location type icon
Online from Belgium
About Me
I'm a Sr Data Scientist | Sr Product Manager with 9+ years of experience in Amazon, Generali, and PWC. I am passionate about building strategies, launching products, and democratizing AI knowledge.
Education
Master of Science, Mathematics (Probability and Statistics) from University of Belgrade, GPA 9.75/10
Bachelor of Science, Mathematics (Probability and Statistics) from University of Belgrade, GPA 9.28/10
Experience / Qualifications
Amazon EU, Italy / Belgium
Sr Product Manager Expansions (July ’21 – present)
• Owner of the Selection and Vendor management strategy for Amazon expansion into a new geography, creating and
executing on a first-time-at-Amazon scalable and lean operating model for expansion
• Single-threaded leader of the Catalog Localization for 5 new countries launch across 3 continents
Amazon EU, Milan, Italy
Sr Data Scientist | Sr Product Manager (July ‘19 – June ‘21)
• Leading a team that uses Machine Learning to introduce step-change in Amazon EU Retail business by incubating
innovative ideas that improve customer experience and optimize the way business is managed.
• Projects: Automatic root cause detection using NLP on customer feedback (return rate reduction 24% using ML
classification and unsupervised insights extraction); Causal inference pipeline for Promotions propensity and
incrementality (>1000 business users, yearly savings 12%); Price erosion prediction along the product lifecycle
• Tech stack: Python (spacy/BERT, sklearn, Keras), AWS (Lambda, Amazon SageMaker, s3, QuickSight)
Generali Group, Milan, Italy
Sr Data Scientist ( March ‘16 – June ‘19)
• End to end Data Science projects: Business case setup, guidance on analytical process, product implementation
• Business areas: Process optimization and automation, Fraud, Claims management, Health insurance, Pricing
• Machine Learning algorithms: Deep Learning with Keras, Computer Vision, Natural Language Processing, OCR
• Tech stack: Python, Spark, R, Microsoft Azure, Spotfire, Tableau
Generali insurance Serbia, Belgrade, Serbia
Actuary (June ‘13 – February ‘16)
• Pricing and product development for property and casualty insurance, modeling of new tariffs for non-life insurance
• Pricing risk assessment, Reserving risk assessment, and technical reserves calculation
• Forecasts and business plans: best estimate of liabilities
PricewaterhouseCoopers, Belgrade, Serbia
Intern in Assurance (September ‘12 – March ‘13)
• Team member on audit engagements of financial statements: audit of business processes, design, and operation of
internal controls, performing substantive testing
• Assessment of loan loss provisions in the financial services industry
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
Italian
Serbian
French
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
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• Deduction: Valid arguments and proofs; Proofs in predicate logic

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Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

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📌 Mentored students to achieve top grades in Cambridge ICT & Computer Science exams.
📌 Developed interactive lesson plans integrating real-world applications of technology.
📌 Conducted coding boot camps and cybersecurity workshops to enhance practical learning.
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How it works (simply): The image of the "giant library": AI has read billions of books and uses them to predict the continuation of a sentence or create an image.

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Ask him to write an administrative email or a complex letter.

Summarize a long newspaper article or document.

Plan a travel itinerary or find recipe ideas with what's left in the fridge.

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Using AI to restore or colorize old family photos.

3: Learning to "talk" to AI (The Art of the Prompt)
The context method: Why "Give me a cake recipe" is less effective than "I am allergic to gluten and I am hosting 4 people, give me a simple chocolate cake recipe".

The expert's role: Learning to tell AI "Act like a travel guide" or "Act like an expert gardener".

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"Hallucinations": Understand that AI can make false claims with complete certainty (never take medical or legal advice from AI without verification).

Privacy protection:

Never give sensitive data (social security number, passwords, bank details) to an AI.

Knowing that everything we write to the AI is potentially used to train it.

Spotting "Deepfakes":

How to recognize a doctored image or video (details on the hands, strange reflections, slightly metallic voice).

Verify the information: the golden rule of cross-referencing sources.

5: Ethics and Impacts (To go further)
Copyright: Who owns an image created by AI?

The environmental impact: The water and energy consumption of AI servers.

The future: Will AI replace us or assist us?
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I use a Pen Display Tablet to write on it using Goodnotes as the writing app, which I share the link to the whiteboard used with the students.

Lessons are available online or in-person (within 30 mins train travel from Shinjuku, Tokyo), and are conducted in English.
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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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I am a certified computer science professor who helps graduates and students with exam retakes and competitions. I tutor preparatory classes (MPSI, MP, PSI, ECS, etc.) up to university level (Bachelor's & Master's in Science or Economics). My method is based on understanding the lessons, practicing correctly, organizing the concepts, and completing exercises and problems of your choice. Each session includes verbal exercises, methodological tips, and subsequent personalized advice. You will receive a video recording and an annotation in PDF format after each session. The online courses are conducted via Google Meet, 5 days a week, with flexible scheduling. I am available between sessions to answer questions. Contact me for an initial consultation.
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As a Master's student in Data Science at EPFL, a graduate of CentraleSupélec (ranked in the top 3% of my class) and holder of a Bachelor's degree in microtechnology from EPFL, I offer tutoring in mathematics, physics and computer science, from primary school to university level.
My teaching experience
I was a student teaching assistant at EPFL for 8 courses, working with over 400 students. I currently lead the linear algebra and ICC (Information, Computation, Communication) exercise sessions. Each week, I adapt my explanations to each student's level: that's what I love most about teaching.
What I propose
• Primary and secondary school: consolidate the basics (calculation, fractions, geometry, equations), regain confidence and improve methodology.
• Gymnasium / high school (maturity, baccalaureate): functions, analysis, probabilities, vectors, mechanics, electricity, exam preparation.
• University / EPF / preparatory classes: analysis, linear algebra, probability and statistics, numerical analysis, programming (Python, C/C++).
My method
I begin by identifying the real obstacle: a misunderstanding of the concept, a lack of methodology, or stress. Then, I build the sessions based on the student's lessons and exercises. The goal isn't just to pass the next test, but to understand the material and become independent.
Whether you need occasional homework help, regular support, or intensive exam preparation, I adapt to your needs.
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Python Level 1Workshop

**Course Description**

Want to learn programming from scratch? This beginner-friendly Python course introduces students to coding through interactive lessons, practical exercises, and fun mini-projects.

Students will learn how to write Python programs, work with different types of data, take user input, make decisions using conditions, and repeat actions using loops. Each concept is explained step by step with real-life examples and hands-on coding activities.

**What You Will Learn**

* **Lesson 1: Your First Python Program** — Learn the `print()` function, display messages, and create simple programs.
* **Lesson 2: Variables and Data Types** — Store and work with text, numbers, and other basic data.
* **Lesson 3: User Input and Calculations** — Build interactive programs that accept user input and perform calculations.
* **Lesson 4: Conditional Statements** — Use `if`, `elif`, and `else` to make programs respond to different situations.
* **Lesson 5: Loops and Mini-Projects** — Use loops to repeat actions and apply your skills in practical coding challenges.

**Hands-On Projects**

Students will apply their learning by building beginner-friendly projects such as a calculator, a number-guessing game, and a Rock-Paper-Scissors game.

**Who Is This Course For?**

* Children and teenagers aged 8–16.
* Complete beginners with no prior programming experience.
* Students who want to develop logical thinking, problem-solving, and computational skills.
* Learners who want to explore programming through practical projects.

**My Teaching Approach**

I explain concepts step by step, use relatable examples, and encourage students to write their own code instead of simply copying solutions. Lessons are adapted to each student's pace, with coding exercises and challenges to strengthen understanding.

**No prior coding experience is required.** Students need a computer and an internet connection to participate.

By the end of Level 1, students will have a solid foundation in Python basics and the confidence to start creating their own simple programs.
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