BIG DATA

Our Approach:

Four weeks of non stop coding and hard work.

• Week 1 : Develop Essential Skills in Computer Science and Statistics
• Week 2 : Big Data: Build Hadoop Cluster and Master Hive and Clustering
• Week 3 : Go Under the Hood, Java M/R and Classification Problems
• Week 4 : Take Hadoop Certification

Who we are

We are a group of data enthusiasts with years of experience working at leading financial companies on Wall Street. In Jan 2014, we started Bit Bootcamp: an intensive and immersive big data boot camp to spread the knowledge and to address the shortage of good talent in the industry.

The motivation for the bootcamp comes from our own difficulties faced while we were trying to hire new talent. No matter now much money we threw at the problem, we could not find people with the right skills. Then we figured we might as well train them ourselves.

We know the education system is broken. Many online courses have sprung up but with so many options to choose from, there is a genuine lack of direction in learning path and perhaps most importantly, motivation to learn dies after a few weeks of effort. ItÕ•¢Ãƒ•¢Ã¢â‚¬Å¡••¬Ãƒ•¢Ã¢â‚¬Å¾••¢s simply a hard path to travel on your own.

To address all the above stated issues, we have designed a 4 week bootcamp. It will provide you the essential training needed to build a solid career in data analytics.

We focus on commercial grade, time tested solutions to problems candidates are most likely to face in a large data environment either at startups or large enterprises

Upon completion of the course

• Job placement assistance is available via select partner companies, salary range from $75K Õ•¢Ãƒ•¢Ã¢â‚¬Å¡••¬Ãƒ•¢Ã¢â€š•¬Ã…“ $150K
• We will refund the fee if you get a job from our partner network
• You will be surprised by how many job offers you will get on your own
• For example, past graduates have moved on to roles at companies such as Google, American Express, GE Capital, etc.. and some startups
• Network with some very smart folks in the field

Next Steps:

• Drop us a note to schedule an interview and see if this course is a good fit for you.

Big Data and Data Science

Decision science is the brains behind big data analytics. It's not a new field; people have been doing decision science for decades.

In the "old days" data was limited, hence complex algorithms were needed to extract useful insights from the data. Given the shift in the data paradigm, we no longer need very complex algorithms. Instead, we need to run simple stuff at scale.

At the end of the day, it's all about counting smart. In this course, we will learn the essential skills for modern development, keep it simple and implement industry standard algorithms on large datasets.

Decision Science is a mix of Computer Science, Statistics, and Management Skills, we will focus on Computer Science (C) and Statistics (S) in this bootcamp.

We will cover the following topics:
Week 1: Essential Training

• S: Model Development and Validation Lifecycle
• S: Various Distance Algorithms and Matrix Math
• S: Recommendation Systems: Collaborative Filtering
• S: Text Mining : Naive Bayes
• C: Fuzzy String Matching
• C: Setup Development Environment
• C: Unix For Data Science
• C: Java Essential Training
• C: SQL Essential Training

Week 2: Wrangle Big Data

• S: Clustering : Knn, K-mean
• C: Build a Personal Hadoop Cluster of 5 to 10 Nodes
• C: Data Fusion and Ingession from Multiple Sources
• C: Hadoop, Map Reduce, HDFS
• C: HiveQL : SQL on Hadoop
• C: Extended Data Dictionary
• C: Advance Hive, Integration with Python, Perl etc..

Week 3: Java Map Reduce

• S: Classification : C4.5 and CART
• C: Java Map Reduce
• C: Unit Testing
• C: Replicate Hive SQL functionality with Java
• C: Map Reduce Design Patterns
• C: Zookeeper for Coordination

Week 4: Apply and Shine

• Review all the Materials
• Option 1: Data Science Challenge from Kaggle.com (a personal favorite)
• Option 2: Prove your mojo by passing the Hadoop cert

Learning Objective:

• Use Unix to manipulate data in serial and parallel
• Develop Extended Data Dictionaries, to understand data and clean data
• Use SQL to replicate the functionality of Pivot Tables in Excel
• Learn to apply Machine Learning techniques to problems at hand
• Most Important : Learn to converse with data and keep it simple