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Understanding Data Science

4.8+
428 reviews
Beginner

An introduction to data science with no coding involved.

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2 Hours15 Videos48 Exercises
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Course Description

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!
  1. 1

    Introduction to Data Science

    Free

    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.

    Play Chapter Now
    What is data science?
    50 xp
    Customer segmentation workflow
    100 xp
    Building a customer service chatbot
    100 xp
    Applications of data science
    50 xp
    Assigning data science project
    100 xp
    Investment research
    50 xp
    Data science roles and tools
    50 xp
    Editing a job post
    50 xp
    Matching skills to jobs
    100 xp
    Classifying data tasks
    100 xp
  2. 2

    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.

    Play Chapter Now
    Data sources
    50 xp
    Sorting data sources
    100 xp
    Asthma frequencies
    50 xp
    Data types
    50 xp
    Classifying data types
    100 xp
    Net promoter score
    50 xp
    Activity tracker
    50 xp
    Data storage and retrieval
    50 xp
    Cloud platforms
    50 xp
    Querying a database
    50 xp
    Which type of database?
    100 xp
    Data Pipelines
    50 xp
    Data pipeline characteristics
    50 xp
    Extract Transform Load
    100 xp
  3. 3

    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.

    Play Chapter Now
    Data preparation
    50 xp
    The truth is out there
    50 xp
    Are you prepared?
    100 xp
    Exploratory Data Analysis
    50 xp
    Numerical EDA
    50 xp
    Visual EDA
    50 xp
    Visualization
    50 xp
    Interactive dashboards
    50 xp
    Improving a dashboard
    50 xp
  4. 4

    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.

    Play Chapter Now
    A/B Testing
    50 xp
    Creating an A/B testing workflow
    100 xp
    Statistical significance
    50 xp
    Intermediate results
    50 xp
    Time series forecasting
    50 xp
    Classifying time series data
    100 xp
    Interpret a time series plot
    50 xp
    Supervised machine learning
    50 xp
    When to use supervised learning
    100 xp
    Features and labels
    50 xp
    Model Evaluation
    50 xp
    Clustering
    50 xp
    Supervised vs. unsupervised
    100 xp
    Cluster size selection
    50 xp
    Congratulations!
    50 xp

In the following tracks

Understanding Data Topics
Sara Billen HeadshotSara Billen

Data Scientist at DataCamp

Sara is a graduate of a master's degree in Business Engineering and Marketing Analysis. Prior to working at DataCamp she worked as a Data Science consultant for a Belgian IT company. Sara is passionate about education, data science, and business and loves that she is able to combine all of these disciplines in her job at DataCamp.
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Lis Sulmont HeadshotLis Sulmont

Content Program Manager at Duolingo

Lis holds a Master's degree in Computer Science from McGill University with a focus on computer science education research and applied machine learning. She's passionate about teaching all things related to data and improving the accessibility of these topics.
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Hadrien Lacroix HeadshotHadrien Lacroix

Curriculum Manager at DataCamp

Hadrien has collaborated on 30+ courses ranging from machine learning to database administration through data engineering. He's currently enrolled in a Masters of Analytics at Georgia Tech.

Hadrien started using DataCamp when the platform only had 27 courses. He then joined the Support team and helped students before becoming a Content Developer himself.

Follow Hadrien on LinkedIn
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Don’t just take our word for it

*4.8
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  • Breno G.
    8 days

    Very clear and interactive.

  • Jakub J.
    12 days

    I need to admit that training is very well prepared, all abbreviations are explained so even I was totally noob in this area I would understand all anyway. From my perspective practicing the explained material after each chapter is great to see if I understood what was explained. Thank you!

  • Robert C.
    17 days

    Very good class, I'm using it to work with college Professors, as a professor's consultant. The professors that I have been talking with are having a hard time keeping up with all the changes taking place in the AI and Machine Learning fields. So they are looking for outside help and that is where I come in. I would like to talk with someone from DataCamp to help me put together an hour-long presentation to give to college Juniors and Seniors that talks about why students should be looking into Datacamp AI and Machine Learning courses. My email address is [email protected]

  • SOUMIK S.
    17 days

    Each lesson was comprehensive and informative. The videos and podcasts were very helpful in understanding the material. I also appreciated the availability of help/hint where I could ask questions and get feedback. After displaying the result, each answer was explained with a few sentences. The XP points kept me going. Overall, this was an amazing course that I would highly recommend!

  • AJAY K.
    20 days

    Your provides course understanding Data Science is fullfill curiosity and knowledge about Data Science . Thanks for provide this course.

"Very clear and interactive."

Breno G.

"I need to admit that training is very well prepared, all abbreviations are explained so even I was totally noob in this area I would understand all anyway. From my perspective practicing the explained material after each chapter is great to see if I understood what was explained. Thank you!"

Jakub J.

"Your provides course understanding Data Science is fullfill curiosity and knowledge about Data Science . Thanks for provide this course."

AJAY K.

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