Overview

An introduction to data science with no coding involved.

What is data science, why is it so popular, and why did the Harvard Business Review hail it as the “sexiest job of the 21st century”? In this non-technical course, you’ll be introduced to everything you were ever too afraid to ask about this fast-growing and exciting field, without needing to write a single line of code. Through hands-on exercises, you’ll learn about the different data scientist roles, foundational topics like A/B testing, time series analysis, and machine learning, and how data scientists extract knowledge and insights from real-world data. So don’t be put off by the buzzwords. Start learning, gain skills in this hugely in-demand field, and discover why data science is for everyone!

Syllabus

Introduction to Data Science

We'll start the course by defining what data science is. We'll cover the data science workflow and how data science is applied to real-world problems. We'll finish the chapter by learning about different roles within the data science field.

Data Collection and Storage

Now that we understand the data science workflow, we'll dive deeper into the first step: data collection and storage. We'll learn about the different data sources you can draw from, what that data looks like, how to store the data once it's collected, and how a data pipeline can automate the process.

Preparation, Exploration, and Visualization

Data preparation is fundamental: data scientists spend 80% of their time cleaning and manipulating data, and only 20% of their time actually analyzing it. This chapter will show you how to diagnose problems in your data, deal with missing values and outliers. You will then learn about visualization, another essential tool to both explore your data and convey your findings.

Experimentation and Prediction

In this final chapter, we'll discuss experimentation and prediction! Beginning with experiments, we'll cover A/B testing, and move on to time series forecasting where we'll learn about predicting future events. Finally, we'll end with machine learning, looking at supervised learning, and clustering.

Taught by

Hadrien Lacroix, Sara Billen and Lis Sulmont

Reviews

4.5 rating, based on 2 Class Central reviews

4.8 rating at DataCamp based on 507 ratings

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Harman Singh

It was a cool course. Quite easy though, so not as challenging as I would have wanted; I got most questions right by guessing if I did not know them outright
Zarnigor Xudoyberdiyeva @zakilamee

"Understanding Data Science" is an exceptional course that provides a comprehensive overview of the dynamic field of data science. This well-structured and engaging program offers a deep dive into the core concepts, tools, and methodologies essentia…

"Understanding Data Science" is an exceptional course that provides a comprehensive overview of the dynamic field of data science. This well-structured and engaging program offers a deep dive into the core concepts, tools, and methodologies essential for extracting insights from data. The course brilliantly covers a wide range of topics, including statistics, machine learning, data visualization, and data analysis techniques. The clear and concise explanations, coupled with hands-on exercises, ensure a solid understanding of key principles. The instructors exhibit a remarkable ability to demystify complex concepts, making them accessible to learners of all levels. Moreover, the real-world examples and case studies presented throughout the course lend practical insight into the application of data science. "Understanding Data Science" is a must for anyone looking to embark on or advance in their data science journey.

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