Hands On Training

Statistical Simulation in Python

DataCamp

(3)

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Simulations are a type if computational algorithm that use the simple idea random sampling to solve increasingly complex problems. Although simulations have been around since ancient times they have gained popularity with the rise in computational power. Simulations are used in many areas, including Artificial Intelligence, Physics, Computational Biology and Finance. To simulate data and generate them, NumPy will be used. Simulators with simple, real-world examples will be used to give students hands-on experience.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Statistical Thinking in Python (Part 2)

What You Will Learn

Learn to solve increasingly complex problems using simulations to generate and analyze data

We will then learn how to run a simulation by first looking at a simulation workflow and then recreating it in the context of a game of dice

We'll look at a number of examples of modeling the data generating process and will conclude with modeling an eCommerce advertising simulation

We will get a taste of bootstrap resampling, jackknife resampling, and permutation testing

We'll work through a business planning problem, learn about Monte Carlo Integration, Power Analysis with simulation and conclude with a financial portfolio simulation

Course Content

Expand all sections

Module 1: Basics of randomness simulation

Module 2: Probability data generation process

Module 3: Resampling methods

Module 4: Advanced Applications of Simulation

Course Instructors

Tushar Shanker

Data Science Manager at Uber

Tushar currently leads the UberEats Marketing Data Science team at Uber, with a focus on improving global marketing efficiency across various channels like Facebook and Google. Before Uber, Tushar le...

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