A Crash Course in Data Science

  • 4.5
Approx. 7 hours to complete

Course Summary

This course provides a comprehensive introduction to data science, covering topics such as data wrangling, visualization, and modeling. Students will learn how to use popular tools like Python, R, and SQL to solve real-world problems.

Key Learning Points

  • Gain practical skills in data analysis and machine learning
  • Learn to use popular data science tools like Python and R
  • Apply your skills to real-world problems and projects

Job Positions & Salaries of people who have taken this course might have

    • USA: $62,453
    • India: ₹428,367
    • Spain: €28,345
    • USA: $62,453
    • India: ₹428,367
    • Spain: €28,345

    • USA: $96,072
    • India: ₹1,071,026
    • Spain: €33,196
    • USA: $62,453
    • India: ₹428,367
    • Spain: €28,345

    • USA: $96,072
    • India: ₹1,071,026
    • Spain: €33,196

    • USA: $112,117
    • India: ₹1,308,254
    • Spain: €40,000

Related Topics for further study


Learning Outcomes

  • Develop practical skills in data analysis and modeling
  • Understand the fundamentals of data science
  • Apply your skills to real-world projects and problems

Prerequisites or good to have knowledge before taking this course

  • Basic knowledge of programming concepts
  • Familiarity with statistics and linear algebra

Course Difficulty Level

Beginner

Course Format

  • Online
  • Self-paced

Similar Courses

  • Applied Data Science with Python
  • Machine Learning
  • Data Science Essentials

Related Education Paths


Related Books

Description

By now you have definitely heard about data science and big data. In this one-week class, we will provide a crash course in what these terms mean and how they play a role in successful organizations. This class is for anyone who wants to learn what all the data science action is about, including those who will eventually need to manage data scientists. The goal is to get you up to speed as quickly as possible on data science without all the fluff. We've designed this course to be as convenient as possible without sacrificing any of the essentials.

Knowledge

  • Describe Data Science’s role in various contexts
  • Understand how Statistics and Machine Learning affect Data Science
  • Use the key terms used by data scientist
  • Predict whether a Data Science project will be successful

Outline

  • A Crash Course in Data Science
  • About Your Instructors
  • What is Data Science?
  • Statistics by example activities
  • Machine learning, the basics
  • Machine learning further reading
  • What is Software Engineering for Data Science?
  • The Structure of a Data Science Project
  • The outputs of a data science experiment
  • The four secrets of a successful data science experiment
  • Data Scientist Toolbox
  • Separating Hype from Value
  • Specialization Textbook
  • Grading
  • Pre-Course Survey
  • Statistics by example activities
  • Machine learning
  • The outputs of a data science experiment
  • The four secrets of a successful data science experiment
  • Post-Course Survey
  • What is data science?
  • What is statistics good for?
  • Machine learning
  • Quiz: Software Engineering
  • Structure of a Data Science Project
  • The outputs of a data science experiment
  • Defining Success in Data Science
  • Data scientist toolbox
  • Separating hype from value

Summary of User Reviews

Learn data science with this comprehensive course on Coursera. Students praise the course for its engaging content and practical approach. With a focus on real-world applications, this course is a great choice for anyone looking to gain skills in data science.

Key Aspect Users Liked About This Course

The practical approach and real-world applications are highly praised by many users.

Pros from User Reviews

  • Engaging content that keeps students interested throughout the course
  • Practical approach to learning data science that prepares students for real-world applications
  • Experienced instructors with a wealth of knowledge and expertise in data science

Cons from User Reviews

  • Some users feel that the course is too basic and doesn't cover advanced topics
  • The course can be time-consuming and requires a significant amount of effort to complete
  • The pace of the course may be too fast for some users who are new to data science
English
Available now
Approx. 7 hours to complete
Jeff Leek, PhD, Brian Caffo, PhD, Roger D. Peng, PhD
Johns Hopkins University
Coursera

Instructor

Jeff Leek, PhD

  • 4.5 Raiting
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