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Archviz training for beginners – Learn architectural visualization with 3ds Max and Photoshop
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From 65 £ /h
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Do you want to discover architectural visualization (archiviz) and learn how to create your first 3D architectural images? This introductory archviz training is specially designed for beginners and curious individuals who want to understand and master the basics of creating architectural images with Autodesk 3ds Max and Adobe Photoshop.

Through a progressive and accessible learning approach, you will discover how to transform a simple 3D model into a realistic and attractive architectural image. The training covers the essential fundamentals: basic modeling, framing and composition, lighting, material application, rendering, and then image enhancement in post-production using Photoshop.

The goal is to give you a clear understanding of the complete workflow in architectural 3D visualization, while developing your artistic eye and your ability to tell a project's story visually. No advanced level is required: the training lays a solid foundation for progressing to more complex and professional renderings.

Ideal for students, architecture enthusiasts or creatives, this training constitutes a concrete first step towards the world of archival visualization and 3D imagery.
Extra information
In order to follow the architectural visualization (archviz) training under the best conditions, participants must have the following hardware and software:

- A personal computer (Windows recommended for smooth 3ds Max operation)
- Autodesk 3ds Max installed and working
- Adobe Photoshop installed
- A stable internet connection
- A webcam and a microphone, as the training is delivered 100% online

No prior experience in 3D modeling or architectural rendering is required. However, a basic knowledge of the computer environment is recommended.
Location
location type icon
Online from Switzerland
About Me
Je suis Piero Rios, visualisateur architectural spécialisé en infographie 3D. J’accompagne les architectes et développeurs dans la création d’images destinées aux concours d’architecture et aux projets de développement urbain.

À travers cette formation, je partage une méthode claire, structurée et accessible pour apprendre les bases de la visualisation architecturale et comprendre comment transformer une idée ou un modèle 3D en une image forte et cohérente.
Education
Certification - Brick Academy - 2021
Intensive Archviz - Budapest, Hungary

Certification - English B2 - 2020
ASC Languages - Geneva, Switzerland

Bachelor - Interior Design - 2011-2015
HEAD - Geneva, Switzerland

academy - Interior Design - 2010-2011
AAD - Geneva, Switzerland

Certification - French C1 - 2009-2010
UNIGE - Geneva Switzerland

Graduate web design - 2008-2009
Azpe Informática - Madrid, Spain

Graphic Design Graduate - 2007-2008
Azpe Informática - Madrid, Spain
Experience / Qualifications
Piero Rios Visuals - 2021-2026
•3D Artist / Architectural visualizer

Architecture Retail & Rites - 2018-2020
Lausanne, Switzerland
• 3D Artist

design in- 2016-2018
Geneva, Switzerland
• Interior designer
• BIM-3D modeler
• 3D Artist

black ghost studio - 2015
Geneva, Switzerland
• game design
• 2D environment design
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Duration
60 minutes
The class is taught in
French
Spanish
English
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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6. Conclusion and Q&A (10 min)

* Summary of achievements.
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Graphing and solution

Fundamentals of Linear Algebra

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Big-M Method

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The original (Primal) and dual problem

The relationship between variables and constraints

Weak Duality Theory

Strong Duality Theory

Conditions for Complementary Slackness

Dual variables as marginal costs

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Applications in Economics and Finance

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Contact Piero
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Objective: To understand AI without fear, to use it to simplify one's life, to know how to identify digital traps, and to use Word, Excel, etc. without difficulty.

1: Demystifying AI (What exactly is it?)
AI is not a movie robot: Difference between fiction and reality.

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.

Where is it already present? Spell checkers, Netflix/YouTube suggestions, GPS, and voice assistants (Siri/Alexa).

2: Using AI to make life easier
Conversing with AI (ChatGPT, Claude, Gemini):

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.

AI for creativity and memory:

Generate images to illustrate a birthday card (Midjourney, DALL-E).

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".

4: Precautions and Critical Thinking (The Survival Guide)
"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?
verified badge
Laroussi
Session 1: Revolutionizing your Scientific Writing with LaTeX & AI
Duration: 2 Hours | Level: Beginner | Tools: Overleaf + AI**

First Hour: Foundations and Cloud Environment (60 min)

1. Introduction to LaTeX Philosophy (15 min)

- The "WYSIWYM" concept:** Explain the difference between Word (*What You See Is What You Get*) and LaTeX (*What You See Is What You Mean*). Why content takes precedence over form.
- Key advantages:** Unrivaled typographic quality, automatic reference management, stability on long documents (theses), and free of charge.
- The structure of a file:** Distinction between the **preamble** (the brain: settings and packages) and the **body of the document** (the heart: text).

2. Immersion in Overleaf (25 min)

- Configuration:** Creation of an account and first project "Blank Project".
- Exploring the interface:** The file panel (left), the code editor (middle) and the PDF preview (right).
- Real-time collaboration:** How to share a project and leave comments (like on Google Docs).
- History and versions:** How to revert to a previous version in case of a compilation error.

3. Practical Workshop: My First Document (20 min)

* Writing basic commands: `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation of the document and observation of the result.
* Structuring: Use of `\section` and `\subsection`.

Second Hour: Mathematics and the Magic of AI (60 min)

4. The Power of Mathematics (20 min)

- Mathematical modes:** Difference between the text (`$...$`) and the centered block (`\[...\]`).
- Essential syntax:** Fractions `\frac{}{}`, exponents `^`, indices `_`, and roots `\sqrt{}`.
- Introduction to AMS packages: Why amsmath and amssymb are essential for professional rendering.

5. From hand to screen: AI at the service of LaTeX (30 min)

- Presentation of OCR tools:** Use of **Mathpix Snip** (the leader) or models like Gemini/ChatGPT to transform a photo into code.
- Concrete demonstration:
1. Take a picture of a complex handwritten formula (e.g., an integral with matrices).
2. Use AI to generate the corresponding LaTeX code.
3. Correction and insertion: Learn to check the AI-generated code before copying and pasting it into Overleaf.

6. Conclusion and Q&A (10 min)

* Summary of achievements.
* Resources for further exploration
* Definition of the exercise for the next session.
verified badge
عبدالرحمن
A comprehensive course in Linear Programming and Linear Optimization, based on the renowned reference:

Bertsimas, D., & Tsitsiklis, J. N. (1997). Introduction to Linear Optimization. Athena Scientific.

The course covers the first five chapters in their entirety, forming the foundation upon which everything that follows in mathematical improvement is built. The concepts are explained in clear Arabic with step-by-step solved examples, illustrations, and practice exercises.

The five lectures:

Lecture 1 — Introduction to Linear Optimization:

What is optimization? And why do we need it?

Variables, decisions, functions, and constraints

The general formula for linear programming

Standard Form

Reducing any issue to the standard formula

Piecewise Linear Convex Functions

Graphing and solution

Fundamentals of Linear Algebra

Analysis of algorithms and number of operations

Lecture 2 — Linear Programming Basics (LP Basics):

Practical examples: food issues, production, scheduling, networks, pattern classification

Converting problems to standard format

Remove free variables

Slack and Surplus variables

convex and concave functions

Absolute values in objective functions

Graphical solution in 2D and 3D

The five possible solutions

Lecture 3 — Geometry of Linear Programming (LP):

Polyhedron and Polytope

Hyperplanes & Halfspaces

Extreme Points

Vertices

Basic Feasible Solutions

Active Constraints

Degeneration

The presence of extreme points

Visual examples in 2D and 3D

Lecture 4 — The Simplex Method:

Optimality Conditions

Reduced Costs

Development of the Simplex algorithm

Simplex Tableau

Pivoting

The Revised Simplex Method

Cycling and how to avoid it

Bland's Rule

Finding a basic, possible, initial solution

Two-Phase Simplex Method

Big-M Method

Mathematical aptitude and average behavior

Klee-Minty cube

Lecture 5 — Duality Theory:

The original (Primal) and dual problem

The relationship between variables and constraints

Weak Duality Theory

Strong Duality Theory

Conditions for Complementary Slackness

Dual variables as marginal costs

Shadow Prices

Dual Simplex Method

Geometric interpretation of duality

Applications in Economics and Finance

Advantages:

🎯 Explanation based on an accredited academic reference

📐 Illustrations for each geometric concept

🧮 Solved examples with numbers

💻 Examples in Python using gurobipy

📊 Comparison tables between different formulas

🔗 Linking theory to practical applications

📝 Exercises at the end of each lecture
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