Introduction to Data Science

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Lavanya Vijayan and Madecraft

2:00:55

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01 - Introduction

01 - Beginning your data science exploration.mp4

00:55

02 - 1. Defining Data Science

01 - Demystifying data science.mp4

03:55

02 - The value of data science.mp4

01:52

03 - Defining the data science life cycle.mp4

00:54

03 - 2. Starting with Data Design

01 - Reducing bias with probability sampling.mp4

04:00

02 - Using non-probability sampling.mp4

02:32

04 - 3. Utilizing Computational Tools

01 - Comparing Python and R.mp4

02:16

02 - Setting up your Jupyter environment.mp4

03:32

05 - 4. Structuring Your Tabular Data

01 - Defining tabular data.mp4

02:41

02 - Reading tabular data.mp4

06:13

03 - Interpreting tabular data.mp4

02:29

04 - Gathering insights.mp4

05:53

05 - Answering specific questions.mp4

02:45

06 - 5. Using Exploratory Data Analysis

01 - Defining exploratory data analysis.mp4

00:51

02 - Recognizing statistical data types.mp4

03:22

03 - Distinguishing properties of data.mp4

05:08

07 - 6. Cleaning Your Data

01 - Explaining data cleaning.mp4

01:22

02 - Questions to guide data cleaning.mp4

04:07

08 - 7. Using Data Visualization

01 - Demystifying data visualization.mp4

01:02

02 - Visualizing your qualitative data.mp4

05:17

03 - Visualizing your quantitative data.mp4

08:08

09 - 8. Using Inference and Statistical Analysis

01 - Defining inference.mp4

00:43

02 - Designing a hypothesis test.mp4

05:13

03 - Creating a permutation.mp4

04:13

04 - Conducting a permutation test.mp4

06:35

05 - Bootstrapping a confidence interval.mp4

07:56

10 - 9. Using Prediction in Data Science

01 - Defining prediction for data science.mp4

01:46

02 - Navigating classification.mp4

02:07

03 - Recognizing the k-NN algorithm.mp4

03:13

04 - Implementing k-Nearest Neighbors.mp4

07:29

05 - Navigating regression.mp4

02:52

06 - Checking assumptions of regression.mp4

02:20

07 - Implementing linear regression.mp4

06:09

11 - Conclusion

01 - Next steps.mp4

01:05

Description

The world of data science is reshaping every business, regardless of industry, location, or role. And there’s never been a better time to get up to speed and learn the basics of this booming field. In this course, designed specifically for beginners, explore the world of data science, its opportunities and innovations, and the fundamental skills required for success.

Join Python trainer and data science expert Lavanya Vijayan as she shares what data science is and how it differs from other common data-related careers. Discover some of the most important tools used in the trade to develop your understanding of data libraries and data manipulation. Along the way, get an introduction to exploratory data analysis, data cleaning, data visualization, sampling, testing, estimating, and more. By the end of this course, you’ll know how to use inference and statistical analysis to make more reliable predictions for your business.

This course was created by Madecraft. We are pleased to host this training in our library.

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Data Science

Lavanya Vijayan and Madecraft

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.