This specialization demystifies data science and familiarizes learners with key data science skills, techniques, and concepts. The course begins with foundational concepts such as analytics taxonomy, the Cross-Industry Standard Process for Data Mining, and data diagnostics, and then moves on to compare data science with classical statistical techniques. The course also provides an overview of the most common techniques used in data science, including data analysis, statistical modeling, data engineering, manipulation of data at scale (big data), algorithms for data mining, data quality, remediation and consistency operations.
Data Science Fundamentals Specialization
Data Science Fundamentals Specialization
Gain an overview of data science fundamentals.
Instructor: Julie Pai
Included with 
Get in-depth knowledge of a subject
(163 reviews)
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(163 reviews)
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Skills you'll gain
- Data Mining
- Predictive Modeling
- Anomaly Detection
- Cloud Computing
- Data Science
- Unsupervised Learning
- Classification And Regression Tree (CART)
- Predictive Analytics
- Analytical Skills
- Data Ethics
- Business Analytics
- Data Strategy
- Social Media
- Data Analysis
- Statistical Modeling
- Statistical Analysis
- Regression Analysis
- Text Mining
- Decision Tree Learning
- Natural Language Processing
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
8 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from University of California, Irvine
Specialization - 4 course series
What you'll learn
The knowledge and skills needed to work in the data science profession
How data science is used to solve business problems
The benefits of using the cross-industry standard process for data mining (CRISP-DM)
Skills you'll gain
Predictive Analytics, Data Science, Business Intelligence, Data Mining, Data Processing, Data Ethics, Data Analysis, Big Data, Business Analytics, Analytical Skills, Descriptive Analytics, Small Data, Data Strategy, and Analytics
What you'll learn
The application of predictive modeling to professional and academic work
Applications of classification analysis: decision trees
Applications of regression analysis (linear and logistic)
Skills you'll gain
Regression Analysis, Predictive Modeling, Supervised Learning, Classification And Regression Tree (CART), Decision Tree Learning, Predictive Analytics, Time Series Analysis and Forecasting, Statistical Analysis, Unsupervised Learning, Statistical Modeling, Machine Learning, Data Analysis, and Forecasting
What you'll learn
Cluster analysis and segmentation
Collaborative filtering and market basket analysis
Applications of classification- and regression-type prediction models
Skills you'll gain
Regression Analysis, Correlation Analysis, Unsupervised Learning, Scatter Plots, Fraud detection, Predictive Analytics, Predictive Modeling, Classification And Regression Tree (CART), Cross Selling, Data Analysis, Anomaly Detection, Machine Learning, Market Analysis, Supervised Learning, Statistical Analysis, and Data Mining
What you'll learn
Applications of natural language processing
Basics of social media analytics
Future trends and possibilities in data science
Skills you'll gain
Text Mining, Geospatial Information and Technology, Machine Learning Methods, Deep Learning, Business Intelligence, Predictive Modeling, Analytics, Unstructured Data, Natural Language Processing, Social Media, Cloud Computing, Data Analysis, Big Data, and Internet Of Things
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor
5 Courses18,695 learners
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Frequently asked questions
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions
Financial aid available,