A Crash Course in Data Science from Coursera

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.

This is a focused course designed to rapidly get you up to speed on the field of data science. Our goal was to make this as convenient as possible for you without sacrificing any essential content. We've left the technical information aside so that you can focus on managing your team and moving it forward.

After completing this course you will know.

1. How to describe the role data science plays in various contexts

2. How statistics, machine learning, and software engineering play a role in data science

3. How to describe the structure of a data science project

4. Know the key terms and tools used by data scientists

5. How to identify a successful and an unsuccessful data science project

3. The role of a data science manager

Course cover image by r2hox. Creative Commons BY-SA: https://flic.kr/p/gdMuhT

What's inside

Syllabus

A Crash Course in Data Science

This one-module course constitutes the first "week" of the Executive Data Science Specialization. This is an intensive introduction to what you need to know about data science itself. You'll learn important terminology and how successful organizations use data science.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches the essential terminology in data science, which is the foundation for deeper study

Taught by leading data science educators Roger D. Peng, PhD, Jeff Leek, PhD, Brian Caffo, PhD, which provides learners with access to their expertise

Introduces learners to the structure of a data science project so they can manage data scientists to fulfill organizational initiatives

Provides a solid foundational understanding to students new to data science, enabling them to engage with the field from a well-rounded perspective

Provides an overview of how data science is used in various contexts, making it valuable to professionals across industries

Course materials are not available after the course ends, which may limit the learner's ability to access information they need later

Reviews summary

Brief data science overview

learners say this course is a great introduction to the field of data science, especially for those without a technical background. It provides a high-level overview of the key concepts, tools, and processes involved in data science projects. The course is well-structured, engaging, and informative, with clear explanations and real-life examples. However, some learners may find the content too basic or superficial, and the quizzes can be frustrating at times.

This course is designed to be accessible to beginners, with no prior knowledge of data science required.

"Great Data Science introductory course for people without previous knowledge"

"Small and sweet this only I can say for the course. Nice and productive content."

"Nice course for the beginners to start with and gain confidence to learn more and more."

This course provides a high-level overview of the field of data science, covering the key concepts, tools, and processes involved.

"This was a great course and alot of information to used daily at work."

"Definitely a good overview and introduction to learning about data science. Helps to know where to go next."

"A great introductory course to get a general idea about the Data Science field."

The course provides numerous real-life examples and case studies to illustrate the concepts and applications of data science.

"Great course with concise explanations and examples that are very useful"

"Interesting overview of what is Data Science. I definitely will look for other related courses."

"Loved how the course flows smoothly, connecting all the dots of the data science world!"

The instructors in this course use clear and concise language to explain complex concepts in a way that is easy to understand, even for beginners.

"Great course with concise explanations and examples that are very useful"

"The sessions were jam-packed with information and insights. Very engaging profs!"

"Simple content, Very useful examples. Instructors deliver in a easy to understan"

Some learners found the content of this course to be too basic or superficial, providing only a high-level overview of the field.

"I know its a crash course, but probably need to be less general management stuff and more on data science"

"It's a nice to starting course, thanks for the effort on developing and keep updating with new cases, tools and info."

"This course is for someone who is already an expert in this field."

Some learners found the quizzes in this course to be frustrating, as they were often difficult to pass and did not provide clear feedback.

"The course is amazing for beginners and gives a clear idea about data science "

"Test questions seem haphazard and do not appear to be validated. It feels like they are written by a bad AI algorithm."

"I felt that the content of this course was too little. It should go one level deeper and explain the challenges that managers may face when handling data science projects."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in A Crash Course in Data Science with these activities:

Review Statistics, Machine Learning, and Data Science Concepts

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Prepares students for the vocabulary and concepts of data science by reviewing existing knowledge in statistics, machine learning, and data science

Browse courses on Statistics

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Review your lecture notes from previous courses in statistics or machine learning.
Go through online tutorials or videos on data science.

Glossary of Data Science Terms

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Reinforces understanding of data science terminology and concepts.

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Create a list of key data science terms from the course.
Define each term clearly and concisely.

Data Analysis Exercises Using Python or R

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Solidifies data analysis skills and knowledge of Python or R through practice exercises.

Browse courses on Python

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Install Python or R and its necessary libraries.
Find datasets online and practice data cleaning, exploration, and visualization.

Three other activities

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Show all six activities

Discussion Group on Data Science Applications

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Provides a platform for students to exchange ideas and learn from each other's experiences in applying data science.

Browse courses on Data Science Applications

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Form a study group with classmates.
Discuss real-world examples of data science applications.
Share insights and best practices.

Data Visualization Dashboard

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Demonstrates the student's ability to communicate data insights through visual representation.

Browse courses on Data Visualization

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Choose a dataset and identify the key insights you want to convey.
Use Tableau or Power BI to create interactive visualizations.
Present your dashboard to your classmates or colleagues.

Mini Data Science Project

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Allows students to apply their knowledge and skills to a real-world problem, fostering critical thinking and problem-solving abilities.

Browse courses on Data Science Project

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Identify a problem or opportunity that can be addressed using data science.
Collect and clean the necessary data.
Analyze the data and develop insights.
Communicate your findings and recommendations.

Career center

Learners who complete A Crash Course in Data Science will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists work to solve business problems with data. They combine knowledge of mathematics, statistics, and computer science to uncover insights in data that can be used to improve efficiency and make better decisions. If you are looking to work as a Data Scientist, this course can help you develop the foundaiton necessary to be successful in this field.

See salaries and explore the career path for Data Scientist

Data Science Manager

Data Science Managers lead teams of data scientists and oversee the development and implementation of data science projects. They use their knowledge of data science to make informed decisions about how to use data to solve business problems. This course can help prepare you for a career as a Data Science Manager by providing you with a strong understanding of the field. You will also learn how to manage teams of data scientists and how to communicate the results of data science projects to stakeholders.

See salaries and explore the career path for Data Science Manager

Data Architect

Data Architects design and implement data management solutions that ensure data is accessible, reliable, and secure. They use their knowledge of data science to understand the business needs of an organization and to design data systems that meet those needs. If you enjoy solving complex problems and have a passion for data, a career as a Data Architect may be a good fit for you.

See salaries and explore the career path for Data Architect

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems in business and industry. They develop models to improve efficiency, reduce costs, and make better decisions. If you have a strong foundation in mathematics and statistics, and you are interested in a career in operations research, this course can help you develop the skills you need to be successful.

See salaries and explore the career path for Operations Research Analyst

Data Engineer

Data Engineers design, build, and maintain data pipelines that make data available for analysis. They use their knowledge of data science to ensure that data is clean, accurate, and reliable. This course provides a strong foundation in the field of data science, which can help prepare you for a rewarding career as a Data Engineer.

See salaries and explore the career path for Data Engineer

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. This course can help you develop the skills you need to be successful as an Actuary by providing you with a strong foundation in data science, statistics, and risk management.

See salaries and explore the career path for Actuary

Business Analyst

Business Analysts gather and analyze data to help companies make better decisions. They use data to understand the needs of customers, identify trends, and improve efficiency. This course can help you develop the skills necessary to be successful as a Business Analyst by providing you with a foundation in data science, statistics, and machine learning.

See salaries and explore the career path for Business Analyst

Machine Learning Engineer

Machine Learning Engineers build the algorithms that enable computers to interpret data and make predictions. They use data science to give computers the ability to learn without being explicitly programmed. This course helps you understand the role of machine learning in data science. By understanding the vocabulary and the objectives of data science, you may find that you wish to pursue a career in this dynamic and lucrative field.

See salaries and explore the career path for Machine Learning Engineer

Risk Analyst

Risk Analysts use data to identify, assess, and mitigate risks. They work in a variety of industries, including finance, insurance, and healthcare. This course can help you develop the skills you need to be successful as a Risk Analyst by providing you with a strong foundation in data science, statistics, and risk management.

See salaries and explore the career path for Risk Analyst

Statistician

Statisticians collect, analyze, interpret, and present data. This course helps you understand how statistics play an important role in data science. The role of a Statistician may be a good fit for you if you are detail-oriented, organized, and analytical.

See salaries and explore the career path for Statistician

Quantitative Analyst

Quantitative Analysts use mathematical and statistical modeling to analyze financial data. They develop models to predict risk, price securities, and make investment decisions. If you have a strong foundation in mathematics and statistics, and you are interested in a career in finance, this course can help you develop the skills you need to be successful as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Insurance Analyst

Insurance Analysts use data to assess risk and determine insurance premiums. They work for insurance companies and other financial institutions. This course can help you develop the skills you need to be successful as an Insurance Analyst by providing you with a strong foundation in data science, statistics, and risk management.

See salaries and explore the career path for Insurance Analyst

Data Analyst

A Data Analyst examines and interprets data to help companies make informed decisions. Data plays a key role in understanding marketing strategy, financial planning, and how to improve customer experience. A Crash Course in Data Science can help you build the foundation you need to understand the basics of data analysis, and may put you on the path towards a new career.

See salaries and explore the career path for Data Analyst

Market Research Analyst

Market Research Analysts use data to understand consumer behavior and market trends. They work for a variety of companies, including marketing firms, product development companies, and consulting firms. This course can help you develop the skills you need to be successful as a Market Research Analyst by providing you with a strong foundation in data science, statistics, and marketing.

See salaries and explore the career path for Market Research Analyst

Software Engineer

Software Engineers design, develop, test, and maintain software applications. They use programming languages to implement solutions to business problems. A Crash Course in Data Science may be helpful as your company begins to use data science tools. This course can put you in the position to be a leader in bringing data science to your company.

See salaries and explore the career path for Software Engineer