Data Science and Machine Learning Bootcamp

Prepare for your training and get started with 40 hours of foundational prep work. Whether you already have Tech knowledge or not, our preparatory phase ensures every Ironhack student is ready to hit the ground running. Start preparing up to four weeks before the Bootcamp begins.

✅ Python: discover this easy-to-learn programming language widely used in data work.
✅ Descriptive statistics: learn how to summarize and describe the key characteristics of data.
✅ Inferential statistics: make informed assumptions about large datasets based on small samples.
✅ Probability: learn how to predict future outcomes.
✅ Mathematical foundations: cover the essentials of calculus, linear algebra, and analytical geometry to break down complex models and challenges.

Data Science Foundations: Python and the Basics of Data Manipulation. Start by mastering the programming languages most widely used by today’s data scientists.

✅ Data Science: discover how to “predict” the future using data.
✅ SQL: master the art of organizing and managing data with ease.
✅ Exploratory Data Analysis: go deeper to uncover meaningful patterns and insights.
✅ Statistical methods: sharpen your skills to decode the true meaning of data.
✅ Python: move from preparation to hands-on practice using Python’s core features.

It’s time to build your own AI model! In this module, you’ll learn the fundamentals of Machine Learning and dive into more advanced concepts.

✅ Probability and statistics: deepen your existing knowledge.
✅ Supervised learning: teach computers using clear, labeled examples.
✅ Unsupervised learning: let computers discover patterns on their own.
✅ Neural networks: technology designed for intelligent pattern recognition.
✅ Deep Learning: next-level neural networks (like Siri!).

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

✅ Computer Vision: teach computers to recognize and understand images.
✅ Natural Language Processing: enable computers to understand and work with human language.
✅ MLOps: manage AI projects smoothly and efficiently, using cloud platforms such as Google Cloud or Amazon Web Services to store and manage data online.