“Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.” ― Richard Feynman

Math literacy, including proficiency in Linear Algebra and Statistics, is a must for anyone pursuing a career in data science. The goal of this workshop is to introduce some key concepts from these domains that get used repeatedly in data science applications. Our approach is what we call the “Hacker’s way”. Instead of going back to formulae and proofs, we teach the concepts by writing code. And in practical applications. Concepts don’t remain sticky if the usage is never taught.

The focus will be on depth rather than breadth. Three areas are chosen - Hypothesis Testing, Supervised Learning and Unsupervised Learning. They will be covered to sufficient depth - 50% of the time will be on the concepts and 50% of the time will be spent coding them.

*Math Concepts*

- Basic Metrics: Mean, Variance, Covariance, Correlation
- Discrete Probability Distributions: Bernoulli, Binomial
- Cumulative Mass Function, Probability Mass Function
- Continuous Probability Distributions: Poisson, Uniform, Normal, Beta, Gamma
- Cumulative Distribution Function, Probability Density Function

*ML Applications*

- Direct Simulation
- Shuffling
- Hypothesis Testing for Continuous Distribution: t-test
- Hypothesis Testing for Discrete Distribution: chi-squared test
- Application to A/B Testing

*Math Concepts*

- Basics of Matrix Operation
- Matrix Determinant, Inverse
- Basics of Linear Algebra
- Solve for
`Ax=b`

for`nxn`

- Solve for
`Ax=b`

for`nxp+1`

*ML Applications*

- Linear Regression
- L2 Regularization
- MLE, Gradient Descent
- Bootstrapping
- Linear Classification

*Math Concepts*

- Matrix Projections
- Solve for
`Ax=λx`

for`nxn`

- Eigenvectors & Eigenvalues

*ML Applications*

- Dimensionality Reduction
- Principle Component Analysis
- Cluster Analysis

- Someone with a background in programming who wants to pick the math needed for data science and get a flavor for different data science problems
- Someone who is a beginner in data science or has been doing data analysis (at least using Excel at a minimum) and wants to pick skills to take the next step in their data science career

- Programming knowledge is mandatory. Attendee should, at the bare minimum, be able to write conditional statements, use loops, be comfortable writing functions and be able to understand code snippets and come up with programming logic.
- Participants should have a basic familiarity of Python. Specifically, we expect participants to know the first three sections from this: http://anandology.com/python-practice-book/

We will be using Python data stack for the workshop. Please install Ananconda for Python 3.5 for the workshop. That has everything we need for the workshop. For attendees more curious, we will be using Jupyter Notebook as our IDE. We will be introducing numpy, scipy, seaborn, matplotlib, statsmodel and scikit-learn.

The working repo for this workshop is at https://github.com/amitkaps/hackermath/

The workshop would be charged at Rs. 150,000 per day (for Indian locations) or USD 5,000 per day (for International locations). Service tax and other government charges as applicable will be additional. Also, for sessions conducted outside of Bangalore, the facilitator’s travel and accommodation cost would be charged on actuals.

Amit Kapoor is interested in learning and teaching the craft of telling visual stories with data. He is the founder partner at narrativeVIZ Consulting, where he teaches data-science, data-visualisation and data-stories as tools for improving communication, persuasion, and leadership and conducts workshops on these topics for businesses, nonprofits, and academic institutes. He also teaches visualisation as a guest faculty in design context at NID, Bangalore and in management context at IIM Bangalore & IIM Ahmedabad

His background is in strategy consulting in using data-driven stories to drive change across organizations and businesses. He has more than 15 years of management consulting experience, first with AT Kearney in India, then with Booz & Company in Europe and more recently for startups in Bangalore. He did his B.Tech in Mechanical Engineering from IIT, Delhi and PGDM (MBA) from IIM, Ahmedabad. You can find more about him at amitkaps.com and tweet him at @amitkaps.