We may earn an affiliate commission when you visit our partners.
Course image
Megan Smith Branch, Stacey McBrine, and Sarah Haq

The field of Data Science has topped the Linked In Emerging Jobs list for the last 3 years with a projected growth of 28% annually and the World Economic Forum lists Data Analytics and Scientists as the top emerging job for 2022.

Read more

The field of Data Science has topped the Linked In Emerging Jobs list for the last 3 years with a projected growth of 28% annually and the World Economic Forum lists Data Analytics and Scientists as the top emerging job for 2022.

Data can reveal insights and inform business—by guiding decisions and influencing day-to-day operations. This specialization will teach learners how to analyze, understand, manipulate, and present data within an effective and repeatable process framework and will enable you to bring value to the business by putting data science concepts into practice.

This course is designed for business professionals that want to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.

Certified Data Science Practitioner (CDSP) will prepare learners for the CertNexus CDSP certification exam.

To complete your journey to the CDSP Certification

Complete the Coursera Certified Data Science Practitioner Professional Certificate. Review the CDSP Exam Blueprint. Purchase your CDSP Exam Voucher. Register for your CDSP Exam.

Enroll now

Share

Help others find Specialization from Coursera by sharing it with your friends and followers:

What's inside

Five courses

Address Business Issues with Data Science

(0 hours)
This course is designed for business professionals who want to learn how to determine if a business issue is appropriate for a data science project and apply the data science process.

Extract, Transform, and Load Data

(0 hours)
This course teaches business and data professionals the first technical phase of the data science process known as Extract, Transform and Load (ETL). Learners will collect data from multiple sources, transform and clean it, and load it into its ultimate destination for analysis and modeling. Students should have experience working with data and aptitude with computer programming.

Analyze Data

(0 hours)
This course is designed for business professionals that want to learn how to analyze data to gain insight, use statistical analysis methods to explore the underlying distribution of data, use visualizations such as histograms, scatter plots, and maps to analyze data and preprocess data to produce a dataset ready for training.

Train Machine Learning Models

(0 hours)
This course introduces business professionals to machine learning concepts. Learners will test model hypothesis, train, tune, and evaluate models using algorithms that solve classification, regression, forecasting, and clustering problems.

Finalize a Data Science Project

(0 hours)
This course teaches business professionals how to gather results from previous stages of a data science project and present them to stakeholders. Learners will communicate the results of a model to stakeholders, build a basic web app to demonstrate machine learning models, and implement and test pipelines that automate the model training, tuning, and deployment processes.

Save this collection

Save CertNexus Certified Data Science Practitioner to your list so you can find it easily later:
Save
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser