Data Science Bootcamp
One-week comprehensive training
4,000 working professionals from
1,000 companies globally.
Comprehensive curriculum
Our data science bootcamp has been attended by 4000 people around the globe. Our teaching team consists of leading data scientists and practitioners who are also passionate about teaching. We have created the most comprehensive short duration curriculum in the industry. We focus on problem solving in real-world business context while providing the right balance between theory and practice.
Course details
5-day, in-person bootcamp
Monday – Friday, 8:00am – 6:00pm
Intensive 50 hrs learning
In-classroom lectures and discussions
Coding exercises and model building labs
Networking dinner
5 hrs prep work before bootcamp
10 hrs homework online
Prerequisites
None. We will teach you the tools needed for the bootcamp.
Fundamentals
Fundamentals for data scientists
Data-related issues are often overlooked – even by practitioners. We emphasize on fundamentals of data exploration, visualization, feature engineering, quality, acquisition and sampling to give you a solid foundation to predictive analytics.
Agenda: Day 1
- Introduction
- Data Exploration
- Data Visualization
- Feature Engineering with R
- Getting Started with Predictive Analytics
- Introduction to Classification Models
Machine Learning
Developing machine learning models
The curriculum covers a wide array of classification, regression, recommendation and unsupervised learning techniques. We emphasize on both of solid understanding of algorithms and their correct usage.
Agenda – Days 2-3
- Building a Predictive Model in R
- Building Generalized Predictive Models
- Deploying a Predictive Model as a Web Service
- Introduction to Ensemble Methods
- Build Your Own Model
- Unsupervised Learning and K-means Clustering
- Text Analytics Fundamentals + Hands-on Lab
Agenda – Day 4
- Introduction to Regression + Hands-on Lab
- Recommender Systems Fundamentals
- Create Your Own Recommemder
Evaluation and Tuning
Model 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 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 generalizable.
Agenda – Days 2-4
- Evaluation of Classification Models
- Cross Validation
- Online Experimentation
- A/B Testing
- Evaluation of Regression Models
Big Data Engineering
Big data engineering and streaming analytics
Even data scientists need some data engineering skills. You will Hadoop cluster in the cloud and run Hive queries. You will also learn to build message queues and process data in real-time. At the end you will build an Internet of Things application.
Agenda – Day 5
- Big Data Engineering
- Distributed Systems
- Deploy Your Own Hadoop Cluster
- Data Ingestion
- Stream Processing
- IOT Hackathon
Kaggle Competition
Kaggle competition and capstone
Starting on day 3, all attendees compete in an in-class Kaggle competition. Kaggle’s Titanic survival prediction competition is the perfect testing ground to cut your teeth on. Winners are announced on the last day of the bootcamp,with the top 2-3 contenders receiving a special prize.
After the Bootcamp
Post-bootcamp homework (optional)
Data science learning is a lifelong journey. We have 10+ hours of video tutorials, R and Python Jupyter notebooks, webinars that will ensure that you keep learning.
- Naive Bayes
- Logistic Regression
- Intro to NoSQL Databases
- Self Directed Labs
- Kaggle Mentoring*
*depends on the package you register with
Real people. Real Projects. Real impact.
Right from day one of the bootcamp, our emphasis is to cultivate a think-business-first mindset. Bootcamp attendees leave with the ability to put machine learning, data analysis, and artificial intelligence skills in a business context.
Leading Fortune-500 companies are our recurring clients because our training adds real business value.
More than just a bootcamp
When you sign up, you sign up for an experience.