Data Literacy

Price
$795.00

Duration
1 Day

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

Data literacy is the ability to read, understand, create, and communicate data as information. Much like literacy as a general concept, data literacy focuses on the competencies involved in working with data. This Data Literacy training is designed to give you a high level overview of the key topics in Data Science and Machine Learning.

Course Objectives

In this course you’ll learn the fundamental concepts relating to data, allowing you to understand what makes data suitable for data analysis, visualization and machine learning.
Then we’ll give you a quick overview of important statistical topics, such as mean, standard deviation, and the normal distribution.
Afterwards you will learn the different ways data scientists are able to visualize data to convey their ideas in a clear manner.
We’ll also teach you about the machine learning process, acquiring data, cleaning data, and an overview of the train/test split philosophy that supervised learning adheres to.
Then we’ll show you some examples of regression and classification algorithms, as well as how to evaluate their results.
We’ll also explore what the future holds by taking a peek at the bleeding edge of AI and ML, including DALLE-2 and GPT-3!

Who Should Attend?

Designed exclusively for students who want to learn about the basics of data science and machine learning at a high level, without needing to learn how to code or cover complex mathematics.

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Course Prerequisites

There are no prerequisites for this course.

Agenda

Data and Opportunities
Data Quality
Understanding Big Data
Data Measurements
- Understanding Central Tendency
- Understanding Dispersion
- Understanding Data Analysis
- Tour of Data Visualizations
- Probability and Uncertainty
- Testing theories and hypotheses
Probability and Statistics Overview
Machine Learning Overview
Understanding Machine Learning Concepts
Supervised Learning Overview
Unsupervised Learning Overview
Dimensionality Reduction Overview
The Future of Data, ML, and AI
Overview of Deep Learning Concepts
What’s next for AI and ML