Description
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.
Objectives
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!
Target audience
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.- 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
There are no prerequisites for this course.