Frequently Asked Questions (FAQ)​‌​‌​‌​​‍​‌​​​‌​‌‍​​‌‌‌​‌​‍​​‌‌​‌​​‍​‌‌​​‌​‌‍​​‌‌‌​​​‍​‌‌​​‌​​‍​​‌‌‌​​‌‍​‌‌​​​‌​‍​​‌‌​​​‌‍​‌‌​​​​‌‍​​‌‌​‌​‌‍​‌‌​​‌‌​‍​​‌‌​‌‌​‍​‌‌​​‌​‌‍​​‌‌​‌‌‌‍​‌‌​​​‌‌‍​​‌‌​​‌‌‍​‌‌​​‌​​‍​​‌‌‌​‌​‍​​‌‌​​‌​‍​​‌‌​​​​‍​​‌‌​​‌​‍​​‌‌​‌‌​‍​​‌‌​​​​‍​​‌‌​​‌​‍​​‌‌​​​‌‍​​‌‌​​‌‌‍​​‌‌‌​‌​‍​​‌‌​‌​‌‍​‌‌​​‌‌​‍​​‌‌​​​‌‍​‌‌​​‌​​‍​‌‌​​‌​‌‍​‌‌​​​‌‌‍​​‌‌​​‌‌‍​‌‌​​​‌​¶

Answers to the most common questions about the course.​‌​‌​‌​​‍​‌​​​‌​‌‍​​‌‌‌​‌​‍​​‌‌​‌​​‍​‌‌​​‌​‌‍​​‌‌‌​​​‍​‌‌​​‌​​‍​​‌‌‌​​‌‍​‌‌​​​‌​‍​​‌‌​​​‌‍​‌‌​​​​‌‍​​‌‌​‌​‌‍​‌‌​​‌‌​‍​​‌‌​‌‌​‍​‌‌​​‌​‌‍​​‌‌​‌‌‌‍​‌‌​​​‌‌‍​​‌‌​​‌‌‍​‌‌​​‌​​‍​​‌‌‌​‌​‍​​‌‌​​‌​‍​​‌‌​​​​‍​​‌‌​​‌​‍​​‌‌​‌‌​‍​​‌‌​​​​‍​​‌‌​​‌​‍​​‌‌​​​‌‍​​‌‌​​‌‌‍​​‌‌‌​‌​‍​​‌‌​‌​‌‍​‌‌​​‌‌​‍​​‌‌​​​‌‍​‌‌​​‌​​‍​‌‌​​‌​‌‍​‌‌​​​‌‌‍​​‌‌​​‌‌‍​‌‌​​​‌​

General¶

Do I need prior experience in Big Data?¶

No. The course starts from scratch. You only need:

• Basic Python knowledge
• Ability to use the terminal/console
• Willingness to learn

How long does it take to complete the exercises?¶

It depends on your level:

No rush. Learn at your own pace. The important thing is to understand each concept well.

Is the data real or synthetic?¶

Real. We use real public datasets:

• NYC Taxi & Limousine Commission (TLC)
• Weather data from NOAA
• Other public datasets from Kaggle

This gives you experience with real-world data (dirty, incomplete, large).

Can I use this in my portfolio?¶

Yes! In fact, we recommend it.

Many students have landed jobs by showcasing:

• Their exercise solutions
• The dashboard they created
• Their GitHub fork with professional commits

Is there a certificate upon completion?¶

For in-person course students: Yes, a 230-hour certificate.

For self-learners: There is no official certificate, but your GitHub is your certificate. Employers value seeing your code more than a PDF.

Technical¶

What computer do I need?¶

Minimum:

• 8GB RAM
• 20GB disk space
• i5 processor or equivalent
• Windows 10+, macOS 10.14+, or Linux (Ubuntu 20.04+)

Recommended:

• 16GB RAM
• 50GB SSD disk space
• i7 processor or equivalent

Does it work on Windows/Mac/Linux?¶

Yes. The course is compatible with all three operating systems.

• Windows: Preferably Windows 10 or higher
• macOS: macOS 10.14 (Mojave) or higher
• Linux: Ubuntu 20.04+, Fedora, Arch, etc.

The Installation Guide has specific instructions for each system.

Can I use another IDE instead of PyCharm?¶

Yes. PyCharm is recommended but not required.

Alternatives:

• Visual Studio Code - Lightweight and very popular
• Jupyter Lab - Excellent for notebooks
• Sublime Text - Advanced text editor
• Vim/Emacs - If you are an advanced user

The important thing is that you feel comfortable with your tool.

How do I download the data?¶

The data is downloaded automatically with a script:

# Ir a la carpeta de datos
cd datos

# Ejecutar script de descarga
python descargar_datos.py

The script automatically downloads and decompresses all the required datasets.

Git and GitHub¶

I have never used Git. Is it very difficult?¶

It is not difficult, but it requires practice.

We have complete step-by-step guides:

1. Fork and Clone - The basics
2. Your First Exercise - Complete workflow
3. Useful Commands - Quick reference

What is a Fork? Why do I need one?¶

Fork = Your personal copy of the repository on GitHub.

You need it because:

• You cannot modify the instructor's repository directly
• The fork is YOUR space to work
• You can sync it with the original
• The system automatically evaluates your PROMPTS in your fork

See the full guide: Fork and Clone

How do I keep my Fork up to date?¶

When the instructor adds new exercises, you need to sync your fork.

Easy method (GitHub Web):

1. Go to your fork on GitHub
2. Click "Sync fork" → "Update branch"
3. On your PC: git pull origin main

Full method (Terminal):

git checkout main
git fetch upstream
git merge upstream/main
git push origin main

See the full guide: Sync Fork

I made a bad commit. How do I undo it?¶

Before pushing:

# Deshacer ultimo commit (mantiene cambios)
git reset --soft HEAD~1

# Deshacer ultimo commit (descarta cambios)
git reset --hard HEAD~1

After pushing:

# Crear nuevo commit que revierte el anterior
git revert HEAD
git push origin tu-rama

Exercises¶

I cannot complete an exercise. What should I do?¶

Step 1: Read the error carefully

Most of the time the error tells you exactly what is wrong.

Step 2: Search on Google

Copy the error message and search for it. Someone else has probably had it before.

Step 3: Check the documentation

• Pandas Docs
• SQLite Tutorial
• Python Docs

Step 4: Ask for help

• In-person students: Ask during class
• Self-learners: Create an Issue on GitHub explaining your problem

Can I do the exercises out of order?¶

Not recommended. The exercises are designed to:

• Build upon previous knowledge
• Gradually increase in difficulty
• Introduce concepts in a logical order

How many times can I attempt an exercise?¶

As many as you need. There is no limit on attempts.

The goal is to learn, not to pass quickly.

• You can update your fork as many times as you want with git push
• The automatic evaluation system checks your PROMPTS.md file
• You learn more from mistakes than from successes

Can I use additional libraries?¶

Yes, but:

1. Justify why you need them
2. Add them to requirements.txt
3. Document how to install them
4. Mention in PROMPTS.md which libraries you used

# requirements.txt
pandas==2.0.0
seaborn==0.12.0  # Para visualizaciones avanzadas

Support¶

Do you offer support if I get stuck?¶

For in-person course students:

• Full support during sessions
• Email consultations
• Automatic submission review

For self-learners:

• No direct support
• You can create Issues on GitHub
• The community can help you
• Complete documentation available

How do I contact the instructor?¶

For course inquiries:

• GitHub Issues: Create Issue
• Email: cursos@todoeconometria.com

For business consulting:

• Email: cursos@todoeconometria.com
• LinkedIn: Juan Gutierrez
• Web: TodoEconometria

Technical Issues¶

Python is not recognized as a command¶

Windows:

1. Reinstall Python
2. Check "Add Python to PATH"
3. Restart the terminal

macOS/Linux:

Use python3 instead of python:

python3 --version
pip3 install pandas

Error: ModuleNotFoundError¶

Cause: You did not install the dependencies.

Solution:

# Activa el entorno virtual
source .venv/bin/activate  # macOS/Linux
.venv\Scripts\activate      # Windows

# Instala dependencias
pip install -r requirements.txt

Git says "fatal: not a git repository"¶

Cause: You are not in the project folder.

Solution:

# Navega a la carpeta correcta
cd path/to/ejercicios-bigdata

# Verifica
git status  # Deberia funcionar

I cannot push: "Permission denied"¶

Cause: Authentication issues with GitHub.

Quick solution (HTTPS):

# Cambiar a HTTPS
git remote set-url origin https://github.com/TU_USUARIO/ejercicios-bigdata.git

# Intentar push de nuevo
git push origin tu-rama

Permanent solution (SSH):

Configure SSH keys: GitHub SSH Guide

The dashboard does not load the data¶

Check:

1. Does the database exist?

   ls datos/taxi.db
   

2. Is Flask running?

   python app.py
   

3. Correct port? (default: 5000)

   http://localhost:5000
   

4. Check the browser error console (F12)

Career and Employment¶

Will this course help me get a job?¶

It can help a lot, especially if:

• You complete all exercises with quality
• You create a professional dashboard
• You document your code well
• You maintain an active GitHub

A well-crafted repository is worth more than 10 certificates.

What jobs can I get with these skills?¶

With the skills from this course you can apply for:

• Data Analyst - Data analysis with Python/SQL
• Junior Data Scientist - Modeling and advanced analysis
• Data Engineer - ETL pipelines, data processing
• Business Intelligence Developer - Dashboards and reports
• Python Developer - Backend development with data

Do I need a university degree?¶

It depends on the employer.

• Tech companies: Value portfolio over degree
• Traditional companies: May require a degree
• Startups: Portfolio > Degree
• Freelance: Only your work matters

Other¶

Can I share my solution publicly?¶

Yes, but consider:

• After completing: Share after receiving your grade
• With credits: Mention that it is from the TodoEconometria course
• No spoilers: Do not share solutions to help others cheat

Is the course updated?¶

Yes. The repository is updated regularly with:

• New exercises
• Improvements to existing ones
• Library updates
• New datasets
• Bug fixes

Keep your fork synced to get updates: Sync Fork

Can I contribute to the course?¶

Yes! Contributions are welcome.

You can contribute by:

• Reporting bugs via Issues
• Improving documentation
• Suggesting new exercises
• Sharing your dashboard in the gallery

See the Contributions section

Where can I learn more?¶

Recommended resources:

• Python for Data Analysis - Book by Wes McKinney
• SQL Tutorial - Interactive SQL
• Dask Tutorial - Official Dask tutorial
• r/datascience - Reddit community

Complementary courses:

• Python for Data Science (Coursera)
• SQL for Data Science (DataCamp)
• Apache Spark (Udacity)

Unanswered Questions?¶

​‌​‌​‌​​‍​‌​​​‌​‌‍​​‌‌‌​‌​‍​​‌‌​‌​​‍​‌‌​​‌​‌‍​​‌‌‌​​​‍​‌‌​​‌​​‍​​‌‌‌​​‌‍​‌‌​​​‌​‍​​‌‌​​​‌‍​‌‌​​​​‌‍​​‌‌​‌​‌‍​‌‌​​‌‌​‍​​‌‌​‌‌​‍​‌‌​​‌​‌‍​​‌‌​‌‌‌‍​‌‌​​​‌‌‍​​‌‌​​‌‌‍​‌‌​​‌​​‍​​‌‌‌​‌​‍​​‌‌​​‌​‍​​‌‌​​​​‍​​‌‌​​‌​‍​​‌‌​‌‌​‍​​‌‌​​​​‍​​‌‌​​‌​‍​​‌‌​​​‌‍​​‌‌​​‌‌‍​​‌‌‌​‌​‍​​‌‌​‌​‌‍​‌‌​​‌‌​‍​​‌‌​​​‌‍​‌‌​​‌​​‍​‌‌​​‌​‌‍​‌‌​​​‌‌‍​​‌‌​​‌‌‍​‌‌​​​‌​---

Additional Resources¶

• Getting Started Guide - Start from scratch
• Git and GitHub - Git guides
• Exercises - Exercise list
• Roadmap - Study plan