During the remote bootcamp you will learn practical, real-world data science – even if you are an absolute beginner. Our carefully curated pre-bootcamp content will teach you the necessary programming, statistics, machine learning and data science concepts to set you up for long-term success in this field. To be successful in the long term, you need to nurture the solid foundations that data science is built on, while implementing data science practically.
You can request a detailed bootcamp curriculum here.
Fundamentals
Data-related issues are often overlooked – even by practitioners. We emphasize on fundamentals of data exploration, visualization, feature engineering, data manipulation, data quality and imputation, sampling techniques, and more to give you a solid foundation for data science.
Machine Learning
The curriculum covers a wide array of classification, regression, recommendation, text analytics, and unsupervised learning techniques. We emphasize on both understanding the underpinnings of algorithms and their correct usage, given the dataset and business problem.
Evaluation and Parameter Tuning
Correct choice of metrics and parameter tuning are essential to building robust predictive models. A combination of lecture, discussion and hands-on, practical labs will ensure that you have the ability to choose the right metrics for your model and you can tune your machine learning model to make it more generalized or adaptable to new data.
Big Data and Streaming Analytics
Even data scientists need some data engineering skills or understanding of the core infrastructure that supports storing and processing huge amounts of data. You will learn how to set up a Hadoop cluster in the cloud and run Hive queries. You will also learn how to build message queues and process data in real-time. At the end you of this, you will build an Internet of Things application.
Kaggle Competition
Once we start to cover predictive models, attendees will begin working on their predictions for the competition. Winners are announced during the final class period.