Hands On Training

Statistical Thinking in Python (Part 2)

DataCamp

(3)

1 Coupon Available

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

Part 1 of Statistical Thinking In Python will give you the foundational skills to be a hacker statistician and a probabilistic mindset that can help you dig into data and extract useful information. This course will teach you how to do just that. This course will help you to improve your hacker statistics skills, including hypothesis testing, parameter estimation, statistical inference and hypothesis testing. You will learn by working with real data, culminating in the analysis and interpretation of finches' beaks. This course will give you the skills and knowledge to solve your own inference problems.

Highlights

Pedagogy

Top 20 Percentile

Hands on training

Top 20 Percentile

Rating & Reviews

Top 30 Percentile

Parameters

Pedagogy

Acquire all major Python Programming for Data Science skills in this course for seamless integration into your daily life. Develop a versatile skill set, allowing you to confidently apply what you've learned in various practical scenarios, enhancing your daily experiences and overall proficiency. An exceptional course in Python Programming for Data Science, this stands out for its Self Paced learning approach. Learners have the flexibility to progress at their own speed, tailoring the experience to their individual needs.

Hands on training

This course stands out as one of the top 20 percentile options in Python Programming for Data Science, offering unparalleled hands-on training. Learners gain practical experience and skills through immersive learning, preparing them for real-world challenges. It ensures a well-rounded skill set, catering to a range of learning preferences. With a focus on Hands on training as well as essential Case Based Learning and Virtual Labs, this course is tailored to meet diverse educational needs.

Rating & Reviews

This highly acclaimed course is among the top-rated in Python Programming for Data Science, boasting a rating greater than 4 and an overall rating of 5.0. Its exceptional quality sets it apart, making it an excellent choice for individuals seeking top-notch learning experience in Python Programming for Data Science.

Course Overview

Virtual Labs

International Faculty

Case Based Learning

Post Course Interactions

Case Studies,Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

n this course, you will do just that, expanding and honing your hacker stats toolbox to perform the two key tasks in statistical inference, parameter estimation and hypothesis testing

You will work with real data sets as you learn, culminating with analysis of measurements of the beaks of the Darwin's famous finches

You will emerge from this course with new knowledge and lots of practice under your belt, ready to attack your own inference problems out in the world

Course Content

Expand all sections

Module 1: Parameter estimation by optimization

Module 2: Bootstrap confidence intervals

Module 3: Introduction to hypothesis testing

Module 4: Hypothesis test examples

Course Instructors

Justin Bois

Lecturer at the California Institute of Technology

Justin Bois is a Teaching Professor in the Division of Biology and Biological Engineering at the California Institute of Technology. He teaches nine different classes there, nearly all of which heavi...

Course Reviews

Average Rating Based on 3 reviews

5.0

100%

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