Video Training → IELTS Academic Describing Graphs
Published by: voska89 on 15-07-2022, 11:42 | 
0
MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz
Language: English | Size: 1.07 GB | Duration: 1h 4m
IELTS preparation: Writing Task 1
What you'll learn
Video Training → ESL Business English Presenting/Describing a Chart or Graph
Published by: voska89 on 27-06-2022, 19:56 | 0
Published 06/2022
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 908 MB | Duration: 8 lectures • 2h 28m
Verbally describing line charts with 1 or 2 elements. Taught by an Economist from a business English language school.
Video Training → Linkedin Learning - Data Fluency Exploring and Describing Data
Published by: Minhchick on 19-04-2022, 08:58 | 0
Linkedin Learning - Data Fluency Exploring and Describing Data-XQZT
English | Size: 756.91 MB
Category: Tutorial
Learn the fundamentals of data fluency and how data can help you make better decisions
Video Training → Linkedin - Data Fluency Exploring and Describing Data
Published by: voska89 on 26-03-2022, 10:04 | 0
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 5h 18m | Size: 778.7 MB
Data analysis isn't just for specialists who need to make sense of massive datasets. Decision-makers in every industry can benefit from a basic understanding of the goals and concepts of applied data analysis. In this course, Barton Poulson focuses on the fundamentals of data fluency, or the ability to work with data to extract insights and determine your next steps. Barton shows how exploring data with graphs and describing data with statistics can help you reach your goals and make better decisions. Instead of focusing on particular tools, he concentrates on general procedures that can help you solve specific problems. Barton covers how to prepare and adapt data, explore it visually, and use statistical methods to describe it. He goes in depth on probability and interference and also touches on data ethics and explainable AI.
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