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    • Applied Data Science

    Applied Data Science Courses Online

    Master applied data science techniques for real-world problem-solving. Learn data manipulation, visualization, and machine learning using Python.

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    Explore the Applied Data Science Course Catalog

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Requirements Gathering for Secure Software Development

      Skills you'll gain: Requirements Analysis, User Requirements Documents, Software Development Methodologies, Requirements Elicitation, Agile Methodology, Functional Requirement, Software Design Documents, System Requirements, Software Development Life Cycle, Verification And Validation, Technical Communication

      4.6
      Rating, 4.6 out of 5 stars
      ·
      682 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      C

      Cloudera

      Analyzing Big Data with SQL

      Skills you'll gain: SQL, Apache Hive, Big Data, MySQL, Query Languages, Databases, Apache Hadoop, PostgreSQL, Data Manipulation, Data Analysis, Virtual Machines

      4.8
      Rating, 4.8 out of 5 stars
      ·
      529 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      R

      Rice University

      Algorithmic Thinking (Part 1)

      Skills you'll gain: Graph Theory, Algorithms, Computational Thinking, Data Analysis, Data Structures, Theoretical Computer Science, Network Analysis, Analysis, Python Programming, Computer Programming

      4.6
      Rating, 4.6 out of 5 stars
      ·
      382 reviews

      Intermediate · Course · 1 - 4 Weeks

    • L

      LearnQuest

      Fundamentals of Kubernetes Deployment

      Skills you'll gain: Kubernetes, Application Deployment, Containerization, Authentications, Authorization (Computing), Cloud Computing, Software Installation, Infrastructure Architecture, Cloud Computing Architecture, Scalability, Data Storage, Command-Line Interface

      4.3
      Rating, 4.3 out of 5 stars
      ·
      321 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Colorado Boulder

      Statistical Inference for Estimation in Data Science

      Skills you'll gain: Statistical Inference, Statistical Methods, Probability & Statistics, Statistical Modeling, Sampling (Statistics), Statistical Analysis, Data Science, Probability Distribution

      4.1
      Rating, 4.1 out of 5 stars
      ·
      88 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of California San Diego

      Genome Sequencing (Bioinformatics II)

      Skills you'll gain: Bioinformatics, Graph Theory, Molecular Biology, Microbiology, Pharmacology, Infectious Diseases, Computational Thinking, Applied Mathematics, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      318 reviews

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Toronto

      Bioinformatic Methods II

      Skills you'll gain: Bioinformatics, Molecular Biology, Network Analysis, Data Analysis, Big Data, Data Visualization Software, Scientific Visualization, Structural Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      486 reviews

      Beginner · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      G

      Georgia Institute of Technology

      System Issues in Cloud Computing

      Skills you'll gain: Cloud Applications, Cloud Development, Cloud-Native Computing, Software-Defined Networking, Cloud Computing, Cloud Infrastructure, Distributed Computing, Application Development, Cloud Management, Virtualization, Virtual Machines, Cloud Computing Architecture, Network Performance Management, Data Store, Network Architecture, Multi-Tenant Cloud Environments, Network Monitoring, Network Infrastructure, Computer Networking, Data Centers

      4.5
      Rating, 4.5 out of 5 stars
      ·
      397 reviews

      Beginner · Specialization · 3 - 6 Months

    • U

      University of California, Santa Cruz

      Children Acquiring Literacy Naturally

      Skills you'll gain: Literacy, Demography, Child Development, Human Learning, Working With Children, Language Learning, Childhood Education and Development, Learning Theory, Education Software and Technology, Liberal Arts, Vocabulary, Research

      4.5
      Rating, 4.5 out of 5 stars
      ·
      185 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Colorado System

      Cryptography and Information Theory

      Skills you'll gain: Cryptography, Cryptographic Protocols, Encryption, Key Management, Cybersecurity, Computer Security, Theoretical Computer Science

      4.5
      Rating, 4.5 out of 5 stars
      ·
      518 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      U

      University of Minnesota

      Nearest Neighbor Collaborative Filtering

      Skills you'll gain: AI Personalization, Machine Learning Algorithms, Predictive Modeling, Applied Machine Learning, Data Mining, Algorithms

      4.3
      Rating, 4.3 out of 5 stars
      ·
      304 reviews

      Mixed · Course · 1 - 3 Months

    • M

      Microsoft

      Microsoft Power Platform Fundamentals

      Skills you'll gain: Microsoft Power Platform, Power BI, Microsoft Power Automate/Flow, Dashboard, Data Visualization, Business Process Automation, Business Intelligence, Workflow Management, Application Development, ChatGPT, Data Analysis Software, Customer Engagement

      4.3
      Rating, 4.3 out of 5 stars
      ·
      152 reviews

      Beginner · Course · 1 - 3 Months

    Applied Data Science learners also search

    Data Science
    R
    Data
    Beginner Data Science
    Data Science Projects
    Data Analytics
    Advanced Data Science
    Data Analysis
    1…187188189…834

    In summary, here are 10 of our most popular applied data science courses

    • Requirements Gathering for Secure Software Development: University of Colorado System
    • Analyzing Big Data with SQL: Cloudera
    • Algorithmic Thinking (Part 1): Rice University
    • Fundamentals of Kubernetes Deployment: LearnQuest
    • Statistical Inference for Estimation in Data Science: University of Colorado Boulder
    • Genome Sequencing (Bioinformatics II): University of California San Diego
    • Bioinformatic Methods II: University of Toronto
    • System Issues in Cloud Computing: Georgia Institute of Technology
    • Children Acquiring Literacy Naturally: University of California, Santa Cruz
    • Cryptography and Information Theory: University of Colorado System

    Frequently Asked Questions about Applied Data Science

    People who are best suited for working in data science have a strong mix of technical skills and complex problem-solving skills. Beyond the job-related skills, people should have strong critical reasoning abilities, which are needed to help them analyze data and solve problems. Creativity, attention to detail, and strong communication skills allow data scientists to translate their analytical findings into actions that business leaders and decision-makers can take. Because this field continues evolving, people in data science should also be enthusiastic about learning new things and willing to constantly expand their skills.‎

    Are you passionate about using data to solve complex problems? Do you enjoy working in both the business and technology fields? Do you have a thirst for learning new things? If you can answer yes to any or all of those questions, learning data science may well be an ideal course for you. Additionally, if you're looking for a field that's in high demand and applicable to a variety of potential positions, it's hard to top data science. It's among the fastest-growing fields, and by 2026 it's predicted to create more than 11 million new jobs, according to the Bureau of Labor Statistics.‎

    Data science opens up a variety of potential career paths, including data scientist, machine learning engineer, data architect, and business intelligence developer. Most people who work in data science start with entry-level jobs like junior data scientist or data analyst after earning a bachelor's degree in computer science or a related field. Some people work their way up from entry-level jobs. Others pursue certifications or trainings specific to systems. To access the largest pool of opportunities, you might want to get a master's or doctoral degree in information technology or computer science.‎

    Data scientists work in a variety of industries, including big tech companies like Google and IBM, financial organizations, pharmaceutical companies, retailers, and even fashion houses. Data scientists work on many different types of jobs, which makes their work valuable to many different types of industries. For example, data scientists might work in fraud identification, market analysis, or manufacturing analysis. Or they might work on projects that task them with analyzing large amounts of data and putting it into reports and dashboards to help stakeholders better understand the significance. Data science can be helpful for marketing, sales, and so much more.‎

    Online Applied Data Science courses offer a convenient and flexible way to enhance your existing knowledge or learn new Applied Data Science skills. With a wide range of Applied Data Science classes, you can conveniently learn at your own pace to advance your Applied Data Science career skills.‎

    When looking to enhance your workforce's skills in Applied Data Science, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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