Data Literacy

with Olivier Maugain

In this course, we will talk about the importance of data literacy. Understanding the language of data allows you to use and interpret data effectively. If you want a successful career path, you will most likely need these skills.

4 hours 58 lessons
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Course Overview

Data literacy involves articulating a problem that can potentially be solved using data. Most importantly, it is about interpreting the results of an analysis and making decisions based on the gained insights. A data literate person would have the ability to understand and check the adequacy of the data involved. Ultimately, you should be able to read and derive valuable information from data. We will cover all these topics extensively in the course.

58 High Quality Lessons
4 Practical Tasks
4 Hours of Video
Certificate of Achievement

Topics covered

Business analyticsdata analysismachine learningTheory

What You'll Learn

Being data literate means having the necessary competencies to work with data. Someone who is data literate would have the ability to:

Understand the data sources involved 
Check the adequacy and fitness of data involved 
Interpret the results of an analysis and extract insights 
Make decisions based on the insights 
Articulate a problem that can potentially be solved using data 


Student feedback


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Yh, your courses are explicitly great such hard work is being put in here. I tremendously appreciate them. But as a level 4 course reader now I have some recommendations that could better ease our understanding of the course materials. 1. I understand that animation presentations of lectures are a faster way and quite a good teaching method.. but when I did the Python Bootcamp it was quite better because I felt like someone was talking to me. Hence, I will appreciate it if the tutors showcase themselves as we move through the courses. 2. Although we have practical examples I will love if real-life projects and videos of how workers in the company discuss and solve them, they should be shown or even as a data major intern goes to work and his job descriptions at the office this help us to prepare for the working environment. More projects and problems faced by companies in each course. Thanks. 3. Take us out of the learning environment sometimes surveying companies and showing us how the data is collected.
Data types like Nominal, Ordinal, Interval, Ratio should have better elaboration and examples. There should be relevant tests/questions interspersed between modules so that the student feels confident that s/he is able to understand correctly
Whatever I write here will not be good enough for this course, the way the concepts are presented in a sequential order and clearly explaining about each is Very Exceptional. Thank you Sir, looking forward to more courses from you.
The resources could have been more elaborative containing the minute/subparts of the content, especially for the statistical terms, i.e. its tough to keep the statistical terminologies intact in the head without lecture notes.
Data literacy is almost like a recap to data strategy and lays the foundation for statistics later on. I do wish the class had captions, but I think it turned out alright in the end. Thanks for the great content!
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“This course will be an invaluable experience for your professional development. Data literacy is an absolute must for anyone who wants to be successful in today's business world. Data literacy is the ability to read, understand, create, and communicate data as information.”

Olivier Maugain
Worked at Henkel
Data Literacy

with Olivier Maugain

Start Course