What is Data Science? from Coursera

Do you want to know why data science has been labeled the sexiest profession of the 21st century? After taking this course, you will be able to answer this question, understand what data science is and what data scientists do, and learn about career paths in the field.

The art of uncovering insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and accurately predicted the Nile River's flooding every year. Since then, people have continued to use data to derive insights and predict outcomes. Recently, they have carved out a unique and distinct field for the work they do. This field is data science.

In today's world, we use Data Science to find patterns in data and make meaningful, data-driven conclusions and predictions.

This course is for everyone and teaches concepts like how data scientists use machine learning and deep learning and how companies apply data science in business.

You will meet several data scientists, who will share their insights and experiences in data science. By taking this introductory course, you will begin your journey into this thriving field.

What's inside

Syllabus

Defining Data Science and What Data Scientists Do

In Module 1, you delve into some fundamentals of Data Science. In lesson 1, you listen to how other professionals in the field define what data science is to them and the paths they took to consider data science as a career for themselves. You explore different roles data scientists fulfill, how data analysis is used in data science, and how data scientists follow certain processes to answer questions with that data. Moving on to Lesson 2, the focus shifts to the daily activities of data scientists. This encompasses learning about various real-world data science problems that professionals solve, the skills and qualities needed to be a successful data scientist, and opinions on how “big data” relates to those skills. You also learn a little about various data formats data scientists work with and algorithms used in the field to process data.

Data Science Topics

In the first lesson in this module, you gain insight into the impact of big data on various aspects of society, from business operations to sports, and develop an understanding of key attributes and challenges associated with big data. You will learn about the big data fundamentals, how data scientists use the cloud to handle big data, and the data mining process. Lesson two delves into machine learning and deep learning and the relationship of artificial intelligence to data science.

Applications and Careers in Data Science

In the first lesson, you learn about the power of data science applications and how organizations leverage this power to drive business goals, improve efficiency, make predictions, and even save lives. You also reviewed the process you will follow as a data scientist to help your organization accomplish these ends. In the second lesson, you investigate what companies seek in a competent, experienced data scientist. You will learn how to position yourself to get hired as a data scientist. Amidst the diverse backgrounds from which data scientists emerge, you identify the qualities they share and skills that consistently set them apart from other data-related roles. You will complete a peer-reviewed final project by looking at a job posting for data scientist and identifying commonalities between the job and what you learned in this course. You will also walk through a case study, where you learn about Sarah and her data science journey.

Data literacy for Data Science (Optional)

This optional module focuses on understanding data and data literacy and is intended to supplement what you learned in the first three modules. As a data scientist, you will need to understand the ecosystem in which your data lives and how it gets manipulated to analyze it. This module introduces you to some of these fundamentals. In lesson one, you explore how data can be generated, stored, and accessed.  In lesson two, you take a deeper dive into data repositories and processes for handling massive data sets.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Builds a strong foundation for beginners interested in data science and develops professional skills and deep expertise in particular topics or sets of topics

Develops core skills for careers in data science and offers hands-on labs and interactive materials

Taught by Rav Ahuja and Alex Aklson, who are recognized for their work in data science and related fields

Covers unique perspectives and ideas that may add color to other topics and subjects

Explores applications of data science in a variety of fields and industries

Optional module on data literacy for data science provides a supplemental understanding of data and its ecosystem

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 What is Data Science? with these activities:

Review foundational statistics concepts

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Strengthen your foundation in statistics to enhance your understanding of data science concepts.

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Review basic statistical concepts such as mean, median, mode, and standard deviation
Practice solving probability problems using Bayes' theorem and other techniques
Explore different data analysis techniques and their applications

Explore online tutorials on machine learning

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Enhance your understanding of machine learning techniques and their practical applications.

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Identify reputable online platforms or resources offering machine learning tutorials
Choose tutorials that align with your skill level and interests
Follow the tutorials step-by-step, implementing the code examples
Experiment with different parameters and datasets to observe the impact on model performance

Join online study groups

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Engage in peer discussions to reinforce concepts and clarify misunderstandings.

Browse courses on Data Science

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Identify relevant discussion forums or online communities focused on data science
Join a group that aligns with your learning goals
Participate actively in discussions, ask questions, and share insights

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Solve data science coding challenges

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Develop your programming skills and problem-solving abilities in a data science context.

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Find online platforms or resources that offer data science coding challenges
Select challenges that align with your skill level and interests
Solve the challenges using appropriate coding techniques and algorithms
Analyze your solutions and identify areas for improvement

Build a data visualization project

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Apply the concepts of data science to create interactive visualizations that communicate insights.

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Identify a dataset of interest
Clean and prepare the data
Choose appropriate visualization techniques
Create an interactive dashboard or presentation
Present your insights to others

Create a blog post or article on a data science topic

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Develop your communication skills and deepen your understanding by explaining data science concepts to others.

Browse courses on Data Science

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Choose a specific topic within data science that interests you
Research and gather information from credible sources
Organize your thoughts and outline your article
Write a clear and engaging blog post or article, explaining the concept in detail
Share your article with others and seek feedback

Participate in data science competitions

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Test your skills and gain practical experience by participating in data science competitions.

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Identify data science competitions that align with your interests and skill level
Form a team or work individually to solve the competition's problem
Apply your knowledge and techniques to develop a solution
Submit your solution and compete with others
Analyze your results and learn from the experience

Mentor aspiring data scientists

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Reinforce your understanding and develop leadership skills by mentoring others.

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Identify opportunities to mentor aspiring data scientists through programs or organizations
Share your knowledge and expertise with your mentees
Provide guidance and support to help your mentees navigate their learning journey
Encourage your mentees to ask questions and seek clarification
Celebrate your mentees' successes and provide constructive feedback

Career center

Learners who complete What is Data Science? will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist is a professional who possesses the technical skills and business understanding to analyze data, extract insights, and communicate findings to inform decision-making. This course provides a comprehensive overview of data science, including its concepts, processes, and applications. By completing this course, you will gain a strong foundation in data science and develop the skills necessary to succeed in this in-demand field.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. This course will introduce you to the fundamental concepts of data analysis and provide you with the skills necessary to perform data analysis tasks effectively. By taking this course, you will be well-prepared to enter the field of data analysis and make valuable contributions to organizations.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

A Machine Learning Engineer is responsible for developing and deploying machine learning models to solve real-world problems. This course provides an introduction to machine learning and explores the different types of machine learning algorithms. By completing this course, you will gain the knowledge and skills necessary to build and deploy machine learning models and advance your career in this exciting field.

See salaries and explore the career path for Machine Learning Engineer

Data Engineer

A Data Engineer is responsible for designing, building, and maintaining data pipelines to ensure the availability and quality of data for analysis. This course provides an overview of data engineering and explores the different tools and technologies used in the field. By completing this course, you will gain the knowledge and skills necessary to build and maintain data pipelines and become a valuable asset to any organization.

See salaries and explore the career path for Data Engineer

Business Analyst

A Business Analyst is responsible for analyzing business processes and identifying areas for improvement. This course provides an overview of business analysis and explores the different tools and techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to perform business analysis tasks effectively and make valuable contributions to organizations.

See salaries and explore the career path for Business Analyst

Data Science Manager

A Data Science Manager is responsible for leading and managing data science teams and projects. This course provides an overview of data science management and explores the different skills and responsibilities of a Data Science Manager. By completing this course, you will gain the knowledge and skills necessary to lead and manage data science teams and projects successfully.

See salaries and explore the career path for Data Science Manager

Statistician

A Statistician is responsible for collecting, analyzing, and interpreting data to make informed decisions. This course provides an overview of statistics and explores the different statistical methods used in the field. By completing this course, you will gain the knowledge and skills necessary to perform statistical analysis tasks effectively and make valuable contributions to organizations.

See salaries and explore the career path for Statistician

Operations Research Analyst

An Operations Research Analyst is responsible for using mathematical and analytical techniques to solve complex business problems. This course provides an overview of operations research and explores the different techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to use operations research techniques to solve business problems effectively.

See salaries and explore the career path for Operations Research Analyst

Financial Analyst

A Financial Analyst is responsible for analyzing financial data and making investment recommendations. This course provides an overview of financial analysis and explores the different techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to perform financial analysis tasks effectively and make sound investment decisions.

See salaries and explore the career path for Financial Analyst

Marketing Analyst

A Marketing Analyst is responsible for analyzing marketing data to identify trends and patterns and make informed marketing decisions. This course provides an overview of marketing analytics and explores the different techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to perform marketing analysis tasks effectively and make valuable contributions to organizations.

See salaries and explore the career path for Marketing Analyst

Software Engineer

A Software Engineer is responsible for designing, developing, and maintaining software applications. This course provides an overview of software engineering and explores the different tools and techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to build and maintain software applications and advance your career in this exciting field.

See salaries and explore the career path for Software Engineer

Computer Scientist

A Computer Scientist is responsible for studying and developing new computing technologies. This course provides an overview of computer science and explores the different areas of research in the field. By completing this course, you will gain the knowledge and skills necessary to conduct research in computer science and make valuable contributions to the field.

See salaries and explore the career path for Computer Scientist

Data Architect

A Data Architect is responsible for designing and managing data architectures to meet the needs of an organization. This course provides an overview of data architecture and explores the different tools and techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to design and manage data architectures and become a valuable asset to any organization.

See salaries and explore the career path for Data Architect

Database Administrator

A Database Administrator is responsible for managing and maintaining databases to ensure the availability and performance of data. This course provides an overview of database administration and explores the different tools and techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to manage and maintain databases and become a valuable asset to any organization.

See salaries and explore the career path for Database Administrator

Information Security Analyst

An Information Security Analyst is responsible for protecting an organization's information assets from unauthorized access, use, disclosure, disruption, modification, or destruction. This course provides an overview of information security and explores the different tools and techniques used in the field. By completing this course, you will gain the knowledge and skills necessary to protect an organization's information assets and become a valuable asset to any organization.

See salaries and explore the career path for Information Security Analyst

What is Data Science?

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