Statistical Thinking in Python (Part 2)
Course Report
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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
Highlights
Rating & Reviews
Top 30 Percentile
Pedagogy
Top 20 Percentile
Hands on training
Top 20 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.
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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.
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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.
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Course Overview
Virtual Labs
International Faculty
Case Based Learning
Post Course Interactions
Case Studies,Hands-On Training,Instructor-Moderated Discussions
Skills You Will Gain
Prerequisites/Requirements
Statistical Thinking in Python (Part 1)
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 Instructors
Justin Bois
Lecturer at the California Institute of Technology
Course Reviews
Average Rating Based on 3 reviews
100%