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Data Science Fundamentals for Data Analysts

In this course we're going to guide you through the fundamental building blocks of data science, one of the fastest-growing fields in the world!

With the help of our industry-leading data scientists, we’ve designed this course to build ready-to-apply data science skills in just 15 hours of learning. First, we’ll give you a quick introduction to data science - what it is and how it is used to solve real-world problems. For the rest of the course, we'll teach you the skills you need to apply foundational data science concepts and techniques to solve these real-world problems.

By the end of this course, you'll be able to leverage your existing data analysis skills to design, execute, assess, and communicate the results of your very own data science projects.

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What's inside

Syllabus

Welcome to the Course

Module description.

An Introduction to Data Science

Introductory Statistics for Data Science

Connecting Data Science to the Real World

Practical Machine Learning

Completing Data Science Projects

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Explores foundational concepts of data science, aimed at beginners new to the field

Teaches foundational data science concepts and techniques to solve real-world problems

Instructed by industry-leading data scientists

Provides practical skills in data science, statistics, and machine learning

Suitable for those with existing data analysis skills seeking to expand their knowledge in data science

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Reviews summary

Data science fundamentals for data analysts

Learners say this course is a good foundation for beginners in data science. According to students, its practical labs, clear instruction, and industry-relevant lessons make it a worthwhile course to take. However, a few learners noted the need to update the course material and peer review process and found some assignments unclear.

Easy-to-follow for those new to data science.

"This can be a good course for data science beginners,..."

Up-to-date lessons connect to real-world applications.

"The Databricks Data Science Fundamentals for Data Analysis coursera was outstanding. I found the lessons to be industry relavent, challenging, and fair."

Engaging assignments aid comprehension.

"The quizzes and assignments help a lot!"

"Testing the skills after very session was is a great idea and give good impact on the learning."

Well explained lessons.

"Straightforward and comprehensive - exactly what I needed!"

"Great for beginners, yet as an experimented data scientist, it was refreshing to recall basics of what I love doing the most, while learning a new tool for me."

Peer review can delay certificate acquisition.

"Not satisfied with the peer review process. Delays generation of specialization certificate."

"People also don't provide useful comments if they feel that something is wrong with the submission. This leaves the participant wondering where exactly things went wrong."

Some assignments lack clear instructions.

"The instruction did not match the assessments. If you already know the fundamentals, you can pass the quizzes and assignments. Otherwise, you will struggle significantly."

"some question unclear, some which I struggled due to some subtelty within only to realize that the solution proposed did not answer the question"

Some course content may need to be revised.

"If your goal is to get just basic understanding about Data Science - it will be absolutely fine for you. However you'll find almost nothing about Databricks ML features and runtime used by authors is obsolete and no longer available for selection during cluster configuration in community edition."

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 Data Science Fundamentals for Data Analysts with these activities:

Read: Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Show steps

Develop a foundational understanding of data science concepts and applications.

View Data Science for Business: What You Need to... on Amazon

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Read chapters 1-3 to familiarize yourself with the basics of data science.
Read chapters 4-6 to learn about data mining techniques.
Read chapters 7-9 to understand data-analytic thinking.

Compile a Glossary of Data Science Terms

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Enhance your understanding of key vocabulary and concepts in data science.

Browse courses on Data Science

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Create a spreadsheet or document to store your glossary
Add new terms and definitions as you encounter them in the course materials or other resources
Review and update your glossary regularly

Solve Introductory Statistics Problems

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Sharpen your statistical skills to better understand data distributions and relationships.

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Visit Khan Academy's Introductory Statistics page
Complete the 'Probability and Sampling' module
Complete the 'Hypothesis Testing' module

Five other activities

Expand to see all activities and additional details

Show all eight activities

Join a Study Group for the Course

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Engage in collaborative learning and support with other students taking the same course.

Browse courses on Data Science

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Create a study group with classmates who are also enrolled in the course
Meet regularly to discuss course material, work on assignments, and prepare for exams
Share your knowledge and expertise with other members of the group

Attend a Local Data Science Meetup

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Connect with professionals in the field and stay updated on the latest trends and technologies.

Browse courses on Data Science

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Search for local data science meetups on Meetup.com or Eventbrite
Attend a meetup and introduce yourself to other attendees
Listen to presentations and engage in discussions on current topics in data science

Create a Data Dictionary for a Real-World Dataset

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Develop the ability to organize and document data for effective data analysis.

Browse courses on Data Cleaning

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Choose a publicly available dataset from Kaggle or UCI Machine Learning Repository.
Identify the variables in the dataset and their data types.
Create a data dictionary that describes each variable, including its name, type, format, and any missing values.

Complete the 'Introduction to Machine Learning' Coursera Course

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Expand your understanding of machine learning algorithms and techniques.

Browse courses on Machine Learning

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Enroll in the 'Introduction to Machine Learning' Coursera course
Complete the course modules and assignments
Apply the concepts you learned in the course to solve a real-world problem

Build a Machine Learning Model to Predict Customer Churn

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Apply your data science skills to solve a real-world business problem.

Browse courses on Machine Learning

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Gather data on customer behavior and demographics
Clean and prepare the data
Build and train a machine learning model to predict customer churn
Evaluate the performance of your model
Deploy your model to a production environment

Career center

Learners who complete Data Science Fundamentals for Data Analysts will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist gathers, analyzes, and interprets large sets of data to uncover patterns and trends. They build models to make predictions and solve problems, communicating insights to stakeholders. This course provides a strong foundation in data science concepts, including introductory statistics, machine learning, and data project completion. These skills are essential for aspiring Data Scientists.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, build, and maintain machine learning models. They work closely with Data Scientists to implement models into production systems. This course provides a practical introduction to machine learning, covering essential concepts and techniques. It also emphasizes the importance of project completion, a key skill for Machine Learning Engineers.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use this information to make recommendations and inform decision-making. This course builds upon existing data analysis skills, providing a deeper understanding of data science techniques. It also emphasizes project completion, a crucial skill for Data Analysts.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts bridge the gap between business and technology, translating business requirements into technical specifications. This course provides a solid foundation in data science, enabling Business Analysts to better understand and leverage data in their work. It also emphasizes communication, a key skill for Business Analysts.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, and interpret data to draw conclusions and make predictions. This course provides a strong foundation in introductory statistics, a core skill for Statisticians. It also covers data science concepts such as machine learning and project completion, expanding the skillset of aspiring Statisticians.

See salaries and explore the career path for Statistician

Data Engineer

Data Engineers design, build, and maintain data pipelines and infrastructure. They work with Data Scientists and Data Analysts to ensure data is accessible and reliable for analysis. This course provides a foundational understanding of data science, including data project completion. These skills can complement the technical expertise of aspiring Data Engineers.

See salaries and explore the career path for Data Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. This course provides a solid foundation in data science concepts such as machine learning, which are increasingly used in software development. It also emphasizes project completion, a valuable skill for Software Engineers.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers define and oversee the development of products. This course provides a comprehensive understanding of data science, enabling Product Managers to make data-driven decisions and develop innovative products. It also emphasizes communication, a crucial skill for Product Managers.

See salaries and explore the career path for Product Manager

Consultant

Consultants provide expert advice and guidance to clients on a variety of business issues. This course provides a strong foundation in data science, enabling Consultants to better understand and address the data-related challenges faced by their clients. It also emphasizes communication, a key skill for Consultants.

See salaries and explore the career path for Consultant

Financial Analyst

Financial Analysts analyze financial data to make investment recommendations and inform financial decisions. This course provides a foundational understanding of data science, including introductory statistics and machine learning. These skills can complement the financial expertise of aspiring Financial Analysts.

See salaries and explore the career path for Financial Analyst

Market Researcher

Market Researchers collect and analyze data to understand market trends and consumer behavior. This course provides a solid foundation in data science, including introductory statistics and machine learning. These skills can enhance the research capabilities of aspiring Market Researchers.

See salaries and explore the career path for Market Researcher

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course provides a foundational understanding of data science, including introductory statistics and machine learning. These skills can complement the analytical expertise of aspiring Operations Research Analysts.

See salaries and explore the career path for Operations Research Analyst

Risk Analyst

Risk Analysts identify, assess, and mitigate risks faced by organizations. This course provides a foundational understanding of data science, including introductory statistics and machine learning. These skills can enhance the risk management capabilities of aspiring Risk Analysts.

See salaries and explore the career path for Risk Analyst

Data Visualization Specialist

Data Visualization Specialists create visual representations of data to communicate insights and trends. This course provides a foundational understanding of data science, including introductory statistics and machine learning. These skills can complement the design and communication expertise of aspiring Data Visualization Specialists.

See salaries and explore the career path for Data Visualization Specialist

Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. This course provides a foundational understanding of data science, including introductory statistics and machine learning. These skills can complement the financial expertise of aspiring Quantitative Analysts.

See salaries and explore the career path for Quantitative Analyst

Reading list

We've selected 14 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Science Fundamentals for Data Analysts.

The Elements of Statistical Learning

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A classic textbook in machine learning, providing a comprehensive overview of statistical learning methods, including linear regression, logistic regression, and support vector machines.

The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

The Elements of Statistical Learning: Data Mining,...

Hardcover

$$$

The Elements of Statistical Learning: Data Mining,...

Kindle Edition

$$$

An Introduction to Statistical Learning

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A widely-used textbook for introductory statistics and machine learning, providing a solid foundation in statistical modeling and machine learning algorithms.

Data Science Fundamentals for Data Analysts

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Data science fundamentals for data analysts

Activities

Career center

Reading list

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