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
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Data Science Fundamentals Specialization
Gain an overview of data science fundamentals.
Instructor: Julie Pai
6,965 already enrolled
Included with 
Get in-depth knowledge of a subject
4.3
(161 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
4.3
(161 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
- Regression Analysis
- Analytics
- Decision Tree Learning
- Classification And Regression Tree (CART)
- Unsupervised Learning
- Data Analysis
- Text Mining
- Statistical Modeling
- Statistical Analysis
- Cloud Computing
- Data Science
- Big Data
- Natural Language Processing
- Social Media
- Predictive Modeling
- Data Mining
- Anomaly Detection
- Business Analytics
- Data Ethics
- Predictive Analytics
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
Category: Predictive Analytics
Category: Business Intelligence
Category: Data Science
Category: Data Mining
Category: Data Processing
Category: Data-Driven Decision-Making
Category: Data Ethics
Category: Data Analysis
Category: Big Data
Category: Business Analytics
Category: Descriptive Analytics
Category: Data Literacy
Category: Analytics
Category: Small Data
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
Category: Regression Analysis
Category: Predictive Modeling
Category: Supervised Learning
Category: Decision Tree Learning
Category: Classification And Regression Tree (CART)
Category: Predictive Analytics
Category: Statistical Modeling
Category: Data Analysis
Category: Unsupervised Learning
Category: Forecasting
Category: Machine Learning
Category: Time Series Analysis and Forecasting
Category: Statistical Analysis
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
Category: Unsupervised Learning
Category: Regression Analysis
Category: Correlation Analysis
Category: Predictive Modeling
Category: Classification And Regression Tree (CART)
Category: Anomaly Detection
Category: Probability & Statistics
Category: AI Personalization
Category: Scatter Plots
Category: Data Analysis
Category: Cross Selling
Category: Predictive Analytics
Category: Supervised Learning
Category: Statistical Analysis
Category: Market Analysis
Category: Statistical Modeling
Category: Machine Learning
Category: 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
Category: Deep Learning
Category: Predictive Modeling
Category: Machine Learning Methods
Category: Social Media
Category: Geospatial Information and Technology
Category: Data Analysis
Category: Big Data
Category: Analytics
Category: Internet Of Things
Category: Business Intelligence
Category: Unstructured Data
Category: Natural Language Processing
Category: Cloud Computing
Category: Text Mining
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 Courses18,329 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.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
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.
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