Data Literacy

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.

with Olivier Maugain

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

Skills you will gain

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

Curriculum

Introduction to Data Literacy

5 Lesson 24 Min

What Exactly is Data Literacy Free Why do We Need Data Literacy Free Data-driven Decision Making Benefits of Data Literacy How to Get Started
Understanding Data

17 Lesson 62 Min

Data Definition Free Qualitative vs. Quantitative Data Free Structured vs. Unstructured Data Data at Rest vs. Data in Motion Transactional vs. Master Data Big Data Storing Data Database Data Warehouse Data Marts The ETL Process Apache Hadoop Data Lake Cloud Systems Edge Computing Batch vs. Stream Processing Graph Database Free
Using Data

16 Lesson 71 Min

Analysis vs. Analytics Descriptive Statistics Inferential Statistics Business Intelligence (BI) Artificial Intelligence (AI) Machine Learning (ML) Free Supervised Learning Regression Analysis Time Series Forecasting Classification Unsupervised Learning Clustering Analysis Association Rules Reinforcement Learning Deep Learning Natural Language Processing (NLP) Free
Reading Data

5 Lesson 30 Min

Reading Data Data Quality Assessment Data Description Measures of Central Tendency Measures of Spread
Interpreting Data

15 Lesson 65 Min

Interpreting Data Correlation Аnalysis Free Correlation Coefficient Correlation and Causation Simple Linear Regression R-squared Forecasting Forecast Errors Statistical Tests Hypothesis Testing P-Value Statistical Significance Classification Models Accuracy Free Recall and Precision

“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

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