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!

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.
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