Remote Data Science & Machine Learning Bootcamp

Get bootcamp-ready and hit the ground running with 40 hours of essential training. No matter your previous tech knowledge (or lack of it), our prework makes sure every Ironhacker is set up for success. Start prepping as early as four weeks before the bootcamp.

✅ Python: get introduced to this easy-to-learn programming language commonly used to work with data.
✅ Descriptive Statistics: learn to summarize and detail data features.
✅ Inferential Statistics: make educated guesses about big groups from small samples.
✅ Probability: see how you can predict the odds.
✅ Math Foundations: tackle the essentials of Calculus, Linear Algebra and Analytic Geometry to crack complex patterns and challenges.

Get started by mastering the most commonly used programming languages by real-world Data Scientists.in JavaScript to create well-structured and maintainable code.

✅ Data Science: unlock future predictions from heaps of data.
✅ SQL: master the art of tidying and managing data with ease.
✅ Exploratory Data Analysis: dive deep to uncover interesting patterns and insights.
✅ Statistical Methods: sharpen your skills to decode what the data is really saying.
✅ Python: level up from prework to hands-on mastery with Python's practical features.

Time to build your own AI model! In this module you'll learn machine learning fundamentals and get started on more advanced topics.

✅ Probability and Statistics: amp up your prework knowledge.
✅ Supervised Learning: teach computers with clear examples.
✅ Unsupervised Learning: let computers uncover patterns on their own.
✅ Neural Networks: brain-like tech for smart pattern recognition
✅ Deep Learning: Next-level neural networks (like Siri!)

Explore more specialized career paths with one of these advanced tracks:

✅ Computer Vision: guide computers to recognize and understand images.
✅ Natural Language Processing: enable computers to understand and use human language.
✅ MLOps: manage AI projects smoothly and effectively, leveraging big cloud platforms like Google Cloud or Amazon Web Services to store and handle data on the internet.